Attacks are growing more complex and dangerous as network capabilities improve at a rapid pace.Network intrusion detection is usually regarded as an efficient means of dealing with security attacks.Many ways have been...Attacks are growing more complex and dangerous as network capabilities improve at a rapid pace.Network intrusion detection is usually regarded as an efficient means of dealing with security attacks.Many ways have been presented,utilizing various strategies and focusing on different types of visitors.Anomaly-based network intrusion monitoring is an essential area of intrusion detection investigation and development.Despite extensive research on anomaly-based network detection,there is still a lack of comprehensive literature reviews covering current methodologies and datasets.Despite the substantial research into anomaly-based network intrusion detection algorithms,there is a dearth of a research evaluation of new methodologies and datasets.We explore and evaluate 50 highest publications on anomaly-based intrusion detection using an in-depth review of related literature techniques.Our work thoroughly explores the technological environment of the subject in order to help future research in this sector.Our examination is carried out from the relevant angles:application areas,data preprocessing and threat detection approaches,assessment measures,and datasets.We select unresolved research difficulties and underexplored research areas from every viewpoint recommendation of the study.Finally,we outline five potentially increased research areas for the future.展开更多
The rapid proliferation of Internet of Things(IoT)devices has heightened security concerns,making intrusion detection a pivotal challenge in safeguarding these networks.Traditional centralized Intrusion Detection Syst...The rapid proliferation of Internet of Things(IoT)devices has heightened security concerns,making intrusion detection a pivotal challenge in safeguarding these networks.Traditional centralized Intrusion Detection Systems(IDS)often fail to meet the privacy requirements and scalability demands of large-scale IoT ecosystems.To address these challenges,we propose an innovative privacy-preserving approach leveraging Federated Learning(FL)for distributed intrusion detection.Our model eliminates the need for aggregating sensitive data on a central server by training locally on IoT devices and sharing only encrypted model updates,ensuring enhanced privacy and scalability without compromising detection accuracy.Key innovations of this research include the integration of advanced deep learning techniques for real-time threat detection with minimal latency and a novel model to fortify the system’s resilience against diverse cyber-attacks such as Distributed Denial of Service(DDoS)and malware injections.Our evaluation on three benchmark IoT datasets demonstrates significant improvements:achieving 92.78%accuracy on NSL-KDD,91.47%on BoT-IoT,and 92.05%on UNSW-NB15.The precision,recall,and F1-scores for all datasets consistently exceed 91%.Furthermore,the communication overhead was reduced to 85 MB for NSL-KDD,105 MB for BoT-IoT,and 95 MB for UNSW-NB15—substantially lower than traditional centralized IDS approaches.This study contributes to the domain by presenting a scalable,secure,and privacy-preserving solution tailored to the unique characteristics of IoT environments.The proposed framework is adaptable to dynamic and heterogeneous settings,with potential applications extending to other privacy-sensitive domains.Future work will focus on enhancing the system’s efficiency and addressing emerging challenges such as model poisoning attacks in federated environments.展开更多
With the widespread deployment of large language models(LLMs)in complex and multimodal scenarios,there is a growing demand for secure and standardized integration of external tools and data sources.The Model Context P...With the widespread deployment of large language models(LLMs)in complex and multimodal scenarios,there is a growing demand for secure and standardized integration of external tools and data sources.The Model Context Protocol(MCP),proposed by Anthropic in late 2024,has emerged as a promising framework.Designed to standardize the interaction between LLMs and their external environments,it serves as a“USB-C interface for AI”.While MCP has been rapidly adopted in the industry,systematic academic studies on its security implications remain scarce.This paper presents a comprehensive review of MCP from a security perspective.We begin by analyzing the architecture and workflow of MCP and identify potential security vulnerabilities across key stages including input processing,decision-making,client invocation,server response,and response generation.We then categorize and assess existing defense mechanisms.In addition,we design a real-world attack experiment to demonstrate the feasibility of tool description injection within an actual MCP environment.Based on the experimental results,we further highlight underexplored threat surfaces and propose future directions for securing AI agent systems powered by MCP.This paper aims to provide a structured reference framework for researchers and developers seeking to balance functionality and security in MCP-based systems.展开更多
A URL(Uniform Resource Locator)is used to locate a digital resource.With this URL,an attacker can perform a variety of attacks,which can lead to serious consequences for both individuals and organizations.Therefore,at...A URL(Uniform Resource Locator)is used to locate a digital resource.With this URL,an attacker can perform a variety of attacks,which can lead to serious consequences for both individuals and organizations.Therefore,attackers create malicious URLs to gain access to an organization’s systems or sensitive information.It is crucial to secure individuals and organizations against these malicious URLs.A combination of machine learning and deep learning was used to predict malicious URLs.This research contributes significantly to the field of cybersecurity by proposing a model that seamlessly integrates the accuracy of machine learning with the swiftness of deep learning.The strategic fusion of Random Forest(RF) and Multilayer Perceptron(MLP)with an accuracy of 81% represents a noteworthy advancement,offering a balanced solution for robust cybersecurity.This study found that by combining RF and MLP,an efficient model was developed with an accuracy of 81%and a training time of 33.78 s.展开更多
Satellite communications have attracted significant interests due to its advantages of large footprint and massive access.However,the commonly used onboard beamforming is hard to achieve reliable security because of t...Satellite communications have attracted significant interests due to its advantages of large footprint and massive access.However,the commonly used onboard beamforming is hard to achieve reliable security because of the highly correlated legitimate and wiretap downlink channels.We exploit the benefits of satellite-terrestrial integrated network(STIN)and a novel absorptive reconfigurable intelligent surface(RIS)for improving the security of satellite downlink communications(SDC)in the presence of eavesdroppers(Eves).This paper aims to maximize the achievable secrecy rate of the earth station(ES)while satisfying the signal reception constraints,harvested power threshold at the RIS,and total transmit power budget.To solve this nonconvex problem,we propose a penalty-function based dual decomposition scheme,which firstly transforms the original problem into a two-layer optimization problem.Then,the outer layer and inner problems are solved by utilizing the successive convex approximation,Lagrange-dual and Rayleigh quotient methods to obtain the beamforming weight vectors and the reflective coefficient matrix.Finally,simulation results verify the effectiveness of the proposed scheme for enhancing the SDC security.展开更多
Mobile banking security has witnessed significant R&D attention from both financial institutions and academia.This is due to the growing number of mobile baking applications and their reachability and usefulness t...Mobile banking security has witnessed significant R&D attention from both financial institutions and academia.This is due to the growing number of mobile baking applications and their reachability and usefulness to society.However,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking information.Related literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security functionality.In this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training datasets.The dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission requests.Further,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s behaviour.Performance evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false positives.Specifically,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art approaches.These promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking applications.Consequently,MoBShield has the potential to significantly enhance the security and trustworthiness of mobile banking platforms,mitigating the risks posed by cyber threats and ensuring a safer user experience.展开更多
Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible t...Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible to cybersecurity threats due to its reliance on low-power biomedical devices and the use of open wireless channels for communication.In this article,we intend to address this shortcoming,and as a result,we propose a new scheme called,the certificateless anonymous authentication(CAA)scheme.The proposed scheme is based on hyperelliptic curve cryptography(HECC),an enhanced variant of elliptic curve cryptography(ECC)that employs a smaller key size of 80 bits as compared to 160 bits.The proposed scheme is secure against various attacks in both formal and informal security analyses.The formal study makes use of the Real-or-Random(ROR)model.A thorough comparative study of the proposed scheme is conducted for the security and efficiency of the proposed scheme with the relevant existing schemes.The results demonstrate that the proposed scheme not only ensures high security for health-related data but also increases efficiency.The proposed scheme’s computation cost is 2.88 ms,and the communication cost is 1440 bits,which shows its better efficiency compared to its counterpart schemes.展开更多
Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexib...Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexible pipes and further diffuse into the annular space,incurring annular pressure build-up and/or production of acidic environment,which poses serious challenges to the structure and integrity of the flexible pipes.Gas permeation in pipes is a complex phenomenon governed by various factors such as internal pressure and temperature,annular structure,external temperature.In a long-distance gas flexible pipe,moreover,gas permeation exhibits non-uniform features,and the gas permeated into the annular space flows along the metal gap.To assess the complex gas transport behavior in long-distance gas flexible pipes,a mathematical model is established in this paper considering the multiphase flow phenomena inside the flexible pipes,the diffusion of gas in the inner liner,and the gas seepage in the annular space under varying permeable properties of the annulus.In addition,the effect of a variable temperature is accounted.A numerical calculation method is accordingly constructed to solve the coupling mathematical equations.The annular permeability was shown to significantly influence the distribution of annular pressure.As permeability increases,the annular pressure tends to become more uniform,and the annular pressure at the wellhead rises more rapidly.After annular pressure relief followed by shut-in,the pressure increase follows a convex function.By simulating the pressure recovery pattern after pressure relief and comparing it with test results,we deduce that the annular permeability lies between 123 and 512 m D.The results help shed light upon assessing the annular pressure in long distance gas flexible pipes and thus ensure the security of gas transport in the emerging development of offshore resources.展开更多
Due to their significant correlation and redundancy,conventional block cipher cryptosystems are not efficient in encryptingmultimedia data.Streamciphers based onCellularAutomata(CA)can provide amore effective solution...Due to their significant correlation and redundancy,conventional block cipher cryptosystems are not efficient in encryptingmultimedia data.Streamciphers based onCellularAutomata(CA)can provide amore effective solution.The CA have recently gained recognition as a robust cryptographic primitive,being used as pseudorandom number generators in hash functions,block ciphers and stream ciphers.CA have the ability to perform parallel transformations,resulting in high throughput performance.Additionally,they exhibit a natural tendency to resist fault attacks.Few stream cipher schemes based on CA have been proposed in the literature.Though,their encryption/decryption throughput is relatively low,which makes them unsuitable formultimedia communication.Trivium and Grain are efficient stream ciphers that were selected as finalists in the eSTREAM project,but they have proven to be vulnerable to differential fault attacks.This work introduces a novel and scalable stream cipher named CeTrivium,whose design is based on CA.CeTrivium is a 5-neighborhood CA-based streamcipher inspired by the designs of Trivium and Grain.It is constructed using three building blocks:the Trivium(Tr)block,the Nonlinear-CA(NCA)block,and the Nonlinear Mixing(NM)block.The NCA block is a 64-bit nonlinear hybrid 5-neighborhood CA,while the Tr block has the same structure as the Trivium stream cipher.The NM block is a nonlinear,balanced,and reversible Boolean function that mixes the outputs of the Tr and NCA blocks to produce a keystream.Cryptanalysis of CeTrivium has indicated that it can resist various attacks,including correlation,algebraic,fault,cube,Meier and Staffelbach,and side channel attacks.Moreover,the scheme is evaluated using histogramand spectrogramanalysis,aswell as several differentmeasurements,including the correlation coefficient,number of samples change rate,signal-to-noise ratio,entropy,and peak signal-to-noise ratio.The performance of CeTrivium is evaluated and compared with other state-of-the-art techniques.CeTrivium outperforms them in terms of encryption throughput while maintaining high security.CeTrivium has high encryption and decryption speeds,is scalable,and resists various attacks,making it suitable for multimedia communication.展开更多
CHINA has tightened up its national security by adopting a new wide-ranging law effective July 1. The law was passed with overwhelming support from the deputies of the National People＇s Con- gress （NPC）, the countr...CHINA has tightened up its national security by adopting a new wide-ranging law effective July 1. The law was passed with overwhelming support from the deputies of the National People＇s Con- gress （NPC）, the country＇s top legislature, whose Standing Committee voted 154 in favor, no votes against and one abstention.展开更多
This paper presents SMRAN, a novel securing multicast route discovery scheme for mobile ad hoc networks. The scheme relies entirely on hash chains based one-time signature mechanism, HORSEI, with very efficient signin...This paper presents SMRAN, a novel securing multicast route discovery scheme for mobile ad hoc networks. The scheme relies entirely on hash chains based one-time signature mechanism, HORSEI, with very efficient signing and verifying, and we do this by improving the HORSE protocol through the introduction of intermediate hash joints. The main purpose of SMRAN is to provide source authentication for multicast routing discovery messages in mobile ad hoc networks. SMRAN will construct multicast tree with authentication constrains in ad hoc networks. The performance measure of SMRAN is evaluated using simulator NS2. The results represent that SMRAN produces less end-to-end packet latency than public key based secure routing scheme, and it is a feasible approach to securing multicast routing for mobile ad hoc networks.展开更多
Due to both of jamming and eavesdropping,active eavesdroppers can induce more serious security threats to unmanned aerial vehicle(UAV)-enabled communications.This paper considers a secure UAV communication system incl...Due to both of jamming and eavesdropping,active eavesdroppers can induce more serious security threats to unmanned aerial vehicle(UAV)-enabled communications.This paper considers a secure UAV communication system including both the downlink(DL)and uplink(UL)transmissions,where the confidential information is transmitted between a UAV and a ground node in the presence of an active eavesdropper.We aim to maximize the average secrecy rates of the DL and UL communications,respectively,by jointly optimizing the UAV trajectory and the UAV/ground node’s transmit power control over a given flight period.Due to the non-convexity of the formulated problems,it is difficult to obtain globally optimal solutions.However,we propose efficient iterative algorithms to obtain high-quality suboptimal solutions by applying the block coordinate descent and successive convex optimization methods.Simulation results show that the joint optimization algorithms can effectively improve the secrecy rate performance for both the DL and UL communications,as compared with other baseline schemes.The proposed schemes can be considered as special cases of UAV-assisted non-orthogonal multiple access(NOMA)networks.展开更多
Existing solutions for secure network coding either bring significant bandwidth overhead or incur a high computational complexity. For exploiting low-overhead mechanism for secure network coding against wiretapping, t...Existing solutions for secure network coding either bring significant bandwidth overhead or incur a high computational complexity. For exploiting low-overhead mechanism for secure network coding against wiretapping, three efficient schemes are proposed for the applications with different security requirements. The basic idea behind this paper is first to encrypt a small part of source vectors and then subject the remaining original source vectors and the encrypted vectors to a special linear transformation. Also, a lightweight version of this scheme is then presented for resource-constrained networks. Moreover, an extensive scheme with enhanced security is also considered. All proposals are shown to have properties of lower security complexity and smaller bandwidth usage compared with the existing solutions. Also, the proposals can be easy to achieve flexible levels of security for various applications.展开更多
With the increasing need of sensitive or secret data transmission through public network,security demands using cryptography and steganography are becoming a thirsty research area of last few years.These two technique...With the increasing need of sensitive or secret data transmission through public network,security demands using cryptography and steganography are becoming a thirsty research area of last few years.These two techniques can be merged and provide better security which is nowadays extremely required.The proposed system provides a novel method of information security using the techniques of audio steganography combined with visual cryptography.In this system,we take a secret image and divide it into several subparts to make more than one incomprehensible sub-images using the method of visual cryptography.Each of the sub-images is then hidden within individual cover audio files using audio steganographic techniques.The cover audios are then sent to the required destinations where reverse steganography schemes are applied to them to get the incomprehensible component images back.At last,all the sub-images are superimposed to get the actual secret image.This method is very secure as it uses a two-step security mechanism to maintain secrecy.The possibility of interception is less in this technique because one must have each piece of correct sub-image to regenerate the actual secret image.Without superimposing every one of the sub-images meaningful secret images cannot be formed.Audio files are composed of densely packed bits.The high density of data in audio makes it hard for a listener to detect the manipulation due to the proposed time-domain audio steganographic method.展开更多
DDoS attacks in the Internet of Things(IoT)technology have increased significantly due to its spread adoption in different industrial domains.The purpose of the current research is to propose a novel technique for det...DDoS attacks in the Internet of Things(IoT)technology have increased significantly due to its spread adoption in different industrial domains.The purpose of the current research is to propose a novel technique for detecting botnet attacks in user-oriented IoT environments.Conspicuously,an attack identification technique inspired by Recurrent Neural networks and Bidirectional Long Short Term Memory(BLRNN)is presented using a unique Deep Learning(DL)technique.For text identification and translation of attack data segments into tokenized form,word embedding is employed.The performance analysis of the presented technique is performed in comparison to the state-of-the-art DL techniques.Specifically,Accuracy(98.4%),Specificity(98.7%),Sensitivity(99.0%),F-measure(99.0%)and Data loss(92.36%)of the presented BLRNN detection model are determined for identifying 4 attacks over Botnet(Mirai).The results show that,although adding cost to each epoch and increasing computation delay,the bidirectional strategy is more superior technique model over different data instances.展开更多
In a digital world moving at a breakneck speed,consultancy services have emerged as one of the prominent resources for seeking effective,sustainable and economically viable solutions to a given crisis.The present day ...In a digital world moving at a breakneck speed,consultancy services have emerged as one of the prominent resources for seeking effective,sustainable and economically viable solutions to a given crisis.The present day consultancy services are aided by the use of multiple tools and techniques.However,ensuring the security of these tools and techniques is an important concern for the consultants because even a slight malfunction of any tool could alter the results drastically.Consultants usually tackle these functions after establishing the clients’needs and developing the appropriate strategy.Nevertheless,most of the consultants tend to focus more on the intended outcomes only and often ignore the security-specific issues.Our research study is an initiative to recommend the use of a hybrid computational technique based on fuzzy Analytical Hierarchy Process(AHP)and fuzzy Technique for Order Preference by Similarity to Ideal Solutions(TOPSIS)for prioritizing the tools and techniques that are used in consultancy services on the basis of their security features and efficacy.The empirical analysis conducted in this context shows that after implementing the assessment process,the rank of the tools and techniques obtained is:A7>A1>A4>A2>A3>A5>A6>A7,and General Electric McKinsey(GE-McKinsey)Nine-box Matrix(A7)obtained the highest rank.Thus,the outcomes show that this order of selection of the tools and techniques will give the most effective and secure services.The awareness about using the best tools and techniques in consultancy services is as important as selecting the most secure tool for solving a given problem.In this league,the results obtained in this study would be a conclusive and a reliable reference for the consultants.展开更多
The energy industry and in particular the Oil Refineries are extremely important elements in Iraq’s infrastructure. A terrorist attack on one oil refinery will have a catastrophic impact on oil production and the who...The energy industry and in particular the Oil Refineries are extremely important elements in Iraq’s infrastructure. A terrorist attack on one oil refinery will have a catastrophic impact on oil production and the whole economy. It can also cause serious damage to the environment and even losses of human lives. The security of information systems and industrial control systems such as Supervisory Control and Data Acquisition (SCADA) systems and Distributed Control System (DCS) used in the oil industry is a major part of infrastructure protection strategy. This paper describes an attempt to use several security procedures to design a secure, robust system for the SCADA and DCS systems currently in use in the North Oil Refinery in the city of Baiji located in northern Iraq.展开更多
Initial works in ad hoc routing have considered only the problem of providing efficient mechanisms for finding paths in such networks,without considering security as a major problem.In such a trusted environment,malic...Initial works in ad hoc routing have considered only the problem of providing efficient mechanisms for finding paths in such networks,without considering security as a major problem.In such a trusted environment,malicious behaviors can disturb routing process.We present the design and performance evaluation of a new secure on-demand routing protocol for ad hoc networks, called CASR.CASR is robust against attackers from outside of the network and even it prevents compromised nodes from tampering with uncompromised routes consisting of uncompromised nodes.Because of using symmetric cryptography in its structure,CASR is robust against large number of types of Denial-of -Service attacks.However,due to the applying of the random key predistributions method to the routing process our proposed scheme reaches a trade-off between the degree of security and complexity.展开更多
While smart devices based on ARM processor bring us a lot of convenience,they also become an attractive target of cyber-attacks.The threat is exaggerated as commodity OSes usually have a large code base and suffer fro...While smart devices based on ARM processor bring us a lot of convenience,they also become an attractive target of cyber-attacks.The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities.Nowadays,adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application.A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device.In this work,we present a scheme named SecDisplay for trusted display service,it protects sensitive data displayed from being stolen or tampered surreptitiously by a compromised OS.The TCB of SecDisplay mainly consists of a tiny hypervisor and a super light-weight rendering painter,and has only^1400 lines of code.We implemented a prototype of SecDisplay and evaluated its performance overhead.The results show that SecDisplay only incurs an average drop of 3.4%.展开更多
Blockchain technology has revolutionized conventional trade.The success of blockchain can be attributed to its distributed ledger characteristic,which secures every record inside the ledger using cryptography rules,ma...Blockchain technology has revolutionized conventional trade.The success of blockchain can be attributed to its distributed ledger characteristic,which secures every record inside the ledger using cryptography rules,making it more reliable,secure,and tamper-proof.This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context.Furthermore,it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure.To realize the full potential of the accurate and efficacious use of blockchain in the transportation sector,it is essential to understand the most effective mechanisms of this technology and identify the most useful one.As a result,the present work offers a priority-based methodology that would be a useful reference for security experts in managing blockchain technology and its models.The study uses the hesitant fuzzy analytical hierarchy process for prioritizing the different blockchain models.Based on the findings of actual performance,alternative solution A1 which is Private Blockchain model has an extremely high level of security satisfaction.The accuracy of the results has been tested using the hesitant fuzzy technique for order of preference by similarity to the ideal solution procedure.The study also uses guidelines from security researchers working in this domain.展开更多
文摘Attacks are growing more complex and dangerous as network capabilities improve at a rapid pace.Network intrusion detection is usually regarded as an efficient means of dealing with security attacks.Many ways have been presented,utilizing various strategies and focusing on different types of visitors.Anomaly-based network intrusion monitoring is an essential area of intrusion detection investigation and development.Despite extensive research on anomaly-based network detection,there is still a lack of comprehensive literature reviews covering current methodologies and datasets.Despite the substantial research into anomaly-based network intrusion detection algorithms,there is a dearth of a research evaluation of new methodologies and datasets.We explore and evaluate 50 highest publications on anomaly-based intrusion detection using an in-depth review of related literature techniques.Our work thoroughly explores the technological environment of the subject in order to help future research in this sector.Our examination is carried out from the relevant angles:application areas,data preprocessing and threat detection approaches,assessment measures,and datasets.We select unresolved research difficulties and underexplored research areas from every viewpoint recommendation of the study.Finally,we outline five potentially increased research areas for the future.
基金supported and funded by the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025).
文摘The rapid proliferation of Internet of Things(IoT)devices has heightened security concerns,making intrusion detection a pivotal challenge in safeguarding these networks.Traditional centralized Intrusion Detection Systems(IDS)often fail to meet the privacy requirements and scalability demands of large-scale IoT ecosystems.To address these challenges,we propose an innovative privacy-preserving approach leveraging Federated Learning(FL)for distributed intrusion detection.Our model eliminates the need for aggregating sensitive data on a central server by training locally on IoT devices and sharing only encrypted model updates,ensuring enhanced privacy and scalability without compromising detection accuracy.Key innovations of this research include the integration of advanced deep learning techniques for real-time threat detection with minimal latency and a novel model to fortify the system’s resilience against diverse cyber-attacks such as Distributed Denial of Service(DDoS)and malware injections.Our evaluation on three benchmark IoT datasets demonstrates significant improvements:achieving 92.78%accuracy on NSL-KDD,91.47%on BoT-IoT,and 92.05%on UNSW-NB15.The precision,recall,and F1-scores for all datasets consistently exceed 91%.Furthermore,the communication overhead was reduced to 85 MB for NSL-KDD,105 MB for BoT-IoT,and 95 MB for UNSW-NB15—substantially lower than traditional centralized IDS approaches.This study contributes to the domain by presenting a scalable,secure,and privacy-preserving solution tailored to the unique characteristics of IoT environments.The proposed framework is adaptable to dynamic and heterogeneous settings,with potential applications extending to other privacy-sensitive domains.Future work will focus on enhancing the system’s efficiency and addressing emerging challenges such as model poisoning attacks in federated environments.
基金supported in part by the National Natural Science Foundation of China under Grant No.62325207.
文摘With the widespread deployment of large language models(LLMs)in complex and multimodal scenarios,there is a growing demand for secure and standardized integration of external tools and data sources.The Model Context Protocol(MCP),proposed by Anthropic in late 2024,has emerged as a promising framework.Designed to standardize the interaction between LLMs and their external environments,it serves as a“USB-C interface for AI”.While MCP has been rapidly adopted in the industry,systematic academic studies on its security implications remain scarce.This paper presents a comprehensive review of MCP from a security perspective.We begin by analyzing the architecture and workflow of MCP and identify potential security vulnerabilities across key stages including input processing,decision-making,client invocation,server response,and response generation.We then categorize and assess existing defense mechanisms.In addition,we design a real-world attack experiment to demonstrate the feasibility of tool description injection within an actual MCP environment.Based on the experimental results,we further highlight underexplored threat surfaces and propose future directions for securing AI agent systems powered by MCP.This paper aims to provide a structured reference framework for researchers and developers seeking to balance functionality and security in MCP-based systems.
文摘A URL(Uniform Resource Locator)is used to locate a digital resource.With this URL,an attacker can perform a variety of attacks,which can lead to serious consequences for both individuals and organizations.Therefore,attackers create malicious URLs to gain access to an organization’s systems or sensitive information.It is crucial to secure individuals and organizations against these malicious URLs.A combination of machine learning and deep learning was used to predict malicious URLs.This research contributes significantly to the field of cybersecurity by proposing a model that seamlessly integrates the accuracy of machine learning with the swiftness of deep learning.The strategic fusion of Random Forest(RF) and Multilayer Perceptron(MLP)with an accuracy of 81% represents a noteworthy advancement,offering a balanced solution for robust cybersecurity.This study found that by combining RF and MLP,an efficient model was developed with an accuracy of 81%and a training time of 33.78 s.
基金supported by the National Natural Science Foundation of China(No.62201592)the Research Plan Project of NUDT(ZK21-33)the Young Elite Scientist Sponsorship Program of CAST,China(2021-JCJQ-QT-048)。
文摘Satellite communications have attracted significant interests due to its advantages of large footprint and massive access.However,the commonly used onboard beamforming is hard to achieve reliable security because of the highly correlated legitimate and wiretap downlink channels.We exploit the benefits of satellite-terrestrial integrated network(STIN)and a novel absorptive reconfigurable intelligent surface(RIS)for improving the security of satellite downlink communications(SDC)in the presence of eavesdroppers(Eves).This paper aims to maximize the achievable secrecy rate of the earth station(ES)while satisfying the signal reception constraints,harvested power threshold at the RIS,and total transmit power budget.To solve this nonconvex problem,we propose a penalty-function based dual decomposition scheme,which firstly transforms the original problem into a two-layer optimization problem.Then,the outer layer and inner problems are solved by utilizing the successive convex approximation,Lagrange-dual and Rayleigh quotient methods to obtain the beamforming weight vectors and the reflective coefficient matrix.Finally,simulation results verify the effectiveness of the proposed scheme for enhancing the SDC security.
基金the Deanship of Scientific Research(DSR),King Khalid University,Abha,under Grant No.RGP.1/260/45The author,therefore,gratefully acknowledges the DSR’s technical and financial support.
文摘Mobile banking security has witnessed significant R&D attention from both financial institutions and academia.This is due to the growing number of mobile baking applications and their reachability and usefulness to society.However,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking information.Related literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security functionality.In this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training datasets.The dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission requests.Further,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s behaviour.Performance evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false positives.Specifically,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art approaches.These promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking applications.Consequently,MoBShield has the potential to significantly enhance the security and trustworthiness of mobile banking platforms,mitigating the risks posed by cyber threats and ensuring a safer user experience.
文摘Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible to cybersecurity threats due to its reliance on low-power biomedical devices and the use of open wireless channels for communication.In this article,we intend to address this shortcoming,and as a result,we propose a new scheme called,the certificateless anonymous authentication(CAA)scheme.The proposed scheme is based on hyperelliptic curve cryptography(HECC),an enhanced variant of elliptic curve cryptography(ECC)that employs a smaller key size of 80 bits as compared to 160 bits.The proposed scheme is secure against various attacks in both formal and informal security analyses.The formal study makes use of the Real-or-Random(ROR)model.A thorough comparative study of the proposed scheme is conducted for the security and efficiency of the proposed scheme with the relevant existing schemes.The results demonstrate that the proposed scheme not only ensures high security for health-related data but also increases efficiency.The proposed scheme’s computation cost is 2.88 ms,and the communication cost is 1440 bits,which shows its better efficiency compared to its counterpart schemes.
基金supported by the Natural Science Research Project of Guangling College of Yangzhou University,China (ZKZD18004)General Program of Natural Science Research in Higher Education Institutions of Jiangsu Province,China (20KJD430006)。
文摘Gas flexible pipes are critical multi-layered equipment for offshore oil and gas development.Under high pressure conditions,small molecular components of natural gas dissolve into the polymer inner liner of the flexible pipes and further diffuse into the annular space,incurring annular pressure build-up and/or production of acidic environment,which poses serious challenges to the structure and integrity of the flexible pipes.Gas permeation in pipes is a complex phenomenon governed by various factors such as internal pressure and temperature,annular structure,external temperature.In a long-distance gas flexible pipe,moreover,gas permeation exhibits non-uniform features,and the gas permeated into the annular space flows along the metal gap.To assess the complex gas transport behavior in long-distance gas flexible pipes,a mathematical model is established in this paper considering the multiphase flow phenomena inside the flexible pipes,the diffusion of gas in the inner liner,and the gas seepage in the annular space under varying permeable properties of the annulus.In addition,the effect of a variable temperature is accounted.A numerical calculation method is accordingly constructed to solve the coupling mathematical equations.The annular permeability was shown to significantly influence the distribution of annular pressure.As permeability increases,the annular pressure tends to become more uniform,and the annular pressure at the wellhead rises more rapidly.After annular pressure relief followed by shut-in,the pressure increase follows a convex function.By simulating the pressure recovery pattern after pressure relief and comparing it with test results,we deduce that the annular permeability lies between 123 and 512 m D.The results help shed light upon assessing the annular pressure in long distance gas flexible pipes and thus ensure the security of gas transport in the emerging development of offshore resources.
文摘Due to their significant correlation and redundancy,conventional block cipher cryptosystems are not efficient in encryptingmultimedia data.Streamciphers based onCellularAutomata(CA)can provide amore effective solution.The CA have recently gained recognition as a robust cryptographic primitive,being used as pseudorandom number generators in hash functions,block ciphers and stream ciphers.CA have the ability to perform parallel transformations,resulting in high throughput performance.Additionally,they exhibit a natural tendency to resist fault attacks.Few stream cipher schemes based on CA have been proposed in the literature.Though,their encryption/decryption throughput is relatively low,which makes them unsuitable formultimedia communication.Trivium and Grain are efficient stream ciphers that were selected as finalists in the eSTREAM project,but they have proven to be vulnerable to differential fault attacks.This work introduces a novel and scalable stream cipher named CeTrivium,whose design is based on CA.CeTrivium is a 5-neighborhood CA-based streamcipher inspired by the designs of Trivium and Grain.It is constructed using three building blocks:the Trivium(Tr)block,the Nonlinear-CA(NCA)block,and the Nonlinear Mixing(NM)block.The NCA block is a 64-bit nonlinear hybrid 5-neighborhood CA,while the Tr block has the same structure as the Trivium stream cipher.The NM block is a nonlinear,balanced,and reversible Boolean function that mixes the outputs of the Tr and NCA blocks to produce a keystream.Cryptanalysis of CeTrivium has indicated that it can resist various attacks,including correlation,algebraic,fault,cube,Meier and Staffelbach,and side channel attacks.Moreover,the scheme is evaluated using histogramand spectrogramanalysis,aswell as several differentmeasurements,including the correlation coefficient,number of samples change rate,signal-to-noise ratio,entropy,and peak signal-to-noise ratio.The performance of CeTrivium is evaluated and compared with other state-of-the-art techniques.CeTrivium outperforms them in terms of encryption throughput while maintaining high security.CeTrivium has high encryption and decryption speeds,is scalable,and resists various attacks,making it suitable for multimedia communication.
文摘CHINA has tightened up its national security by adopting a new wide-ranging law effective July 1. The law was passed with overwhelming support from the deputies of the National People＇s Con- gress （NPC）, the country＇s top legislature, whose Standing Committee voted 154 in favor, no votes against and one abstention.
基金Supported by the National Natural Science Foundation of China (90304018)
文摘This paper presents SMRAN, a novel securing multicast route discovery scheme for mobile ad hoc networks. The scheme relies entirely on hash chains based one-time signature mechanism, HORSEI, with very efficient signing and verifying, and we do this by improving the HORSE protocol through the introduction of intermediate hash joints. The main purpose of SMRAN is to provide source authentication for multicast routing discovery messages in mobile ad hoc networks. SMRAN will construct multicast tree with authentication constrains in ad hoc networks. The performance measure of SMRAN is evaluated using simulator NS2. The results represent that SMRAN produces less end-to-end packet latency than public key based secure routing scheme, and it is a feasible approach to securing multicast routing for mobile ad hoc networks.
基金This work was partially supported by the National Natural Science Foundation of China(No.61802034)National Key Research and Development Program of China(No.2019YFC1509602)Chongqing Natural Science Foundation(cstc2019jcyj-msxmX0264).
文摘Due to both of jamming and eavesdropping,active eavesdroppers can induce more serious security threats to unmanned aerial vehicle(UAV)-enabled communications.This paper considers a secure UAV communication system including both the downlink(DL)and uplink(UL)transmissions,where the confidential information is transmitted between a UAV and a ground node in the presence of an active eavesdropper.We aim to maximize the average secrecy rates of the DL and UL communications,respectively,by jointly optimizing the UAV trajectory and the UAV/ground node’s transmit power control over a given flight period.Due to the non-convexity of the formulated problems,it is difficult to obtain globally optimal solutions.However,we propose efficient iterative algorithms to obtain high-quality suboptimal solutions by applying the block coordinate descent and successive convex optimization methods.Simulation results show that the joint optimization algorithms can effectively improve the secrecy rate performance for both the DL and UL communications,as compared with other baseline schemes.The proposed schemes can be considered as special cases of UAV-assisted non-orthogonal multiple access(NOMA)networks.
基金Supported by the National Natural Science Foundation of China(6127117)
文摘Existing solutions for secure network coding either bring significant bandwidth overhead or incur a high computational complexity. For exploiting low-overhead mechanism for secure network coding against wiretapping, three efficient schemes are proposed for the applications with different security requirements. The basic idea behind this paper is first to encrypt a small part of source vectors and then subject the remaining original source vectors and the encrypted vectors to a special linear transformation. Also, a lightweight version of this scheme is then presented for resource-constrained networks. Moreover, an extensive scheme with enhanced security is also considered. All proposals are shown to have properties of lower security complexity and smaller bandwidth usage compared with the existing solutions. Also, the proposals can be easy to achieve flexible levels of security for various applications.
基金Taif University Researchers Supporting Project No.(TURSP-2020/77),Taif university,Taif,Saudi Arabia.
文摘With the increasing need of sensitive or secret data transmission through public network,security demands using cryptography and steganography are becoming a thirsty research area of last few years.These two techniques can be merged and provide better security which is nowadays extremely required.The proposed system provides a novel method of information security using the techniques of audio steganography combined with visual cryptography.In this system,we take a secret image and divide it into several subparts to make more than one incomprehensible sub-images using the method of visual cryptography.Each of the sub-images is then hidden within individual cover audio files using audio steganographic techniques.The cover audios are then sent to the required destinations where reverse steganography schemes are applied to them to get the incomprehensible component images back.At last,all the sub-images are superimposed to get the actual secret image.This method is very secure as it uses a two-step security mechanism to maintain secrecy.The possibility of interception is less in this technique because one must have each piece of correct sub-image to regenerate the actual secret image.Without superimposing every one of the sub-images meaningful secret images cannot be formed.Audio files are composed of densely packed bits.The high density of data in audio makes it hard for a listener to detect the manipulation due to the proposed time-domain audio steganographic method.
基金The authors extend their appreciation to the Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number(IF-PSAU-2021/01/17795).
文摘DDoS attacks in the Internet of Things(IoT)technology have increased significantly due to its spread adoption in different industrial domains.The purpose of the current research is to propose a novel technique for detecting botnet attacks in user-oriented IoT environments.Conspicuously,an attack identification technique inspired by Recurrent Neural networks and Bidirectional Long Short Term Memory(BLRNN)is presented using a unique Deep Learning(DL)technique.For text identification and translation of attack data segments into tokenized form,word embedding is employed.The performance analysis of the presented technique is performed in comparison to the state-of-the-art DL techniques.Specifically,Accuracy(98.4%),Specificity(98.7%),Sensitivity(99.0%),F-measure(99.0%)and Data loss(92.36%)of the presented BLRNN detection model are determined for identifying 4 attacks over Botnet(Mirai).The results show that,although adding cost to each epoch and increasing computation delay,the bidirectional strategy is more superior technique model over different data instances.
基金Funding for this study was received from the Taif University Researchers Supporting Projects at Taif University,Kingdom of Saudi Arabia under Grant No.TURSP-2020/254.
文摘In a digital world moving at a breakneck speed,consultancy services have emerged as one of the prominent resources for seeking effective,sustainable and economically viable solutions to a given crisis.The present day consultancy services are aided by the use of multiple tools and techniques.However,ensuring the security of these tools and techniques is an important concern for the consultants because even a slight malfunction of any tool could alter the results drastically.Consultants usually tackle these functions after establishing the clients’needs and developing the appropriate strategy.Nevertheless,most of the consultants tend to focus more on the intended outcomes only and often ignore the security-specific issues.Our research study is an initiative to recommend the use of a hybrid computational technique based on fuzzy Analytical Hierarchy Process(AHP)and fuzzy Technique for Order Preference by Similarity to Ideal Solutions(TOPSIS)for prioritizing the tools and techniques that are used in consultancy services on the basis of their security features and efficacy.The empirical analysis conducted in this context shows that after implementing the assessment process,the rank of the tools and techniques obtained is:A7>A1>A4>A2>A3>A5>A6>A7,and General Electric McKinsey(GE-McKinsey)Nine-box Matrix(A7)obtained the highest rank.Thus,the outcomes show that this order of selection of the tools and techniques will give the most effective and secure services.The awareness about using the best tools and techniques in consultancy services is as important as selecting the most secure tool for solving a given problem.In this league,the results obtained in this study would be a conclusive and a reliable reference for the consultants.
文摘The energy industry and in particular the Oil Refineries are extremely important elements in Iraq’s infrastructure. A terrorist attack on one oil refinery will have a catastrophic impact on oil production and the whole economy. It can also cause serious damage to the environment and even losses of human lives. The security of information systems and industrial control systems such as Supervisory Control and Data Acquisition (SCADA) systems and Distributed Control System (DCS) used in the oil industry is a major part of infrastructure protection strategy. This paper describes an attempt to use several security procedures to design a secure, robust system for the SCADA and DCS systems currently in use in the North Oil Refinery in the city of Baiji located in northern Iraq.
基金supported by Iran Telecommunication Research Center
文摘Initial works in ad hoc routing have considered only the problem of providing efficient mechanisms for finding paths in such networks,without considering security as a major problem.In such a trusted environment,malicious behaviors can disturb routing process.We present the design and performance evaluation of a new secure on-demand routing protocol for ad hoc networks, called CASR.CASR is robust against attackers from outside of the network and even it prevents compromised nodes from tampering with uncompromised routes consisting of uncompromised nodes.Because of using symmetric cryptography in its structure,CASR is robust against large number of types of Denial-of -Service attacks.However,due to the applying of the random key predistributions method to the routing process our proposed scheme reaches a trade-off between the degree of security and complexity.
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.61379145)the Joint Funds of CETC(Grant No.20166141B08020101).
文摘While smart devices based on ARM processor bring us a lot of convenience,they also become an attractive target of cyber-attacks.The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities.Nowadays,adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application.A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device.In this work,we present a scheme named SecDisplay for trusted display service,it protects sensitive data displayed from being stolen or tampered surreptitiously by a compromised OS.The TCB of SecDisplay mainly consists of a tiny hypervisor and a super light-weight rendering painter,and has only^1400 lines of code.We implemented a prototype of SecDisplay and evaluated its performance overhead.The results show that SecDisplay only incurs an average drop of 3.4%.
文摘Blockchain technology has revolutionized conventional trade.The success of blockchain can be attributed to its distributed ledger characteristic,which secures every record inside the ledger using cryptography rules,making it more reliable,secure,and tamper-proof.This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context.Furthermore,it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure.To realize the full potential of the accurate and efficacious use of blockchain in the transportation sector,it is essential to understand the most effective mechanisms of this technology and identify the most useful one.As a result,the present work offers a priority-based methodology that would be a useful reference for security experts in managing blockchain technology and its models.The study uses the hesitant fuzzy analytical hierarchy process for prioritizing the different blockchain models.Based on the findings of actual performance,alternative solution A1 which is Private Blockchain model has an extremely high level of security satisfaction.The accuracy of the results has been tested using the hesitant fuzzy technique for order of preference by similarity to the ideal solution procedure.The study also uses guidelines from security researchers working in this domain.
