To ensure the access security of 6G,physical-layer authentication(PLA)leverages the randomness and space-time-frequency uniqueness of the channel to provide unique identity signatures for transmitters.Furthermore,the ...To ensure the access security of 6G,physical-layer authentication(PLA)leverages the randomness and space-time-frequency uniqueness of the channel to provide unique identity signatures for transmitters.Furthermore,the introduction of artificial intelligence(AI)facilitates the learning of the distribution characteristics of channel fingerprints,effectively addressing the uncertainties and unknown dynamic challenges in wireless link modeling.This paper reviews representative AI-enabled PLA schemes and proposes a graph neural network(GNN)-based PLA approach in response to the challenges existing methods face in identifying mobile users.Simulation results demonstrate that the proposed method outperforms six baseline schemes in terms of authentication accuracy.Furthermore,this paper outlines the future development directions of PLA.展开更多
Pre-Authentication and Post-Connection(PAPC)plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication.While earlier ap...Pre-Authentication and Post-Connection(PAPC)plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication.While earlier approaches such as Port Knocking(PK)and Single Packet Authorization(SPA)introduced pre-authentication concepts,they suffer from limitations including plaintext communication,protocol dependency,reliance on dedicated clients,and inefficiency under modern network conditions.These constraints hinder their applicability in emerging distributed and resource-constrained environments such as AIoT and browser-based systems.To address these challenges,this study proposes a novel port-sequence-based PAPC scheme structured as a modular model comprising a client,server,and ephemeral Key Management System(KMS).The system employs the Advanced Encryption Standard(AES-128)to protect message confidentiality and uses a Hash-Based Message Authentication Code(HMAC-SHA256)to ensure integrity.Authentication messages are securely fragmented and mapped to destination port numbers using a signature-based avoidance algorithm,which prevents collisions with unsafe or reserved port ranges.The server observes incoming port sequences,retrieves the necessary keys from the KMS,reconstructs and verifies the encrypted data,and conditionally updates firewall policies.Unlike SPA,which requires decrypting all incoming payloads and imposes server-side overhead,the proposed system verifies only port-derived fragments,significantly reducing computational burden.Furthermore,it eliminates the need for raw socket access or custom clients,supporting browser-based operation and enabling protocol-independent deployment.Through a functional web-based prototype and emulated testing,the system achieved an F1-score exceeding 95%in detecting unauthorized access while maintaining low resource overhead.Although port sequence generation introduces some client-side cost,it remains lightweight and scalable.By tightly integrating lightweight cryptographic algorithms with a transport-layer communication model,this work presents a conceptually validated architecture that contributes a novel direction for interoperable and scalable Zero Trust enforcement in future network ecosystems.展开更多
As the adoption of Vehicular Ad-hoc Networks(VANETs)grows,ensuring secure communication between smart vehicles and remote application servers(APPs)has become a critical challenge.While existing solutions focus on vari...As the adoption of Vehicular Ad-hoc Networks(VANETs)grows,ensuring secure communication between smart vehicles and remote application servers(APPs)has become a critical challenge.While existing solutions focus on various aspects of security,gaps remain in addressing both high security requirements and the resource-constrained nature of VANET environments.This paper proposes an extended-Kerberos protocol that integrates Physical Unclonable Function(PUF)for authentication and key agreement,offering a comprehensive solution to the security challenges in VANETs.The protocol facilitates mutual authentication and secure key agreement between vehicles and APPs,ensuring the confidentiality and integrity of vehicle-to-network(V2N)communications and preventing malicious data injection.Notably,by replacing traditional Kerberos password authentication with Challenge-Response Pairs(CRPs)generated by PUF,the protocol significantly reduces the risk of key leakage.The inherent properties of PUF—such as unclonability and unpredictability—make it an ideal defense against physical attacks,including intrusion,semi-intrusion,and side-channel attacks.The results of this study demonstrate that this approach not only enhances security but also optimizes communication efficiency,reduces latency,and improves overall user experience.The analysis proves that our protocol achieves at least 86%improvement in computational efficiency compared to some existed protocols.This is particularly crucial in resource-constrained VANET environments,where it enables efficient data transmission between vehicles and applications,reduces latency,and enhances the overall user experience.展开更多
As a model for the next generation of the Internet,the metaverse—a fully immersive,hyper-temporal virtual shared space—is transitioning from imagination to reality.At present,the metaverse has been widely applied in...As a model for the next generation of the Internet,the metaverse—a fully immersive,hyper-temporal virtual shared space—is transitioning from imagination to reality.At present,the metaverse has been widely applied in a variety of fields,including education,social entertainment,Internet of vehicles(IoV),healthcare,and virtual tours.In IoVs,researchers primarily focus on using the metaverse to improve the traffic safety of vehicles,while paying limited attention to passengers’social needs.At the same time,Social Internet ofVehicles(SIoV)introduces the concept of social networks in IoV to provide better resources and services for users.However,the problem of single interaction between SIoVand users has become increasingly prominent.In this paper,we first introduce a SIoVenvironment combined with the metaverse.In this environment,we adopt blockchain as the platform of the metaverse to provide a decentralized environment.Concerning passengers’social data may contain sensitive/private information,we then design an authentication and key agreement protocol calledMSIoV-AKAto protect the communications.Through formal security verifications in the real-or-random(ROR)model and using the AVISPA(Automated Validation of Internet Security Protocols and Applications)tool,we firmly verify the security of the protocol.Finally,detailed comparisons are made between our protocol and robust protocols/schemes in terms of computational cost and communication cost.In addition,we implement the MSIoV-AKA protocol in the Ethereum test network and Hyperledger Sawtooth to show the practicality.展开更多
Vehicular Ad-hoc Network(VANET)is a platform that facilitates Vehicle-to-Everything(V2X)interconnection.However,its open communication channels and high-speed mobility introduce security and privacy vulnerabilities.An...Vehicular Ad-hoc Network(VANET)is a platform that facilitates Vehicle-to-Everything(V2X)interconnection.However,its open communication channels and high-speed mobility introduce security and privacy vulnerabilities.Anonymous authentication is crucial in ensuring secure communication and privacy protection in VANET.However,existing anonymous authentication schemes are prone to single points of failure and often overlook the efficient tracking of the true identities of malicious vehicles after pseudonym changes.To address these challenges,we propose an efficient anonymous authentication scheme for blockchain-based VANET.By leveraging blockchain technology,our approach addresses the challenges of single points of failure and high latency,thereby enhancing the service stability and scalability of VANET.The scheme integrates homomorphic encryption and elliptic curve cryptography,allowing vehicles to independently generate new pseudonyms when entering a new domain without third-party assistance.Security analyses and simulation results demonstrate that our scheme achieves effective anonymous authentication in VANET.Moreover,the roadside unit can process 500 messages per 19 ms.As the number of vehicles in the communication domain grows,our scheme exhibits superior messageprocessing capabilities.展开更多
How to ensure the security of device access is a common concern in the Internet of Things(IoT)scenario with extremely high device connection density.To achieve efficient and secure network access for IoT devices with ...How to ensure the security of device access is a common concern in the Internet of Things(IoT)scenario with extremely high device connection density.To achieve efficient and secure network access for IoT devices with constrained resources,this paper proposes a lightweight physical-layer authentication protocol based on Physical Unclonable Function(PUF)and channel pre-equalization.PUF is employed as a secret carrier to provide authentication credentials for devices due to its hardware-based uniqueness and unclonable property.Meanwhile,the short-term reciprocity and spatio-temporal uniqueness of wireless channels are utilized to attach an authentication factor related to the spatio-temporal position of devices and to secure the transmission of authentication messages.The proposed protocol is analyzed formally and informally to prove its correctness and security against typical attacks.Simulation results show its robustness in various radio environments.Moreover,we illustrate the advantages of our protocol in terms of security features and complexity through performance comparison with existing authentication schemes.展开更多
With the rapid development and widespread adoption of Internet of Things(IoT)technology,the innovative concept of the Internet of Vehicles(IoV)has emerged,ushering in a new era of intelligent transportation.Since vehi...With the rapid development and widespread adoption of Internet of Things(IoT)technology,the innovative concept of the Internet of Vehicles(IoV)has emerged,ushering in a new era of intelligent transportation.Since vehicles are mobile entities,they move across different domains and need to communicate with the Roadside Unit(RSU)in various regions.However,open environments are highly susceptible to becoming targets for attackers,posing significant risks of malicious attacks.Therefore,it is crucial to design a secure authentication protocol to ensure the security of communication between vehicles and RSUs,particularly in scenarios where vehicles cross domains.In this paper,we propose a provably secure cross-domain authentication and key agreement protocol for IoV.Our protocol comprises two authentication phases:intra-domain authentication and cross-domain authentication.To ensure the security of our protocol,we conducted rigorous analyses based on the ROR(Real-or-Random)model and Scyther.Finally,we show in-depth comparisons of our protocol with existing ones from both security and performance perspectives,fully demonstrating its security and efficiency.展开更多
To date,many previous studies have been proposed for driver authentication;however,these solutions have many shortcomings and are still far from practical for real-world applications.In this paper,we tackle the shortc...To date,many previous studies have been proposed for driver authentication;however,these solutions have many shortcomings and are still far from practical for real-world applications.In this paper,we tackle the shortcomings of the existing solutions and reach toward proposing a lightweight and practical authentication system,dubbed DriveMe,for identifying drivers on cars.Our novelty aspects are 1⃝Lightweight scheme that depends only on a single sensor data(i.e.,pressure readings)attached to the driver’s seat and belt.2⃝Practical evaluation in which one-class authentication models are trained from only the owner users and tested using data collected from both owners and attackers.3⃝Rapid Authentication to quickly identify drivers’identities using a few pressure samples collected within short durations(1,2,3,5,or 10 s).4⃝Realistic experiments where the sensory data is collected from real experiments rather than computer simulation tools.We conducted real experiments and collected about 13,200 samples and 22,800 samples of belt-only and seat-only datasets from all 12 users under different settings.To evaluate system effectiveness,we implemented extensive evaluation scenarios using four one-class detectors One-Class Support Vector Machine(OCSVM),Local Outlier Factor(LOF),Isolation Forest(IF),and Elliptic Envelope(EE),three dataset types(belt-only,seat-only,and fusion),and four different dataset sizes.Our average experimental results show that the system can authenticate the driver with an F1 score of 93.1%for seat-based data using OCSVM classifier,an F1 score of 98.53%for fusion-based data using LOF classifier,an F1 score of 91.65%for fusion-based data using IF classifier,and an F1 score of 95.79%for fusion-based data using EE classifier.展开更多
In the rapidly evolving landscape of intelligent transportation systems,the security and authenticity of vehicular communication have emerged as critical challenges.As vehicles become increasingly interconnected,the n...In the rapidly evolving landscape of intelligent transportation systems,the security and authenticity of vehicular communication have emerged as critical challenges.As vehicles become increasingly interconnected,the need for robust authentication mechanisms to safeguard against cyber threats and ensure trust in an autonomous ecosystem becomes essential.On the other hand,using intelligence in the authentication system is a significant attraction.While existing surveys broadly address vehicular security,a critical gap remains in the systematic exploration of Deep Learning(DL)-based authentication methods tailored to these communication paradigms.This survey fills that gap by offering a comprehensive analysis of DL techniques—including supervised,unsupervised,reinforcement,and hybrid learning—for vehicular authentication.This survey highlights novel contributions,such as a taxonomy of DL-driven authentication protocols,real-world case studies,and a critical evaluation of scalability and privacy-preserving techniques.Additionally,this paper identifies unresolved challenges,such as adversarial resilience and real-time processing constraints,and proposes actionable future directions,including lightweight model optimization and blockchain integration.By grounding the discussion in concrete applications,such as biometric authentication for driver safety and adaptive key management for infrastructure security,this survey bridges theoretical advancements with practical deployment needs,offering a roadmap for next-generation secure intelligent vehicular ecosystems for the modern world.展开更多
Because the modified remote user authentication scheme proposed by Shen, Lin and Hwang is insecure, the Shen-Lin-Hwang＇ s scheme is improved and a new secure remote user authentication scheme based on the bi- linear ...Because the modified remote user authentication scheme proposed by Shen, Lin and Hwang is insecure, the Shen-Lin-Hwang＇ s scheme is improved and a new secure remote user authentication scheme based on the bi- linear parings is proposed. Moreover, the effectiveness of the new scheme is analyzed, and it is proved that the new scheme can prevent from all kinds of known attack. The one-way hash function is effective in the new scheme. The new scheme is proved that it has high effectiveness and fast convergence speed. Moreover, the ap- plication of the new scheme is easy and operational.展开更多
The Internet of Things(IoT)is extensively applied across various industrial domains,such as smart homes,factories,and intelligent transportation,becoming integral to daily life.Establishing robust policies for managin...The Internet of Things(IoT)is extensively applied across various industrial domains,such as smart homes,factories,and intelligent transportation,becoming integral to daily life.Establishing robust policies for managing and governing IoT devices is imperative.Secure authentication for IoT devices in resource-constrained environments remains challenging due to the limitations of conventional complex protocols.Prior methodologies enhanced mutual authentication through key exchange protocols or complex operations,which are impractical for lightweight devices.To address this,our study introduces the privacy-preserving software-defined range proof(SDRP)model,which achieves secure authentication with low complexity.SDRP minimizes the overhead of confidentiality and authentication processes by utilizing range proof to verify whether the attribute information of a user falls within a specific range.Since authentication is performed using a digital ID sequence generated from indirect personal data,it can avoid the disclosure of actual individual attributes.Experimental results demonstrate that SDRP significantly improves security efficiency,increasing it by an average of 93.02%compared to conventional methods.It mitigates the trade-off between security and efficiency by reducing leakage risk by an average of 98.7%.展开更多
Car manufacturers aim to enhance the use of two-factor authentication (2FA) to protect keyless entry systems in contemporary cars. Despite providing significant ease for users, keyless entry systems have become more s...Car manufacturers aim to enhance the use of two-factor authentication (2FA) to protect keyless entry systems in contemporary cars. Despite providing significant ease for users, keyless entry systems have become more susceptible to appealing attacks like relay attacks and critical fob hacking. These weaknesses present considerable security threats, resulting in unauthorized entry and car theft. The suggested approach combines a conventional keyless entry feature with an extra security measure. Implementing multi-factor authentication significantly improves the security of systems that allow keyless entry by reducing the likelihood of unauthorized access. Research shows that the benefits of using two-factor authentication, such as a substantial increase in security, far outweigh any minor drawbacks.展开更多
The integration of artificial intelligence(AI)with advanced power technologies is transforming energy system management,particularly through real-time data monitoring and intelligent decision-making driven by Artifici...The integration of artificial intelligence(AI)with advanced power technologies is transforming energy system management,particularly through real-time data monitoring and intelligent decision-making driven by Artificial Intelligence Generated Content(AIGC).However,the openness of power system channels and the resource-constrained nature of power sensors have led to new challenges for the secure transmission of power data and decision instructions.Although traditional public key cryptographic primitives can offer high security,the substantial key management and computational overhead associated with these primitives make them unsuitable for power systems.To ensure the real-time and security of power data and command transmission,we propose a lightweight identity authentication scheme tailored for power AIGC systems.The scheme utilizes lightweight symmetric encryption algorithms,minimizing the resource overhead on power sensors.Additionally,it incorporates a dynamic credential update mechanism,which can realize the rotation and update of temporary credentials to ensure anonymity and security.We rigorously validate the security of the scheme using the Real-or-Random(ROR)model and AVISPA simulation,and the results show that our scheme can resist various active and passive attacks.Finally,performance comparisons and NS3 simulation results demonstrate that our proposed scheme offers enhanced security features with lower overhead,making it more suitable for power AIGC systems compared to existing solutions.展开更多
Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant attention.Compared with traditional encryption and blockchain technologies,PLA provides a more computationally effi...Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant attention.Compared with traditional encryption and blockchain technologies,PLA provides a more computationally efficient alternative to exploiting the properties of the wireless medium itself.Some existing PLA solutions rely on static mechanisms,which are insufficient to address the authentication challenges in fifth generation(5G)and beyond wireless networks.Additionally,with the massive increase in mobile device access,the communication security of the IoT is vulnerable to spoofing attacks.To overcome the above challenges,this paper proposes a lightweight deep convolutional neural network(CNN)equipped with squeeze and excitation module(SE module)in dynamic wireless environments,namely SE-ConvNet.To be more specific,a convolution factorization is developed to reduce the complexity of PLA models based on deep learning.Moreover,an SE module is designed in the deep CNN to enhance useful features andmaximize authentication accuracy.Compared with the existing solutions,the proposed SE-ConvNet enabled PLA scheme performs excellently in mobile and time-varying wireless environments while maintaining lower computational complexity.展开更多
Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunatel...Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.展开更多
The increasing importance of terminal privacy in the Unmanned Aerial Vehicle(UAV)network has led to a growing recognition of the crucial role of authentication technology in UAV network security.However,traditional au...The increasing importance of terminal privacy in the Unmanned Aerial Vehicle(UAV)network has led to a growing recognition of the crucial role of authentication technology in UAV network security.However,traditional authentication approaches are vulnerable due to the transmission of identity information between UAVs and cryptographic paradigm management centers over a public channel.These vulnerabilities include brute-force attacks,single point of failure,and information leakage.Blockchain,as a decentralized distributed ledger with blockchain storage,tamper-proof,secure,and trustworthy features,can solve problems such as single-point-of-failure and trust issues,while the hidden communication in the physical layer can effectively resist information leakage and violent attacks.In this paper,we propose a lightweight UAV network authentication mechanism that leverages blockchain and covert communication,where the identity information is transmitted as covert tags carried by normal modulated signals.In addition,a weight-based Practical Byzantine Fault-Tolerant(wPBFT)consensus protocol is devised,where the weights are determined by the channel states of UAVs and the outcomes of past authentication scenarios.Simulation results demonstrate that the proposed mechanism outperforms traditional benchmarks in terms of security and robustness,particularly under conditions of low Signal-to-Noise Ratio(SNR)and short tag length.展开更多
With the recent advances in quantum computing,the key agreement algorithm based on traditional cryptography theory,which is applied to the Internet of Things(IoT)scenario,will no longer be secure due to the possibilit...With the recent advances in quantum computing,the key agreement algorithm based on traditional cryptography theory,which is applied to the Internet of Things(IoT)scenario,will no longer be secure due to the possibility of information leakage.In this paper,we propose a anti-quantum dynamic authenticated group key agreement scheme(AQDA-GKA)according to the ring-learning with errors(RLWE)problem,which is suitable for IoT environments.First,the proposed AQDA-GKA scheme can implement a group key agreement against quantum computing attacks by leveraging an RLWE-based key agreement mechanism.Second,this scheme can achieve dynamic node management,ensuring that any node can freely join or exit the current group.Third,we formally prove that the proposed scheme can resist quantum computing attacks as well as collusion attacks.Finally,the performance and security analysis reveals that the proposed AQDA-GKA scheme is secure and effective.展开更多
Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backb...Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.展开更多
Lemon oils are broadly used as flavoring agents in beverages,foods,cosmetics and pharmaceuticals,yet the adulteration of natural,particularly cold pressed lemon oils is very common in the industry due to its unmet dem...Lemon oils are broadly used as flavoring agents in beverages,foods,cosmetics and pharmaceuticals,yet the adulteration of natural,particularly cold pressed lemon oils is very common in the industry due to its unmet demand and high cost.Nowadays,most quality control(QC)analysis of lemon oils is conducted by gas chromatography(GC)analysis,which is far from a reliable method.Oxygen heterocyclic compounds(OHCs)in non-volatile fraction are gaining increasing attention in authentication process because of the nearly finger-printing profiles of OHCs in cold pressed citrus essential oils.Our goal in this study was to identify OHCs using high performance liquid chromatography(HPLC)in lemon oils,establish OHC profiles,perform stepwise logistic regression analysis(SLRA)and build effective predicting model and further determine adulterated lemon oils by referencing the OHC profiles and established models.After HPLC analyses,profiling and SLRA modeling of 154 OHCs samples of industrial lemon oils,we found that the combination of isopimpinellin and total OHC concentration are essential and robust predictors to differentiate authentic samples from adulterated lemon oils with a success rate of 98%from the 5-fold cross validation.This study provided a reliable and efficient method in determining the authenticity of lemon oils.展开更多
In wireless communication,the problem of authenticating the transmitter’s identity is challeng-ing,especially for those terminal devices in which the security schemes based on cryptography are approxi-mately unfeasib...In wireless communication,the problem of authenticating the transmitter’s identity is challeng-ing,especially for those terminal devices in which the security schemes based on cryptography are approxi-mately unfeasible owing to limited resources.In this paper,a physical layer authentication scheme is pro-posed to detect whether there is anomalous access by the attackers disguised as legitimate users.Explicitly,channel state information(CSI)is used as a form of fingerprint to exploit spatial discrimination among de-vices in the wireless network and machine learning(ML)technology is employed to promote the improve-ment of authentication accuracy.Considering that the falsified messages are not accessible for authenticator during the training phase,deep support vector data de-scription(Deep SVDD)is selected to solve the one-class classification(OCC)problem.Simulation results show that Deep SVDD based scheme can tackle the challenges of physical layer authentication in wireless communication environments.展开更多
文摘To ensure the access security of 6G,physical-layer authentication(PLA)leverages the randomness and space-time-frequency uniqueness of the channel to provide unique identity signatures for transmitters.Furthermore,the introduction of artificial intelligence(AI)facilitates the learning of the distribution characteristics of channel fingerprints,effectively addressing the uncertainties and unknown dynamic challenges in wireless link modeling.This paper reviews representative AI-enabled PLA schemes and proposes a graph neural network(GNN)-based PLA approach in response to the challenges existing methods face in identifying mobile users.Simulation results demonstrate that the proposed method outperforms six baseline schemes in terms of authentication accuracy.Furthermore,this paper outlines the future development directions of PLA.
基金supported by Institute for Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2022-II221200)Convergence Security Core Talent Training Business(Chungnam National University).
文摘Pre-Authentication and Post-Connection(PAPC)plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication.While earlier approaches such as Port Knocking(PK)and Single Packet Authorization(SPA)introduced pre-authentication concepts,they suffer from limitations including plaintext communication,protocol dependency,reliance on dedicated clients,and inefficiency under modern network conditions.These constraints hinder their applicability in emerging distributed and resource-constrained environments such as AIoT and browser-based systems.To address these challenges,this study proposes a novel port-sequence-based PAPC scheme structured as a modular model comprising a client,server,and ephemeral Key Management System(KMS).The system employs the Advanced Encryption Standard(AES-128)to protect message confidentiality and uses a Hash-Based Message Authentication Code(HMAC-SHA256)to ensure integrity.Authentication messages are securely fragmented and mapped to destination port numbers using a signature-based avoidance algorithm,which prevents collisions with unsafe or reserved port ranges.The server observes incoming port sequences,retrieves the necessary keys from the KMS,reconstructs and verifies the encrypted data,and conditionally updates firewall policies.Unlike SPA,which requires decrypting all incoming payloads and imposes server-side overhead,the proposed system verifies only port-derived fragments,significantly reducing computational burden.Furthermore,it eliminates the need for raw socket access or custom clients,supporting browser-based operation and enabling protocol-independent deployment.Through a functional web-based prototype and emulated testing,the system achieved an F1-score exceeding 95%in detecting unauthorized access while maintaining low resource overhead.Although port sequence generation introduces some client-side cost,it remains lightweight and scalable.By tightly integrating lightweight cryptographic algorithms with a transport-layer communication model,this work presents a conceptually validated architecture that contributes a novel direction for interoperable and scalable Zero Trust enforcement in future network ecosystems.
基金supported in part by the Jiangsu“Qing Lan Project”,Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Major Research Project:23KJA520007)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX25_1303).
文摘As the adoption of Vehicular Ad-hoc Networks(VANETs)grows,ensuring secure communication between smart vehicles and remote application servers(APPs)has become a critical challenge.While existing solutions focus on various aspects of security,gaps remain in addressing both high security requirements and the resource-constrained nature of VANET environments.This paper proposes an extended-Kerberos protocol that integrates Physical Unclonable Function(PUF)for authentication and key agreement,offering a comprehensive solution to the security challenges in VANETs.The protocol facilitates mutual authentication and secure key agreement between vehicles and APPs,ensuring the confidentiality and integrity of vehicle-to-network(V2N)communications and preventing malicious data injection.Notably,by replacing traditional Kerberos password authentication with Challenge-Response Pairs(CRPs)generated by PUF,the protocol significantly reduces the risk of key leakage.The inherent properties of PUF—such as unclonability and unpredictability—make it an ideal defense against physical attacks,including intrusion,semi-intrusion,and side-channel attacks.The results of this study demonstrate that this approach not only enhances security but also optimizes communication efficiency,reduces latency,and improves overall user experience.The analysis proves that our protocol achieves at least 86%improvement in computational efficiency compared to some existed protocols.This is particularly crucial in resource-constrained VANET environments,where it enables efficient data transmission between vehicles and applications,reduces latency,and enhances the overall user experience.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology and Natural Science Foundation of Shandong Province,China(Grant no.ZR202111230202).
文摘As a model for the next generation of the Internet,the metaverse—a fully immersive,hyper-temporal virtual shared space—is transitioning from imagination to reality.At present,the metaverse has been widely applied in a variety of fields,including education,social entertainment,Internet of vehicles(IoV),healthcare,and virtual tours.In IoVs,researchers primarily focus on using the metaverse to improve the traffic safety of vehicles,while paying limited attention to passengers’social needs.At the same time,Social Internet ofVehicles(SIoV)introduces the concept of social networks in IoV to provide better resources and services for users.However,the problem of single interaction between SIoVand users has become increasingly prominent.In this paper,we first introduce a SIoVenvironment combined with the metaverse.In this environment,we adopt blockchain as the platform of the metaverse to provide a decentralized environment.Concerning passengers’social data may contain sensitive/private information,we then design an authentication and key agreement protocol calledMSIoV-AKAto protect the communications.Through formal security verifications in the real-or-random(ROR)model and using the AVISPA(Automated Validation of Internet Security Protocols and Applications)tool,we firmly verify the security of the protocol.Finally,detailed comparisons are made between our protocol and robust protocols/schemes in terms of computational cost and communication cost.In addition,we implement the MSIoV-AKA protocol in the Ethereum test network and Hyperledger Sawtooth to show the practicality.
基金supported by the National Natural Science Foundation of China under Grant U2001213.
文摘Vehicular Ad-hoc Network(VANET)is a platform that facilitates Vehicle-to-Everything(V2X)interconnection.However,its open communication channels and high-speed mobility introduce security and privacy vulnerabilities.Anonymous authentication is crucial in ensuring secure communication and privacy protection in VANET.However,existing anonymous authentication schemes are prone to single points of failure and often overlook the efficient tracking of the true identities of malicious vehicles after pseudonym changes.To address these challenges,we propose an efficient anonymous authentication scheme for blockchain-based VANET.By leveraging blockchain technology,our approach addresses the challenges of single points of failure and high latency,thereby enhancing the service stability and scalability of VANET.The scheme integrates homomorphic encryption and elliptic curve cryptography,allowing vehicles to independently generate new pseudonyms when entering a new domain without third-party assistance.Security analyses and simulation results demonstrate that our scheme achieves effective anonymous authentication in VANET.Moreover,the roadside unit can process 500 messages per 19 ms.As the number of vehicles in the communication domain grows,our scheme exhibits superior messageprocessing capabilities.
基金supported by National Natural Science Foundation of China(No.61931020,No.U19B2024 and No.62371462).
文摘How to ensure the security of device access is a common concern in the Internet of Things(IoT)scenario with extremely high device connection density.To achieve efficient and secure network access for IoT devices with constrained resources,this paper proposes a lightweight physical-layer authentication protocol based on Physical Unclonable Function(PUF)and channel pre-equalization.PUF is employed as a secret carrier to provide authentication credentials for devices due to its hardware-based uniqueness and unclonable property.Meanwhile,the short-term reciprocity and spatio-temporal uniqueness of wireless channels are utilized to attach an authentication factor related to the spatio-temporal position of devices and to secure the transmission of authentication messages.The proposed protocol is analyzed formally and informally to prove its correctness and security against typical attacks.Simulation results show its robustness in various radio environments.Moreover,we illustrate the advantages of our protocol in terms of security features and complexity through performance comparison with existing authentication schemes.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology and Natural Science Foundation of Shandong Province,China(Grant no.ZR202111230202).
文摘With the rapid development and widespread adoption of Internet of Things(IoT)technology,the innovative concept of the Internet of Vehicles(IoV)has emerged,ushering in a new era of intelligent transportation.Since vehicles are mobile entities,they move across different domains and need to communicate with the Roadside Unit(RSU)in various regions.However,open environments are highly susceptible to becoming targets for attackers,posing significant risks of malicious attacks.Therefore,it is crucial to design a secure authentication protocol to ensure the security of communication between vehicles and RSUs,particularly in scenarios where vehicles cross domains.In this paper,we propose a provably secure cross-domain authentication and key agreement protocol for IoV.Our protocol comprises two authentication phases:intra-domain authentication and cross-domain authentication.To ensure the security of our protocol,we conducted rigorous analyses based on the ROR(Real-or-Random)model and Scyther.Finally,we show in-depth comparisons of our protocol with existing ones from both security and performance perspectives,fully demonstrating its security and efficiency.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(1ITP)(Project Nos.RS-2024-00438551,30%,2022-11220701,30%,2021-0-01816,30%)the National Research Foundation of Korea(NRF)grant funded by the Korean Government(Project No.RS2023-00208460,10%).
文摘To date,many previous studies have been proposed for driver authentication;however,these solutions have many shortcomings and are still far from practical for real-world applications.In this paper,we tackle the shortcomings of the existing solutions and reach toward proposing a lightweight and practical authentication system,dubbed DriveMe,for identifying drivers on cars.Our novelty aspects are 1⃝Lightweight scheme that depends only on a single sensor data(i.e.,pressure readings)attached to the driver’s seat and belt.2⃝Practical evaluation in which one-class authentication models are trained from only the owner users and tested using data collected from both owners and attackers.3⃝Rapid Authentication to quickly identify drivers’identities using a few pressure samples collected within short durations(1,2,3,5,or 10 s).4⃝Realistic experiments where the sensory data is collected from real experiments rather than computer simulation tools.We conducted real experiments and collected about 13,200 samples and 22,800 samples of belt-only and seat-only datasets from all 12 users under different settings.To evaluate system effectiveness,we implemented extensive evaluation scenarios using four one-class detectors One-Class Support Vector Machine(OCSVM),Local Outlier Factor(LOF),Isolation Forest(IF),and Elliptic Envelope(EE),three dataset types(belt-only,seat-only,and fusion),and four different dataset sizes.Our average experimental results show that the system can authenticate the driver with an F1 score of 93.1%for seat-based data using OCSVM classifier,an F1 score of 98.53%for fusion-based data using LOF classifier,an F1 score of 91.65%for fusion-based data using IF classifier,and an F1 score of 95.79%for fusion-based data using EE classifier.
基金funded and supported by the UCSI University Research Excellence&Innovation Grant(REIG),REIG-ICSDI-2024/044.
文摘In the rapidly evolving landscape of intelligent transportation systems,the security and authenticity of vehicular communication have emerged as critical challenges.As vehicles become increasingly interconnected,the need for robust authentication mechanisms to safeguard against cyber threats and ensure trust in an autonomous ecosystem becomes essential.On the other hand,using intelligence in the authentication system is a significant attraction.While existing surveys broadly address vehicular security,a critical gap remains in the systematic exploration of Deep Learning(DL)-based authentication methods tailored to these communication paradigms.This survey fills that gap by offering a comprehensive analysis of DL techniques—including supervised,unsupervised,reinforcement,and hybrid learning—for vehicular authentication.This survey highlights novel contributions,such as a taxonomy of DL-driven authentication protocols,real-world case studies,and a critical evaluation of scalability and privacy-preserving techniques.Additionally,this paper identifies unresolved challenges,such as adversarial resilience and real-time processing constraints,and proposes actionable future directions,including lightweight model optimization and blockchain integration.By grounding the discussion in concrete applications,such as biometric authentication for driver safety and adaptive key management for infrastructure security,this survey bridges theoretical advancements with practical deployment needs,offering a roadmap for next-generation secure intelligent vehicular ecosystems for the modern world.
基金Supported by the National Science Foundation for Young Scholars of China(61001091)~~
文摘Because the modified remote user authentication scheme proposed by Shen, Lin and Hwang is insecure, the Shen-Lin-Hwang＇ s scheme is improved and a new secure remote user authentication scheme based on the bi- linear parings is proposed. Moreover, the effectiveness of the new scheme is analyzed, and it is proved that the new scheme can prevent from all kinds of known attack. The one-way hash function is effective in the new scheme. The new scheme is proved that it has high effectiveness and fast convergence speed. Moreover, the ap- plication of the new scheme is easy and operational.
基金funding from the Korea Institute for Advancement of Technology(KIAT)through a grant provided by the Korean Government Ministry of Trade,Industry,and Energy(MOTIE)(RS-2024-00415520,Training Industrial Security Specialist for High-Tech Industry)Additional support was received from the Ministry of Science and ICT(MSIT)under the ICAN(ICT Challenge and Advanced Network of HRD)program(No.IITP-2022-RS-2022-00156310)overseen by the Institute of Information&Communication Technology Planning and Evaluation(IITP).
文摘The Internet of Things(IoT)is extensively applied across various industrial domains,such as smart homes,factories,and intelligent transportation,becoming integral to daily life.Establishing robust policies for managing and governing IoT devices is imperative.Secure authentication for IoT devices in resource-constrained environments remains challenging due to the limitations of conventional complex protocols.Prior methodologies enhanced mutual authentication through key exchange protocols or complex operations,which are impractical for lightweight devices.To address this,our study introduces the privacy-preserving software-defined range proof(SDRP)model,which achieves secure authentication with low complexity.SDRP minimizes the overhead of confidentiality and authentication processes by utilizing range proof to verify whether the attribute information of a user falls within a specific range.Since authentication is performed using a digital ID sequence generated from indirect personal data,it can avoid the disclosure of actual individual attributes.Experimental results demonstrate that SDRP significantly improves security efficiency,increasing it by an average of 93.02%compared to conventional methods.It mitigates the trade-off between security and efficiency by reducing leakage risk by an average of 98.7%.
文摘Car manufacturers aim to enhance the use of two-factor authentication (2FA) to protect keyless entry systems in contemporary cars. Despite providing significant ease for users, keyless entry systems have become more susceptible to appealing attacks like relay attacks and critical fob hacking. These weaknesses present considerable security threats, resulting in unauthorized entry and car theft. The suggested approach combines a conventional keyless entry feature with an extra security measure. Implementing multi-factor authentication significantly improves the security of systems that allow keyless entry by reducing the likelihood of unauthorized access. Research shows that the benefits of using two-factor authentication, such as a substantial increase in security, far outweigh any minor drawbacks.
文摘The integration of artificial intelligence(AI)with advanced power technologies is transforming energy system management,particularly through real-time data monitoring and intelligent decision-making driven by Artificial Intelligence Generated Content(AIGC).However,the openness of power system channels and the resource-constrained nature of power sensors have led to new challenges for the secure transmission of power data and decision instructions.Although traditional public key cryptographic primitives can offer high security,the substantial key management and computational overhead associated with these primitives make them unsuitable for power systems.To ensure the real-time and security of power data and command transmission,we propose a lightweight identity authentication scheme tailored for power AIGC systems.The scheme utilizes lightweight symmetric encryption algorithms,minimizing the resource overhead on power sensors.Additionally,it incorporates a dynamic credential update mechanism,which can realize the rotation and update of temporary credentials to ensure anonymity and security.We rigorously validate the security of the scheme using the Real-or-Random(ROR)model and AVISPA simulation,and the results show that our scheme can resist various active and passive attacks.Finally,performance comparisons and NS3 simulation results demonstrate that our proposed scheme offers enhanced security features with lower overhead,making it more suitable for power AIGC systems compared to existing solutions.
基金supported in part by the National Key R&D Program of China under grant no.2022YFB2703000in part by the Young Backbone Teachers Support Plan of BISTU under grant no.YBT202437+1 种基金in part by the R&D Program of Beijing Municipal Education Commission under grant no.KM202211232012in part by the Educational Innovation Program of BISTU under grant no.2025JGYB19。
文摘Physical layer authentication(PLA)in the context of the Internet of Things(IoT)has gained significant attention.Compared with traditional encryption and blockchain technologies,PLA provides a more computationally efficient alternative to exploiting the properties of the wireless medium itself.Some existing PLA solutions rely on static mechanisms,which are insufficient to address the authentication challenges in fifth generation(5G)and beyond wireless networks.Additionally,with the massive increase in mobile device access,the communication security of the IoT is vulnerable to spoofing attacks.To overcome the above challenges,this paper proposes a lightweight deep convolutional neural network(CNN)equipped with squeeze and excitation module(SE module)in dynamic wireless environments,namely SE-ConvNet.To be more specific,a convolution factorization is developed to reduce the complexity of PLA models based on deep learning.Moreover,an SE module is designed in the deep CNN to enhance useful features andmaximize authentication accuracy.Compared with the existing solutions,the proposed SE-ConvNet enabled PLA scheme performs excellently in mobile and time-varying wireless environments while maintaining lower computational complexity.
文摘Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.
基金supported by the Hainan Province Science and Technology Special Fund,China(No.ZDYF2024GXJS292).
文摘The increasing importance of terminal privacy in the Unmanned Aerial Vehicle(UAV)network has led to a growing recognition of the crucial role of authentication technology in UAV network security.However,traditional authentication approaches are vulnerable due to the transmission of identity information between UAVs and cryptographic paradigm management centers over a public channel.These vulnerabilities include brute-force attacks,single point of failure,and information leakage.Blockchain,as a decentralized distributed ledger with blockchain storage,tamper-proof,secure,and trustworthy features,can solve problems such as single-point-of-failure and trust issues,while the hidden communication in the physical layer can effectively resist information leakage and violent attacks.In this paper,we propose a lightweight UAV network authentication mechanism that leverages blockchain and covert communication,where the identity information is transmitted as covert tags carried by normal modulated signals.In addition,a weight-based Practical Byzantine Fault-Tolerant(wPBFT)consensus protocol is devised,where the weights are determined by the channel states of UAVs and the outcomes of past authentication scenarios.Simulation results demonstrate that the proposed mechanism outperforms traditional benchmarks in terms of security and robustness,particularly under conditions of low Signal-to-Noise Ratio(SNR)and short tag length.
基金Supported by the National Engineering Research Center of Classified Protection and Safeguard Technology for Cybersecurity(No.C23640-XD-07)the Open Foundation of Key Laboratory of Cyberspace Security of Ministry of Education of China and Henan Key Laboratory of Network Cryptography(No.KLCS20240301)。
文摘With the recent advances in quantum computing,the key agreement algorithm based on traditional cryptography theory,which is applied to the Internet of Things(IoT)scenario,will no longer be secure due to the possibility of information leakage.In this paper,we propose a anti-quantum dynamic authenticated group key agreement scheme(AQDA-GKA)according to the ring-learning with errors(RLWE)problem,which is suitable for IoT environments.First,the proposed AQDA-GKA scheme can implement a group key agreement against quantum computing attacks by leveraging an RLWE-based key agreement mechanism.Second,this scheme can achieve dynamic node management,ensuring that any node can freely join or exit the current group.Third,we formally prove that the proposed scheme can resist quantum computing attacks as well as collusion attacks.Finally,the performance and security analysis reveals that the proposed AQDA-GKA scheme is secure and effective.
文摘Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.
文摘Lemon oils are broadly used as flavoring agents in beverages,foods,cosmetics and pharmaceuticals,yet the adulteration of natural,particularly cold pressed lemon oils is very common in the industry due to its unmet demand and high cost.Nowadays,most quality control(QC)analysis of lemon oils is conducted by gas chromatography(GC)analysis,which is far from a reliable method.Oxygen heterocyclic compounds(OHCs)in non-volatile fraction are gaining increasing attention in authentication process because of the nearly finger-printing profiles of OHCs in cold pressed citrus essential oils.Our goal in this study was to identify OHCs using high performance liquid chromatography(HPLC)in lemon oils,establish OHC profiles,perform stepwise logistic regression analysis(SLRA)and build effective predicting model and further determine adulterated lemon oils by referencing the OHC profiles and established models.After HPLC analyses,profiling and SLRA modeling of 154 OHCs samples of industrial lemon oils,we found that the combination of isopimpinellin and total OHC concentration are essential and robust predictors to differentiate authentic samples from adulterated lemon oils with a success rate of 98%from the 5-fold cross validation.This study provided a reliable and efficient method in determining the authenticity of lemon oils.
基金partially supported by the National Key Research and Development Project under Grant2020YFB1806805Social Development Projects of Jiangsu Science and Technology Department under Grant No.BE2018704
文摘In wireless communication,the problem of authenticating the transmitter’s identity is challeng-ing,especially for those terminal devices in which the security schemes based on cryptography are approxi-mately unfeasible owing to limited resources.In this paper,a physical layer authentication scheme is pro-posed to detect whether there is anomalous access by the attackers disguised as legitimate users.Explicitly,channel state information(CSI)is used as a form of fingerprint to exploit spatial discrimination among de-vices in the wireless network and machine learning(ML)technology is employed to promote the improve-ment of authentication accuracy.Considering that the falsified messages are not accessible for authenticator during the training phase,deep support vector data de-scription(Deep SVDD)is selected to solve the one-class classification(OCC)problem.Simulation results show that Deep SVDD based scheme can tackle the challenges of physical layer authentication in wireless communication environments.
