Cloud Computing expands its usability to various fields that utilize data and store it in a common space that is required for computing and the purpose of analysis as like the IoT devices.These devices utilize the clo...Cloud Computing expands its usability to various fields that utilize data and store it in a common space that is required for computing and the purpose of analysis as like the IoT devices.These devices utilize the cloud for storing and retrieving data since the devices are not capable of storing processing data on its own.Cloud Computing provides various services to the users like the IaaS,PaaS and SaaS.The major drawback that is faced by cloud computing include the Utilization of Cloud services for the storage of data that could be accessed by all the users related to cloud.The use of Public Key Encryptions with keyword search(PEKS)provides security against the untrustworthy third-party search capability on publicly encryption keys without revealing the data’s contents.But the Security concerns of PEKs arise when Inside Keywords Guessing attacks(IKGA),is identified in the system due to the untrusted server presume the keyword in trapdoor.This issue could be solved by using various algorithms like the Certificateless Hashed Public Key Authenticated Encryption with Keyword Search(CL-HPAEKS)which utilizes the Modified Elliptic Curve Cryptography(MECC)along with the Mutation Centred flower pollinations algorithm(CM-FPA)that is used in enhancing the performance of the algorithm using the Optimization in keys.The additional use of Message Digests 5(MD5)hash function in the system enhances the security Level that is associated with the system.The system that is proposed achieves the security level performance of 96 percent and the effort consumed by the algorithm is less compared to the other encryption techniques.展开更多
As a major component of thefifth-generation(5G)wireless networks,network densification greatly increases the network capacity by adding more cell sites into the network.However,the densified network increases the hand...As a major component of thefifth-generation(5G)wireless networks,network densification greatly increases the network capacity by adding more cell sites into the network.However,the densified network increases the handover frequency of fast-moving mobile users,like vehicles.Thus,seamless handover with security provision is highly desirable in 5G networks.The third generation partnership project(3GPP)has been working on standardization of the handover procedure in 5G networks to meet the stringent efficiency and security requirement.However,the existing handover authentication process in 5G networks has securityflaws,i.e.vulnerable to replay and de-synchronization attacks,and cannot provide perfect forward secrecy.In this paper,we propose a secure and efficient handover authentication and key management protocol utilizing the Chinese remainder theory.The proposed scheme preserves the majority part of the original 5G system architecture defined by 3GPP,thus can be easily implemented in practice.Formal security analysis based on BAN-logic shows that the proposed scheme achieves secure mutual authentication and can remedy some security flaws in original 5G handover process.Performance analysis shows that the proposed protocol has lower communication overhead and computation overhead compared with other handover authentication schemes.展开更多
Purpose-Due to the connectivity of the multiple devices and the systems on the same network,rapid development has become possible in Internet of Things(IoTs)for the last decade.But,IoT is mostly affected with severe s...Purpose-Due to the connectivity of the multiple devices and the systems on the same network,rapid development has become possible in Internet of Things(IoTs)for the last decade.But,IoT is mostly affected with severe security challenges due to the potential vulnerabilities happened through the multiple connectivity of sensors,devices and system.In order to handle the security challenges,literature presents a handful of security protocols for IoT.The purpose of this paper is to present a threat profiling and elliptic curve cryptography(ECC)-based mutual and multi-level authentication for the security of IoTs.This work contains two security attributes like memory and machine-related attributes for maintaining the profile table.Also,the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol.Furthermore,three entities like,IoT device,server and authorization centre(AC)performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks.Finally,DPWSim is utilized for simulation of IoT and verification of proposed protocol to show that the protocol is secure against passive and active attacks.Design/methodology/approach-In this work,the authors have presented a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs.This work contains two security attributes like memory and machine-related attributes for maintaining the profile table.Also,the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol.Furthermore,three entities like,IoT device,server and AC performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks.Findings-DPWSim is utilized for simulation of IoT and verification of the proposed protocol to show that this protocol is secure against passive and active attacks.Also,attack analysis is carried out to prove the robustness of the proposed protocol against the password guessing attack,impersonation attack,server spoofing attack,stolen verifier attack and reply attack.Originality/value-This paper presents a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs.展开更多
User Equipment(UE)authentication holds paramount importance in upholding the security of wireless networks.A nascent technology,Radio Frequency Fingerprint Identification(RFFI),is gaining prominence as a means to bols...User Equipment(UE)authentication holds paramount importance in upholding the security of wireless networks.A nascent technology,Radio Frequency Fingerprint Identification(RFFI),is gaining prominence as a means to bolster network security authentication.To expedite the integration of RFFI within fifth-generation(5G)networks,this research undertakes the creation of a comprehensive link-level simulation platform tailored for 5G scenarios.The devised platform emulates various device impairments,including an oscillator,IQ modulator,and power amplifier(PA)nonlinearities,alongside simulating channel distortions.Consequent to this,a plausibility analysis is executed,intertwining transmitter device impairments with 3rd Generation Partnership Project(3GPP)new radio(NR)protocols.Subsequently,an exhaustive exploration is conducted to assess the impact of transmitter impairments,deep neural networks(DNNs),and channel effects on RF fingerprinting performance.Notably,under a signal-to-noise ratio(SNR)of 15 d B,the deep learning approach demonstrates the capability to accurately classify 100 UEs with a commendable 91%accuracy rate.Through a multifaceted evaluation,it is ascertained that the Attention-based network architecture emerges as the optimal choice for the RFFI task,serving as the new benchmark model for RFFI applications.展开更多
文摘Cloud Computing expands its usability to various fields that utilize data and store it in a common space that is required for computing and the purpose of analysis as like the IoT devices.These devices utilize the cloud for storing and retrieving data since the devices are not capable of storing processing data on its own.Cloud Computing provides various services to the users like the IaaS,PaaS and SaaS.The major drawback that is faced by cloud computing include the Utilization of Cloud services for the storage of data that could be accessed by all the users related to cloud.The use of Public Key Encryptions with keyword search(PEKS)provides security against the untrustworthy third-party search capability on publicly encryption keys without revealing the data’s contents.But the Security concerns of PEKs arise when Inside Keywords Guessing attacks(IKGA),is identified in the system due to the untrusted server presume the keyword in trapdoor.This issue could be solved by using various algorithms like the Certificateless Hashed Public Key Authenticated Encryption with Keyword Search(CL-HPAEKS)which utilizes the Modified Elliptic Curve Cryptography(MECC)along with the Mutation Centred flower pollinations algorithm(CM-FPA)that is used in enhancing the performance of the algorithm using the Optimization in keys.The additional use of Message Digests 5(MD5)hash function in the system enhances the security Level that is associated with the system.The system that is proposed achieves the security level performance of 96 percent and the effort consumed by the algorithm is less compared to the other encryption techniques.
文摘As a major component of thefifth-generation(5G)wireless networks,network densification greatly increases the network capacity by adding more cell sites into the network.However,the densified network increases the handover frequency of fast-moving mobile users,like vehicles.Thus,seamless handover with security provision is highly desirable in 5G networks.The third generation partnership project(3GPP)has been working on standardization of the handover procedure in 5G networks to meet the stringent efficiency and security requirement.However,the existing handover authentication process in 5G networks has securityflaws,i.e.vulnerable to replay and de-synchronization attacks,and cannot provide perfect forward secrecy.In this paper,we propose a secure and efficient handover authentication and key management protocol utilizing the Chinese remainder theory.The proposed scheme preserves the majority part of the original 5G system architecture defined by 3GPP,thus can be easily implemented in practice.Formal security analysis based on BAN-logic shows that the proposed scheme achieves secure mutual authentication and can remedy some security flaws in original 5G handover process.Performance analysis shows that the proposed protocol has lower communication overhead and computation overhead compared with other handover authentication schemes.
文摘Purpose-Due to the connectivity of the multiple devices and the systems on the same network,rapid development has become possible in Internet of Things(IoTs)for the last decade.But,IoT is mostly affected with severe security challenges due to the potential vulnerabilities happened through the multiple connectivity of sensors,devices and system.In order to handle the security challenges,literature presents a handful of security protocols for IoT.The purpose of this paper is to present a threat profiling and elliptic curve cryptography(ECC)-based mutual and multi-level authentication for the security of IoTs.This work contains two security attributes like memory and machine-related attributes for maintaining the profile table.Also,the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol.Furthermore,three entities like,IoT device,server and authorization centre(AC)performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks.Finally,DPWSim is utilized for simulation of IoT and verification of proposed protocol to show that the protocol is secure against passive and active attacks.Design/methodology/approach-In this work,the authors have presented a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs.This work contains two security attributes like memory and machine-related attributes for maintaining the profile table.Also,the profile table stores the value after encrypting the value with ECC to avoid storage resilience using the proposed protocol.Furthermore,three entities like,IoT device,server and AC performs the verification based on seven levels mutually to provide the resilience against most of the widely accepted attacks.Findings-DPWSim is utilized for simulation of IoT and verification of the proposed protocol to show that this protocol is secure against passive and active attacks.Also,attack analysis is carried out to prove the robustness of the proposed protocol against the password guessing attack,impersonation attack,server spoofing attack,stolen verifier attack and reply attack.Originality/value-This paper presents a threat profiling and ECC-based mutual and multi-level authentication for the security of IoTs.
基金supported by the National Natural Science Foundation of China(No:62201172)the National Key Research and Development Program of China(2022YFE0136800)
文摘User Equipment(UE)authentication holds paramount importance in upholding the security of wireless networks.A nascent technology,Radio Frequency Fingerprint Identification(RFFI),is gaining prominence as a means to bolster network security authentication.To expedite the integration of RFFI within fifth-generation(5G)networks,this research undertakes the creation of a comprehensive link-level simulation platform tailored for 5G scenarios.The devised platform emulates various device impairments,including an oscillator,IQ modulator,and power amplifier(PA)nonlinearities,alongside simulating channel distortions.Consequent to this,a plausibility analysis is executed,intertwining transmitter device impairments with 3rd Generation Partnership Project(3GPP)new radio(NR)protocols.Subsequently,an exhaustive exploration is conducted to assess the impact of transmitter impairments,deep neural networks(DNNs),and channel effects on RF fingerprinting performance.Notably,under a signal-to-noise ratio(SNR)of 15 d B,the deep learning approach demonstrates the capability to accurately classify 100 UEs with a commendable 91%accuracy rate.Through a multifaceted evaluation,it is ascertained that the Attention-based network architecture emerges as the optimal choice for the RFFI task,serving as the new benchmark model for RFFI applications.
