As quantum computing continues to advance,traditional cryptographic methods are increasingly challenged,particularly when it comes to securing critical systems like Supervisory Control andData Acquisition(SCADA)system...As quantum computing continues to advance,traditional cryptographic methods are increasingly challenged,particularly when it comes to securing critical systems like Supervisory Control andData Acquisition(SCADA)systems.These systems are essential for monitoring and controlling industrial operations,making their security paramount.A key threat arises from Shor’s algorithm,a powerful quantum computing tool that can compromise current hash functions,leading to significant concerns about data integrity and confidentiality.To tackle these issues,this article introduces a novel Quantum-Resistant Hash Algorithm(QRHA)known as the Modular Hash Learning Algorithm(MHLA).This algorithm is meticulously crafted to withstand potential quantum attacks by incorporating advanced mathematical and algorithmic techniques,enhancing its overall security framework.Our research delves into the effectiveness ofMHLA in defending against both traditional and quantum-based threats,with a particular emphasis on its resilience to Shor’s algorithm.The findings from our study demonstrate that MHLA significantly enhances the security of SCADA systems in the context of quantum technology.By ensuring that sensitive data remains protected and confidential,MHLA not only fortifies individual systems but also contributes to the broader efforts of safeguarding industrial and infrastructure control systems against future quantumthreats.Our evaluation demonstrates that MHLA improves security by 38%against quantumattack simulations compared to traditional hash functionswhilemaintaining a computational efficiency ofO(m⋅n⋅k+v+n).The algorithm achieved a 98%success rate in detecting data tampering during integrity testing.These findings underline MHLA’s effectiveness in enhancing SCADA system security amidst evolving quantum technologies.This research represents a crucial step toward developing more secure cryptographic systems that can adapt to the rapidly changing technological landscape,ultimately ensuring the reliability and integrity of critical infrastructure in an era where quantum computing poses a growing risk.展开更多
The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchai...The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchains enable on-chain modification,they suffer from inefficiency and excessive centralization,the majority of redactable blockchain schemes ignore the difficult problems of traceability and consistency check.In this paper,we present a Dynamically Redactable Blockchain based on decentralized Chameleon hash(DRBC).Specifically,we propose an Identity-Based Decentralized Chameleon Hash(IDCH)and a Version-Based Transaction structure(VT)to realize the traceability of transaction modifications in a decentralized environment.Then,we propose an efficient block consistency check protocol based on the Bloom filter tree,which can realize the consistency check of transactions with extremely low time and space cost.Security analysis and experiment results demonstrate the reliability of DRBC and its significant advantages in a decentralized environment.展开更多
Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.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
To enable efficient sharing of unbounded streaming data,this paper introduces blockchain technology into traditional cloud data,proposing a hybrid on-chain/off-chain storage model.We design a real-time verifiable data...To enable efficient sharing of unbounded streaming data,this paper introduces blockchain technology into traditional cloud data,proposing a hybrid on-chain/off-chain storage model.We design a real-time verifiable data structure that is more suitable for streaming data to achieve efficient real-time verifiability for streaming data.Based on the notch gate hash function and vector commitment,an adaptive notch gate hash tree structure is constructed,and an efficient real-time verifiable data structure for on-chain and off-chain stream data is proposed.The structure binds dynamic root nodes sequentially to ordered leaf nodes in its child nodes.Only the vector commitment of the dynamic root node is stored on the chain,and the complete data structure is stored off-chain.This structure ensures tamperproofing against malicious off-chain cloud servers of off-chain cloud servers.Preserves storage scalability space,realizes the immediate verification of stream data upon arrival,and the computational overhead of on-chain and off-chain hybrid storage verification is only related to the current data volume,which is more practical when dealing with stream data with unpredictable data volume.We formalize this as an efficient real-time verification scheme for stream data in on-chain and off-chain hybrid storage.Finally,the technology’s security and performance were empirically validated through rigorous analysis.展开更多
Cloud environments are essential for modern computing,but are increasingly vulnerable to Side-Channel Attacks(SCAs),which exploit indirect information to compromise sensitive data.To address this critical challenge,we...Cloud environments are essential for modern computing,but are increasingly vulnerable to Side-Channel Attacks(SCAs),which exploit indirect information to compromise sensitive data.To address this critical challenge,we propose SecureCons Framework(SCF),a novel consensus-based cryptographic framework designed to enhance resilience against SCAs in cloud environments.SCF integrates a dual-layer approach combining lightweight cryptographic algorithms with a blockchain-inspired consensus mechanism to secure data exchanges and thwart potential side-channel exploits.The framework includes adaptive anomaly detection models,cryptographic obfuscation techniques,and real-time monitoring to identify and mitigate vulnerabilities proactively.Experimental evaluations demonstrate the framework's robustness,achieving over 95%resilience against advanced SCAs with minimal computational overhead.SCF provides a scalable,secure,and efficient solution,setting a new benchmark for side-channel attack mitigation in cloud ecosystems.展开更多
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R343),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiathe Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia for funding this research work through the project number NBU-FFR-2025-1092-10.
文摘As quantum computing continues to advance,traditional cryptographic methods are increasingly challenged,particularly when it comes to securing critical systems like Supervisory Control andData Acquisition(SCADA)systems.These systems are essential for monitoring and controlling industrial operations,making their security paramount.A key threat arises from Shor’s algorithm,a powerful quantum computing tool that can compromise current hash functions,leading to significant concerns about data integrity and confidentiality.To tackle these issues,this article introduces a novel Quantum-Resistant Hash Algorithm(QRHA)known as the Modular Hash Learning Algorithm(MHLA).This algorithm is meticulously crafted to withstand potential quantum attacks by incorporating advanced mathematical and algorithmic techniques,enhancing its overall security framework.Our research delves into the effectiveness ofMHLA in defending against both traditional and quantum-based threats,with a particular emphasis on its resilience to Shor’s algorithm.The findings from our study demonstrate that MHLA significantly enhances the security of SCADA systems in the context of quantum technology.By ensuring that sensitive data remains protected and confidential,MHLA not only fortifies individual systems but also contributes to the broader efforts of safeguarding industrial and infrastructure control systems against future quantumthreats.Our evaluation demonstrates that MHLA improves security by 38%against quantumattack simulations compared to traditional hash functionswhilemaintaining a computational efficiency ofO(m⋅n⋅k+v+n).The algorithm achieved a 98%success rate in detecting data tampering during integrity testing.These findings underline MHLA’s effectiveness in enhancing SCADA system security amidst evolving quantum technologies.This research represents a crucial step toward developing more secure cryptographic systems that can adapt to the rapidly changing technological landscape,ultimately ensuring the reliability and integrity of critical infrastructure in an era where quantum computing poses a growing risk.
基金supported in part by the National Key R&D Program of China under project 2022YFB2702901the Guangxi Natural Science Foundation under grants 2024GXNSFDA010064 and 2024GXNSFAA010453+5 种基金the National Natural Science Foundation of China under projects 62172119,62362013,U21A20467 and 72192801Zhejiang Provincial Natural Science Foundation of China under grant LZ23F020012Innovation Project of GUET Graduate Education under grants 2023YCXS070the Guangxi Young Teachers'Basic Ability Improvement Program under grant 2024KY0224Lion Rock Labs of Cyberspace Security under grant LRL24-1-C003one of the research outcomes of the Xiong'an Autonomous and Controllable Blockchain Underlying Technology Platform Project(2020).
文摘The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchains enable on-chain modification,they suffer from inefficiency and excessive centralization,the majority of redactable blockchain schemes ignore the difficult problems of traceability and consistency check.In this paper,we present a Dynamically Redactable Blockchain based on decentralized Chameleon hash(DRBC).Specifically,we propose an Identity-Based Decentralized Chameleon Hash(IDCH)and a Version-Based Transaction structure(VT)to realize the traceability of transaction modifications in a decentralized environment.Then,we propose an efficient block consistency check protocol based on the Bloom filter tree,which can realize the consistency check of transactions with extremely low time and space cost.Security analysis and experiment results demonstrate the reliability of DRBC and its significant advantages in a decentralized environment.
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
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supported by the National Cryptologic Science Fund of China(Grant No.2025NCSF02020)awarded to Yi Sunsupported by the Natural Science Foundation of Henan Province(Grant No.242300420297)awarded to Yi Sun。
文摘To enable efficient sharing of unbounded streaming data,this paper introduces blockchain technology into traditional cloud data,proposing a hybrid on-chain/off-chain storage model.We design a real-time verifiable data structure that is more suitable for streaming data to achieve efficient real-time verifiability for streaming data.Based on the notch gate hash function and vector commitment,an adaptive notch gate hash tree structure is constructed,and an efficient real-time verifiable data structure for on-chain and off-chain stream data is proposed.The structure binds dynamic root nodes sequentially to ordered leaf nodes in its child nodes.Only the vector commitment of the dynamic root node is stored on the chain,and the complete data structure is stored off-chain.This structure ensures tamperproofing against malicious off-chain cloud servers of off-chain cloud servers.Preserves storage scalability space,realizes the immediate verification of stream data upon arrival,and the computational overhead of on-chain and off-chain hybrid storage verification is only related to the current data volume,which is more practical when dealing with stream data with unpredictable data volume.We formalize this as an efficient real-time verification scheme for stream data in on-chain and off-chain hybrid storage.Finally,the technology’s security and performance were empirically validated through rigorous analysis.
文摘Cloud environments are essential for modern computing,but are increasingly vulnerable to Side-Channel Attacks(SCAs),which exploit indirect information to compromise sensitive data.To address this critical challenge,we propose SecureCons Framework(SCF),a novel consensus-based cryptographic framework designed to enhance resilience against SCAs in cloud environments.SCF integrates a dual-layer approach combining lightweight cryptographic algorithms with a blockchain-inspired consensus mechanism to secure data exchanges and thwart potential side-channel exploits.The framework includes adaptive anomaly detection models,cryptographic obfuscation techniques,and real-time monitoring to identify and mitigate vulnerabilities proactively.Experimental evaluations demonstrate the framework's robustness,achieving over 95%resilience against advanced SCAs with minimal computational overhead.SCF provides a scalable,secure,and efficient solution,setting a new benchmark for side-channel attack mitigation in cloud ecosystems.
