In today’s rapidly evolving digital landscape,web application security has become paramount as organizations face increasingly sophisticated cyber threats.This work presents a comprehensive methodology for implementi...In today’s rapidly evolving digital landscape,web application security has become paramount as organizations face increasingly sophisticated cyber threats.This work presents a comprehensive methodology for implementing robust security measures in modern web applications and the proof of the Methodology applied to Vue.js,Spring Boot,and MySQL architecture.The proposed approach addresses critical security challenges through a multi-layered framework that encompasses essential security dimensions including multi-factor authentication,fine-grained authorization controls,sophisticated session management,data confidentiality and integrity protection,secure logging mechanisms,comprehensive error handling,high availability strategies,advanced input validation,and security headers implementation.Significant contributions are made to the field of web application security.First,a detailed catalogue of security requirements specifically tailored to protect web applications against contemporary threats,backed by rigorous analysis and industry best practices.Second,the methodology is validated through a carefully designed proof-of-concept implementation in a controlled environment,demonstrating the practical effectiveness of the security measures.The validation process employs cutting-edge static and dynamic analysis tools for comprehensive dependency validation and vulnerability detection,ensuring robust security coverage.The validation results confirm the prevention and avoidance of security vulnerabilities of the methodology.A key innovation of this work is the seamless integration of DevSecOps practices throughout the secure Software Development Life Cycle(SSDLC),creating a security-first mindset from initial design to deployment.By combining proactive secure coding practices with defensive security approaches,a framework is established that not only strengthens application security but also fosters a culture of security awareness within development teams.This hybrid approach ensures that security considerations are woven into every aspect of the development process,rather than being treated as an afterthought.展开更多
The secured access is studied in this paper for the network of the image remote sensing.Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sens...The secured access is studied in this paper for the network of the image remote sensing.Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection point.In order to enhance the sensing quality for the remote uploading,the passive reflection surface technique is employed.If one eavesdropper that exists nearby this sensor is keeping on accessing the same networks,he may receive the same image from this sensor.Our goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing images.In order to achieve this goal,the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading coefficients.Based on this theoretical result,the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper sensor.Finally,the analytical expression is theoretically derived for the optimum uploading power.Numerical simulations verify the design approach.展开更多
Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving ...Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage problems.However,the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless channel.This paper considers a UAV-MEC secure network based on NOMA technology,which aims to minimize the UAV energy consumption.To achieve the purpose while meeting the security and users’latency requirements,we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network resources.Given that the original problem is non-convex and multivariate coupled,we proposed an effective algorithm to decouple the nonconvex problem into independent user relation coefficients and subproblems based on successive convex approximation(SCA)and block coordinate descent(BCD).The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.展开更多
As industrialization and informatization in China deeply integrate and the Internet of Things rapidly develops,industrial control systems are facing increasingly severe information security challenges.The industrial c...As industrialization and informatization in China deeply integrate and the Internet of Things rapidly develops,industrial control systems are facing increasingly severe information security challenges.The industrial control system of the gas extraction plant is characterized by numerous points and centralized operations,with a strong reliance on the system and stringent real-time requirements.展开更多
In wireless Energy Harvesting(EH)cooperative networks,we investigate the problem of secure energy-saving resource allocation for downlink physical layer security transmission.Initially,we establish a model for a multi...In wireless Energy Harvesting(EH)cooperative networks,we investigate the problem of secure energy-saving resource allocation for downlink physical layer security transmission.Initially,we establish a model for a multi-relay cooperative network incorporating wireless energy harvesting,spectrum sharing,and system power constraints,focusing on physical layersecurity transmission in the presence of eavesdropping nodes.In this model,the source node transmits signals while injecting Artificial Noise(AN)to mitigate eavesdropping risks,and an idle relay can act as a jamming node to assist in this process.Based on this model,we formulate an optimization problem for maximizing system secure harvesting energy efficiency,this problem integrates constraints on total power,bandwidth,and AN allocation.We proceed by conducting a mathematical analysis of the optimization problem,deriving optimal solutions for secure energy-saving resource allocation,this includes strategies for power allocation at the source and relay nodes,bandwidth allocation among relays,and power splitting for the energy harvesting node.Thus,we propose a secure resource allocation algorithm designed to maximize secure harvesting energy efficiency.Finally,we validate the correctness of the theoretical derivation through Monte Carlo simulations,discussing the impact of parameters such as legitimate channel gain,power splitting factor,and the number of relays on secure harvesting energy efficiency of the system.The simulation results show that the proposed secure energy-saving resource allocation algorithm effectively enhances the security performance of the system.展开更多
In this paper,the application of Non-Orthogonal Multiple Access(NOMA)is investigated in a multiple-input single-output network consisting of multiple legitimate users and a potential eavesdropper.To support secure tra...In this paper,the application of Non-Orthogonal Multiple Access(NOMA)is investigated in a multiple-input single-output network consisting of multiple legitimate users and a potential eavesdropper.To support secure transmissions from legitimate users,two NOMA Secrecy Sum Rate Transmit Beam Forming(NOMA-SSR-TBF)schemes are proposed to maximise the SSR of a Base Station(BS)with sufficient and insufficient transmit power.For BS with sufficient transmit power,an artificial jamming beamforming design scheme is proposed to disrupt the potential eavesdropping without impacting the legitimate transmissions.In addition,for BS with insufficient transmit power,a modified successive interference cancellation decoding sequence is used to reduce the impact of artificial jamming on legitimate transmissions.More specifically,iterative algorithm for the successive convex approximation are provided to jointly optimise the vectors of transmit beamforming and artificial jamming.Experimental results demonstrate that the proposed NOMA-SSR-TBF schemes outperforms the existing works,such as the maximized artificial jamming power scheme,the maximized artificial jamming power scheme with artificial jamming beamforming design and maximized secrecy sum rate scheme without artificial jamming beamforming design.展开更多
Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deplo...Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deployment.Diffusion model-based methods face security vulnerabilities,particularly due to potential information leakage during generation.We propose a fixed neural network image steganography framework based on secure diffu-sion models to address these challenges.Unlike conventional approaches,our method minimizes cover modifications through neural network optimization,achieving superior steganographic performance in human visual perception and computer vision analyses.The cover images are generated in an anime style using state-of-the-art diffusion models,ensuring the transmitted images appear more natural.This study introduces fixed neural network technology that allows senders to transmit only minimal critical information alongside stego-images.Recipients can accurately reconstruct secret images using this compact data,significantly reducing transmission overhead compared to conventional deep steganography.Furthermore,our framework innovatively integrates ElGamal,a cryptographic algorithm,to protect critical information during transmission,enhancing overall system security and ensuring end-to-end information protection.This dual optimization of payload reduction and cryptographic reinforcement establishes a new paradigm for secure and efficient image steganography.展开更多
The performance of traditional regular Intelligent Reflecting Surface(IRS)improves as the number of IRS elements increases,but more reflecting elements lead to higher IRS power consumption and greater overhead of chan...The performance of traditional regular Intelligent Reflecting Surface(IRS)improves as the number of IRS elements increases,but more reflecting elements lead to higher IRS power consumption and greater overhead of channel estimation.The Irregular Intelligent Reflecting Surface(IIRS)can enhance the performance of the IRS as well as boost the system performance when the number of reflecting elements is limited.However,due to the lack of radio frequency chain in IRS,it is challenging for the Base Station(BS)to gather perfect Channel State Information(CSI),especially in the presence of Eavesdroppers(Eves).Therefore,in this paper we investigate the minimum transmit power problem of IIRS-aided Simultaneous Wireless Information and Power Transfer(SWIPT)secure communication system with imperfect CSI of BS-IIRS-Eves links,which is subject to the rate outage probability constraints of the Eves,the minimum rate constraints of the Information Receivers(IRs),the energy harvesting constraints of the Energy Receivers(ERs),and the topology matrix constraints.Afterward,the formulated nonconvex problem can be efficiently tackled by employing joint optimization algorithm combined with successive refinement method and adaptive topology design method.Simulation results demonstrate the effectiveness of the proposed scheme and the superiority of IIRS.展开更多
Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third...Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a designed multi-attention mechanism focuses on important local features during the feature extraction stage. Moreover, a triplet loss function is utilized to learn discriminative hash codes to construct a compact and efficient triplet deep hashing. Finally, upsampling is used to restore the original resolution of the images during retrieval, thereby enabling more accurate matching. To ensure the security of medical image data, a lightweight image encryption method based on frequency domain encryption is designed to encrypt the chest X-ray images. The findings of the experiment indicate that, in comparison to various advanced image retrieval techniques, the suggested approach improves the precision of feature extraction and retrieval using the COVIDx dataset. Additionally, it offers enhanced protection for the confidentiality of medical images stored in cloud settings and demonstrates strong practicality.展开更多
Continuous-variable quantum secure direct communication(CVQSDC)with Gaussian modulation(GM)demands a considerable quantity of random numbers during the preparation process and encodes them separately on the quadrature...Continuous-variable quantum secure direct communication(CVQSDC)with Gaussian modulation(GM)demands a considerable quantity of random numbers during the preparation process and encodes them separately on the quadrature components of the quantum states.Hence,high-speed random number generators are required to satisfy this demand,which is difficult to implement in practical applications.CVQSDC with discrete modulation(DM),correspondingly,employs a finite number of quantum states to achieve encoding,which can circumvent the shortcomings of the GM scheme.Based on the advantages of DM,the issue of attaining the most optimal secrecy capacity and communication distance remains to be resolved.Here,we propose a CVQSDC protocol based on N-symbol amplitude phase shift keying(N-APSK),which exploits the Boltzmann-Maxwell distribution assisted probability shaping technique.In comparison with the uniform distribution,according to 32-APSK CVQSDC,the proposed scheme extends the communication distance by about 38%,while obtaining a higher secrecy capacity at the same communication distance.Furthermore,increasing the value of N will concurrently increase the quantity of rings in the constellation,thereby facilitating enhancements of communication distance.This work incorporates the modulation approaches prevalently employed in classical communication into the realm of quantum communication,attaining gratifying advancements in communication distance and secrecy capacity,and concurrently facilitating the integrated development of quantum communication and classical communication.展开更多
Integrating Artificial Intelligence of Things(AIoT)in healthcare offers transformative potential for real-time diagnostics and collaborative learning but presents critical challenges,including privacy preservation,com...Integrating Artificial Intelligence of Things(AIoT)in healthcare offers transformative potential for real-time diagnostics and collaborative learning but presents critical challenges,including privacy preservation,computational efficiency,and regulatory compliance.Traditional approaches,such as differential privacy,homomorphic encryption,and secure multi-party computation,often fail to balance performance and privacy,rendering them unsuitable for resource-constrained healthcare AIoT environments.This paper introduces LMSA(Lightweight Multi-Key Secure Aggregation),a novel framework designed to address these challenges and enable efficient,secure federated learning across distributed healthcare institutions.LMSA incorporates three key innovations:(1)a lightweight multikey management system leveraging Diffie-Hellman key exchange and SHA3-256 hashing,achieving O(n)complexity with AES(Advanced Encryption Standard)-256-level security;(2)a privacy-preserving aggregation protocol employing hardware-accelerated AES-CTR(CounTeR)encryption andmodular arithmetic for securemodel weight combination;and(3)a resource-optimized implementation utilizing AES-NI(New Instructions)instructions and efficient memory management for real-time operations on constrained devices.Experimental evaluations using the National Institutes of Health(NIH)Chest X-ray dataset demonstrate LMSA’s ability to train multi-label thoracic disease prediction models with Vision Transformer(ViT),ResNet-50,and MobileNet architectures across distributed healthcare institutions.Memory usage analysis confirmed minimal overhead,with ViT(327.30 MB),ResNet-50(89.87 MB),and MobileNet(8.63 MB)maintaining stable encryption times across communication rounds.LMSA ensures robust security through hardware acceleration,enabling real-time diagnostics without compromising patient confidentiality or regulatory compliance.Future research aims to optimize LMSA for ultra-low-power devices and validate its scalability in heterogeneous,real-world environments.LMSA represents a foundational advancement for privacy-conscious healthcare AI applications,bridging the gap between privacy and performance.展开更多
Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade...Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols.展开更多
Semantic secure communication is an emerging field that combines the principles of source-channel coding with the need for secure data transmission.It is of great significance in modern communications to protect the c...Semantic secure communication is an emerging field that combines the principles of source-channel coding with the need for secure data transmission.It is of great significance in modern communications to protect the confidentiality and privacy of sensitive information and prevent information leaks and malicious attacks.This paper presents a novel approach to semantic secure communication through the utilization of joint source-channel coding,which is based on the design of an automated joint source-channel coding algorithm and an encryption and decryption algorithm based on semantic security.The traditional and state-of-the-art joint source-channel coding algorithms are selected as two baselines for different comparison purposes.Experimental results demonstrate that our proposed algorithm outperforms the first baseline algorithm,the traditional source-channel coding,by 61.21%in efficiency under identical channel conditions(SNR=15 dB).In security,our proposed method can resist 2 more types of attacks compared to the two baselines,exhibiting nearly no increases in time consumption and error rate compared to the state-of-the-art joint source-channel coding algorithm while the secure semantic communication is supported.展开更多
Join CEN as the lead rapporteur of this initiative takes you inside the development of the European harmonized standards for smartcards,similar devices,and secure elements.This session will provide exclusive insights ...Join CEN as the lead rapporteur of this initiative takes you inside the development of the European harmonized standards for smartcards,similar devices,and secure elements.This session will provide exclusive insights into the current content and approach shaping the compliance criteria needed to meet the essential requirements of the Cyber Resilience Act(EU 2024/2847).展开更多
As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and use...As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.展开更多
The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of user...The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.展开更多
The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-inpu...The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.展开更多
Ensuring the integrity and confidentiality of patient medical information is a critical priority in the healthcare sector.In the context of security,this paper proposes a novel encryption algorithm that integrates Blo...Ensuring the integrity and confidentiality of patient medical information is a critical priority in the healthcare sector.In the context of security,this paper proposes a novel encryption algorithm that integrates Blockchain technology,aiming to improve the security and privacy of transmitted data.The proposed encryption algorithm is a block-cipher image encryption scheme based on different chaotic maps:The logistic Map,the Tent Map,and the Henon Map used to generate three encryption keys.The proposed block-cipher system employs the Hilbert curve to perform permutation while a generated chaos-based S-Box is used to perform substitution.Furthermore,the integration of a Blockchain-based solution for securing data transmission and communication between nodes and authenticating the encrypted medical image’s authenticity adds a layer of security to our proposed method.Our proposed cryptosystem is divided into two principal modules presented as a pseudo-random number generator(PRNG)used for key generation and an encryption and decryption system based on the properties of confusion and diffusion.The security analysis and experimental tests for the proposed algorithm show that the average value of the information entropy of the encrypted images is 7.9993,the Number of Pixels Change Rate(NPCR)values are over 99.5%and the Unified Average Changing Intensity(UACI)values are greater than 33%.These results prove the strength of our proposed approach,demonstrating that it can significantly enhance the security of encrypted images.展开更多
Cloud storage,a core component of cloud computing,plays a vital role in the storage and management of data.Electronic Health Records(EHRs),which document users’health information,are typically stored on cloud servers...Cloud storage,a core component of cloud computing,plays a vital role in the storage and management of data.Electronic Health Records(EHRs),which document users’health information,are typically stored on cloud servers.However,users’sensitive data would then become unregulated.In the event of data loss,cloud storage providers might conceal the fact that data has been compromised to protect their reputation and mitigate losses.Ensuring the integrity of data stored in the cloud remains a pressing issue that urgently needs to be addressed.In this paper,we propose a data auditing scheme for cloud-based EHRs that incorporates recoverability and batch auditing,alongside a thorough security and performance evaluation.Our scheme builds upon the indistinguishability-based privacy-preserving auditing approach proposed by Zhou et al.We identify that this scheme is insecure and vulnerable to forgery attacks on data storage proofs.To address these vulnerabilities,we enhanced the auditing process using masking techniques and designed new algorithms to strengthen security.We also provide formal proof of the security of the signature algorithm and the auditing scheme.Furthermore,our results show that our scheme effectively protects user privacy and is resilient against malicious attacks.Experimental results indicate that our scheme is not only secure and efficient but also supports batch auditing of cloud data.Specifically,when auditing 10,000 users,batch auditing reduces computational overhead by 101 s compared to normal auditing.展开更多
文摘In today’s rapidly evolving digital landscape,web application security has become paramount as organizations face increasingly sophisticated cyber threats.This work presents a comprehensive methodology for implementing robust security measures in modern web applications and the proof of the Methodology applied to Vue.js,Spring Boot,and MySQL architecture.The proposed approach addresses critical security challenges through a multi-layered framework that encompasses essential security dimensions including multi-factor authentication,fine-grained authorization controls,sophisticated session management,data confidentiality and integrity protection,secure logging mechanisms,comprehensive error handling,high availability strategies,advanced input validation,and security headers implementation.Significant contributions are made to the field of web application security.First,a detailed catalogue of security requirements specifically tailored to protect web applications against contemporary threats,backed by rigorous analysis and industry best practices.Second,the methodology is validated through a carefully designed proof-of-concept implementation in a controlled environment,demonstrating the practical effectiveness of the security measures.The validation process employs cutting-edge static and dynamic analysis tools for comprehensive dependency validation and vulnerability detection,ensuring robust security coverage.The validation results confirm the prevention and avoidance of security vulnerabilities of the methodology.A key innovation of this work is the seamless integration of DevSecOps practices throughout the secure Software Development Life Cycle(SSDLC),creating a security-first mindset from initial design to deployment.By combining proactive secure coding practices with defensive security approaches,a framework is established that not only strengthens application security but also fosters a culture of security awareness within development teams.This hybrid approach ensures that security considerations are woven into every aspect of the development process,rather than being treated as an afterthought.
基金supported in part by Jiangsu Province High Level“333”Program (0401206044)National Natural Science Foundation of China (61801243,62072255)+4 种基金Program for Scientific Research Foundation for Talented Scholars of Jinling Institute of Technology (JIT-B-202031)University Incubator Foundation of Jinling Institute of Technology (JIT-FHXM-202110)Open Project of Fujian Provincial Key Lab.of Network Security and Cryptology (NSCL-KF2021-02)Open Foundation of National Railway Intelligence Transportation System Engineering Tech.Research Center (RITS2021KF02)China Postdoctoral Science Foundation (2019M651914)。
文摘The secured access is studied in this paper for the network of the image remote sensing.Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection point.In order to enhance the sensing quality for the remote uploading,the passive reflection surface technique is employed.If one eavesdropper that exists nearby this sensor is keeping on accessing the same networks,he may receive the same image from this sensor.Our goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing images.In order to achieve this goal,the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading coefficients.Based on this theoretical result,the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper sensor.Finally,the analytical expression is theoretically derived for the optimum uploading power.Numerical simulations verify the design approach.
基金supported in part by the National Natural Science Foundation of China under Grant 61971474in part by the National Natural Science Foundation of China under Grant 62301594+2 种基金in part by the Special Funds of the National Natural Science Foundation of China under Grant 62341112in part by the Beijing Nova Program under Grant Z201100006820121in part by the Beijing Municipal Science and Technology Project under Grant Z181100003218015.
文摘Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage problems.However,the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless channel.This paper considers a UAV-MEC secure network based on NOMA technology,which aims to minimize the UAV energy consumption.To achieve the purpose while meeting the security and users’latency requirements,we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network resources.Given that the original problem is non-convex and multivariate coupled,we proposed an effective algorithm to decouple the nonconvex problem into independent user relation coefficients and subproblems based on successive convex approximation(SCA)and block coordinate descent(BCD).The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.
文摘As industrialization and informatization in China deeply integrate and the Internet of Things rapidly develops,industrial control systems are facing increasingly severe information security challenges.The industrial control system of the gas extraction plant is characterized by numerous points and centralized operations,with a strong reliance on the system and stringent real-time requirements.
基金supported by the National Natural Science Foundation of China(NSFC)[grant numbers 62171188]the Guangdong Provincial Key Laboratory of Human Digital Twin[Grant 2022B1212010004].
文摘In wireless Energy Harvesting(EH)cooperative networks,we investigate the problem of secure energy-saving resource allocation for downlink physical layer security transmission.Initially,we establish a model for a multi-relay cooperative network incorporating wireless energy harvesting,spectrum sharing,and system power constraints,focusing on physical layersecurity transmission in the presence of eavesdropping nodes.In this model,the source node transmits signals while injecting Artificial Noise(AN)to mitigate eavesdropping risks,and an idle relay can act as a jamming node to assist in this process.Based on this model,we formulate an optimization problem for maximizing system secure harvesting energy efficiency,this problem integrates constraints on total power,bandwidth,and AN allocation.We proceed by conducting a mathematical analysis of the optimization problem,deriving optimal solutions for secure energy-saving resource allocation,this includes strategies for power allocation at the source and relay nodes,bandwidth allocation among relays,and power splitting for the energy harvesting node.Thus,we propose a secure resource allocation algorithm designed to maximize secure harvesting energy efficiency.Finally,we validate the correctness of the theoretical derivation through Monte Carlo simulations,discussing the impact of parameters such as legitimate channel gain,power splitting factor,and the number of relays on secure harvesting energy efficiency of the system.The simulation results show that the proposed secure energy-saving resource allocation algorithm effectively enhances the security performance of the system.
基金supported in part by the Natural Science Foundation of Fujian Province under Grant 2022J01169the Local Science and Technology Development of Fujian Province under Grant 2021L3010+3 种基金the Key Project of Science and Technology Innovation of Fujian Province under Grant 2021G02006the National Natural Science Foundation of China under Grants 61971360 and 62271420the National Natural Science Foundation of China under Grant 62071247the Urban Carbon Neutral Science and Technology Innovation Fund Project of Beijing University of Technology ($040000514122607$)。
文摘In this paper,the application of Non-Orthogonal Multiple Access(NOMA)is investigated in a multiple-input single-output network consisting of multiple legitimate users and a potential eavesdropper.To support secure transmissions from legitimate users,two NOMA Secrecy Sum Rate Transmit Beam Forming(NOMA-SSR-TBF)schemes are proposed to maximise the SSR of a Base Station(BS)with sufficient and insufficient transmit power.For BS with sufficient transmit power,an artificial jamming beamforming design scheme is proposed to disrupt the potential eavesdropping without impacting the legitimate transmissions.In addition,for BS with insufficient transmit power,a modified successive interference cancellation decoding sequence is used to reduce the impact of artificial jamming on legitimate transmissions.More specifically,iterative algorithm for the successive convex approximation are provided to jointly optimise the vectors of transmit beamforming and artificial jamming.Experimental results demonstrate that the proposed NOMA-SSR-TBF schemes outperforms the existing works,such as the maximized artificial jamming power scheme,the maximized artificial jamming power scheme with artificial jamming beamforming design and maximized secrecy sum rate scheme without artificial jamming beamforming design.
基金supported in part by the National Natural Science Foundation of China under Grants 62102450,62272478 and the Independent Research Project of a Certain Unit under Grant ZZKY20243127。
文摘Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deployment.Diffusion model-based methods face security vulnerabilities,particularly due to potential information leakage during generation.We propose a fixed neural network image steganography framework based on secure diffu-sion models to address these challenges.Unlike conventional approaches,our method minimizes cover modifications through neural network optimization,achieving superior steganographic performance in human visual perception and computer vision analyses.The cover images are generated in an anime style using state-of-the-art diffusion models,ensuring the transmitted images appear more natural.This study introduces fixed neural network technology that allows senders to transmit only minimal critical information alongside stego-images.Recipients can accurately reconstruct secret images using this compact data,significantly reducing transmission overhead compared to conventional deep steganography.Furthermore,our framework innovatively integrates ElGamal,a cryptographic algorithm,to protect critical information during transmission,enhancing overall system security and ensuring end-to-end information protection.This dual optimization of payload reduction and cryptographic reinforcement establishes a new paradigm for secure and efficient image steganography.
基金supported in part by the Shenzhen Basic Research Program under Grant JCYJ20220531103008018,and Grants 20231120142345001 and 20231127144045001the Natural Science Foundation of China under Grant U20A20156.
文摘The performance of traditional regular Intelligent Reflecting Surface(IRS)improves as the number of IRS elements increases,but more reflecting elements lead to higher IRS power consumption and greater overhead of channel estimation.The Irregular Intelligent Reflecting Surface(IIRS)can enhance the performance of the IRS as well as boost the system performance when the number of reflecting elements is limited.However,due to the lack of radio frequency chain in IRS,it is challenging for the Base Station(BS)to gather perfect Channel State Information(CSI),especially in the presence of Eavesdroppers(Eves).Therefore,in this paper we investigate the minimum transmit power problem of IIRS-aided Simultaneous Wireless Information and Power Transfer(SWIPT)secure communication system with imperfect CSI of BS-IIRS-Eves links,which is subject to the rate outage probability constraints of the Eves,the minimum rate constraints of the Information Receivers(IRs),the energy harvesting constraints of the Energy Receivers(ERs),and the topology matrix constraints.Afterward,the formulated nonconvex problem can be efficiently tackled by employing joint optimization algorithm combined with successive refinement method and adaptive topology design method.Simulation results demonstrate the effectiveness of the proposed scheme and the superiority of IIRS.
基金supported by the NationalNatural Science Foundation of China(No.61862041).
文摘Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a designed multi-attention mechanism focuses on important local features during the feature extraction stage. Moreover, a triplet loss function is utilized to learn discriminative hash codes to construct a compact and efficient triplet deep hashing. Finally, upsampling is used to restore the original resolution of the images during retrieval, thereby enabling more accurate matching. To ensure the security of medical image data, a lightweight image encryption method based on frequency domain encryption is designed to encrypt the chest X-ray images. The findings of the experiment indicate that, in comparison to various advanced image retrieval techniques, the suggested approach improves the precision of feature extraction and retrieval using the COVIDx dataset. Additionally, it offers enhanced protection for the confidentiality of medical images stored in cloud settings and demonstrates strong practicality.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62071381 and 62301430)Shaanxi Fundamental Science Research Project for Mathematics and Physics(Grant No.23JSY014)+1 种基金Scientific Research Plan Project of Shaanxi Education Department Natural Science Special Project(Grant No.23JK0680)Young Talent Fund of Xi’an Association for Science and Technology(Grant No.959202313011)。
文摘Continuous-variable quantum secure direct communication(CVQSDC)with Gaussian modulation(GM)demands a considerable quantity of random numbers during the preparation process and encodes them separately on the quadrature components of the quantum states.Hence,high-speed random number generators are required to satisfy this demand,which is difficult to implement in practical applications.CVQSDC with discrete modulation(DM),correspondingly,employs a finite number of quantum states to achieve encoding,which can circumvent the shortcomings of the GM scheme.Based on the advantages of DM,the issue of attaining the most optimal secrecy capacity and communication distance remains to be resolved.Here,we propose a CVQSDC protocol based on N-symbol amplitude phase shift keying(N-APSK),which exploits the Boltzmann-Maxwell distribution assisted probability shaping technique.In comparison with the uniform distribution,according to 32-APSK CVQSDC,the proposed scheme extends the communication distance by about 38%,while obtaining a higher secrecy capacity at the same communication distance.Furthermore,increasing the value of N will concurrently increase the quantity of rings in the constellation,thereby facilitating enhancements of communication distance.This work incorporates the modulation approaches prevalently employed in classical communication into the realm of quantum communication,attaining gratifying advancements in communication distance and secrecy capacity,and concurrently facilitating the integrated development of quantum communication and classical communication.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2022R1C1C2012463).
文摘Integrating Artificial Intelligence of Things(AIoT)in healthcare offers transformative potential for real-time diagnostics and collaborative learning but presents critical challenges,including privacy preservation,computational efficiency,and regulatory compliance.Traditional approaches,such as differential privacy,homomorphic encryption,and secure multi-party computation,often fail to balance performance and privacy,rendering them unsuitable for resource-constrained healthcare AIoT environments.This paper introduces LMSA(Lightweight Multi-Key Secure Aggregation),a novel framework designed to address these challenges and enable efficient,secure federated learning across distributed healthcare institutions.LMSA incorporates three key innovations:(1)a lightweight multikey management system leveraging Diffie-Hellman key exchange and SHA3-256 hashing,achieving O(n)complexity with AES(Advanced Encryption Standard)-256-level security;(2)a privacy-preserving aggregation protocol employing hardware-accelerated AES-CTR(CounTeR)encryption andmodular arithmetic for securemodel weight combination;and(3)a resource-optimized implementation utilizing AES-NI(New Instructions)instructions and efficient memory management for real-time operations on constrained devices.Experimental evaluations using the National Institutes of Health(NIH)Chest X-ray dataset demonstrate LMSA’s ability to train multi-label thoracic disease prediction models with Vision Transformer(ViT),ResNet-50,and MobileNet architectures across distributed healthcare institutions.Memory usage analysis confirmed minimal overhead,with ViT(327.30 MB),ResNet-50(89.87 MB),and MobileNet(8.63 MB)maintaining stable encryption times across communication rounds.LMSA ensures robust security through hardware acceleration,enabling real-time diagnostics without compromising patient confidentiality or regulatory compliance.Future research aims to optimize LMSA for ultra-low-power devices and validate its scalability in heterogeneous,real-world environments.LMSA represents a foundational advancement for privacy-conscious healthcare AI applications,bridging the gap between privacy and performance.
基金this project under Geran Putra Inisiatif(GPI)with reference of GP-GPI/2023/976210。
文摘Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks(WSNs),especially in security-critical,time-sensitive applications.However,most existing protocols degrade substantially under malicious interference.We introduce iSTSP,an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust,precise synchronization even in hostile environments:(1)trust preprocessing that filters node participation using behavioral trust scoring;(2)anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time;(3)reliability-weighted consensus that prioritizes high-trust nodes during time aggregation;and(4)convergence-optimized synchronization that dynamically adjusts parameters using theoretical stability bounds.We provide rigorous convergence analysis including a closed-form expression for convergence time,and validate the protocol through both simulations and realworld experiments on a controlled 16-node testbed.Under Sybil attacks with five malicious nodes within this testbed,iSTSP maintains synchronization error increases under 12%and achieves a rapid convergence.Compared to state-ofthe-art protocols like TPSN,SE-FTSP,and MMAR-CTS,iSTSP offers 60%faster detection,broader threat coverage,and more than 7 times lower synchronization error,with a modest 9.3%energy overhead over 8 h.We argue this is an acceptable trade-off for mission-critical deployments requiring guaranteed security.These findings demonstrate iSTSP’s potential as a reliable solution for secure WSN synchronization and motivate future work on large-scale IoT deployments and integration with energy-efficient communication protocols.
基金supported in part by the National Key R&D Program of China under Grant 2022YFB3103500in part by the National Natural Science Foundation of China under Grant 62302195.
文摘Semantic secure communication is an emerging field that combines the principles of source-channel coding with the need for secure data transmission.It is of great significance in modern communications to protect the confidentiality and privacy of sensitive information and prevent information leaks and malicious attacks.This paper presents a novel approach to semantic secure communication through the utilization of joint source-channel coding,which is based on the design of an automated joint source-channel coding algorithm and an encryption and decryption algorithm based on semantic security.The traditional and state-of-the-art joint source-channel coding algorithms are selected as two baselines for different comparison purposes.Experimental results demonstrate that our proposed algorithm outperforms the first baseline algorithm,the traditional source-channel coding,by 61.21%in efficiency under identical channel conditions(SNR=15 dB).In security,our proposed method can resist 2 more types of attacks compared to the two baselines,exhibiting nearly no increases in time consumption and error rate compared to the state-of-the-art joint source-channel coding algorithm while the secure semantic communication is supported.
文摘Join CEN as the lead rapporteur of this initiative takes you inside the development of the European harmonized standards for smartcards,similar devices,and secure elements.This session will provide exclusive insights into the current content and approach shaping the compliance criteria needed to meet the essential requirements of the Cyber Resilience Act(EU 2024/2847).
基金supported by the National Key R&D Program of China(No.2023YFB2703700)the National Natural Science Foundation of China(Nos.U21A20465,62302457,62402444,62172292)+4 种基金the Fundamental Research Funds of Zhejiang Sci-Tech University(Nos.23222092-Y,22222266-Y)the Program for Leading Innovative Research Team of Zhejiang Province(No.2023R01001)the Zhejiang Provincial Natural Science Foundation of China(Nos.LQ24F020008,LQ24F020012)the Foundation of State Key Laboratory of Public Big Data(No.[2022]417)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01119).
文摘As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.
基金funding from King Saud University through Researchers Supporting Project number(RSP2024R387),King Saud University,Riyadh,Saudi Arabia.
文摘The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.
文摘The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.
基金supported by the Large Group Project under grant number(RGP2/473/46).
文摘Ensuring the integrity and confidentiality of patient medical information is a critical priority in the healthcare sector.In the context of security,this paper proposes a novel encryption algorithm that integrates Blockchain technology,aiming to improve the security and privacy of transmitted data.The proposed encryption algorithm is a block-cipher image encryption scheme based on different chaotic maps:The logistic Map,the Tent Map,and the Henon Map used to generate three encryption keys.The proposed block-cipher system employs the Hilbert curve to perform permutation while a generated chaos-based S-Box is used to perform substitution.Furthermore,the integration of a Blockchain-based solution for securing data transmission and communication between nodes and authenticating the encrypted medical image’s authenticity adds a layer of security to our proposed method.Our proposed cryptosystem is divided into two principal modules presented as a pseudo-random number generator(PRNG)used for key generation and an encryption and decryption system based on the properties of confusion and diffusion.The security analysis and experimental tests for the proposed algorithm show that the average value of the information entropy of the encrypted images is 7.9993,the Number of Pixels Change Rate(NPCR)values are over 99.5%and the Unified Average Changing Intensity(UACI)values are greater than 33%.These results prove the strength of our proposed approach,demonstrating that it can significantly enhance the security of encrypted images.
基金supported by National Natural Science Foundation of China(No.62172436)Additionally,it is supported by Natural Science Foundation of Shaanxi Province(No.2023-JC-YB-584)Engineering University of PAP’s Funding for Scientific Research Innovation Team and Key Researcher(No.KYGG202011).
文摘Cloud storage,a core component of cloud computing,plays a vital role in the storage and management of data.Electronic Health Records(EHRs),which document users’health information,are typically stored on cloud servers.However,users’sensitive data would then become unregulated.In the event of data loss,cloud storage providers might conceal the fact that data has been compromised to protect their reputation and mitigate losses.Ensuring the integrity of data stored in the cloud remains a pressing issue that urgently needs to be addressed.In this paper,we propose a data auditing scheme for cloud-based EHRs that incorporates recoverability and batch auditing,alongside a thorough security and performance evaluation.Our scheme builds upon the indistinguishability-based privacy-preserving auditing approach proposed by Zhou et al.We identify that this scheme is insecure and vulnerable to forgery attacks on data storage proofs.To address these vulnerabilities,we enhanced the auditing process using masking techniques and designed new algorithms to strengthen security.We also provide formal proof of the security of the signature algorithm and the auditing scheme.Furthermore,our results show that our scheme effectively protects user privacy and is resilient against malicious attacks.Experimental results indicate that our scheme is not only secure and efficient but also supports batch auditing of cloud data.Specifically,when auditing 10,000 users,batch auditing reduces computational overhead by 101 s compared to normal auditing.
