FL-EASGD:Federated Learning Privacy Security Method Based on Homomorphic Encryption

Federated learning ensures data privacy and security by sharing models among multiple computing nodes instead of plaintext data.However,there is still a potential risk of privacy leakage,for example,attackers can obtain the original data through model inference attacks.Therefore,safeguarding the privacy of model parameters becomes crucial.One proposed solution involves incorporating homomorphic encryption algorithms into the federated learning process.However,the existing federated learning privacy protection scheme based on homomorphic encryption will greatly reduce the efficiency and robustness when there are performance differences between parties or abnormal nodes.To solve the above problems,this paper proposes a privacy protection scheme named Federated Learning-Elastic Averaging Stochastic Gradient Descent(FL-EASGD)based on a fully homomorphic encryption algorithm.First,this paper introduces the homomorphic encryption algorithm into the FL-EASGD scheme to preventmodel plaintext leakage and realize privacy security in the process ofmodel aggregation.Second,this paper designs a robust model aggregation algorithm by adding time variables and constraint coefficients,which ensures the accuracy of model prediction while solving performance differences such as computation speed and node anomalies such as downtime of each participant.In addition,the scheme in this paper preserves the independent exploration of the local model by the nodes of each party,making the model more applicable to the local data distribution.Finally,experimental analysis shows that when there are abnormalities in the participants,the efficiency and accuracy of the whole protocol are not significantly affected.

Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things

In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.

A Post-Quantum Cross-Domain Authentication Scheme Based on Multi-Chain Architecture

Due to the rapid advancements in network technology,blockchain is being employed for distributed data storage.In the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication techniques.However,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security threat.In response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange process.Firstly,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication scheme.Secondly,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust domains.Furthermore,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum security.Last but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.

QBIoT:A Quantum Blockchain Framework for IoT with an Improved Proof-of-Authority Consensus Algorithm and a Public-Key Quantum Signature

The Internet of Things(IoT)is a network system that connects physical devices through the Internet,allowing them to interact.Nowadays,IoT has become an integral part of our lives,offering convenience and smart functionality.However,the growing number of IoT devices has brought about a corresponding increase in cybersecurity threats,such as device vulnerabilities,data privacy concerns,and network susceptibilities.Integrating blockchain technology with IoT has proven to be a promising approach to enhance IoT security.Nevertheless,the emergence of quantum computing poses a significant challenge to the security of traditional classical cryptography used in blockchain,potentially exposing it to quantum cyber-attacks.To support the growth of the IoT industry,mitigate quantum threats,and safeguard IoT data,this study proposes a robust blockchain solution for IoT that incorporates both classical and post-quantum security measures.Firstly,we present the Quantum-Enhanced Blockchain Architecture for IoT(QBIoT)to ensure secure data sharing and integrity protection.Secondly,we propose an improved Proof of Authority consensus algorithm called“Proof of Authority with Random Election”(PoARE),implemented within QBIoT for leader selection and new block creation.Thirdly,we develop a publickey quantum signature protocol for transaction verification in the blockchain.Finally,a comprehensive security analysis of QBIoT demonstrates its resilience against cyber threats from both classical and quantum adversaries.In summary,this research introduces an innovative quantum-enhanced blockchain solution to address quantum security concernswithin the realmof IoT.The proposedQBIoT framework contributes to the ongoing development of quantum blockchain technology and offers valuable insights for future research on IoT security.

Improving Security and Sharing in Online Social Efficiency for Encrypted Data Networks

Despite that existing data sharing systems in online social networks （OSNs） propose to encrypt data before sharing, the multiparty access control of encrypted data has become a challenging issue. In this paper, we propose a secure data sharing scheme in 0SNs based on ciphertext-policy attribute- based proxy re-encryption and secret sharing. In order to protect users＇ sensitive data, our scheme allows users to customize access policies of their data and then outsource encrypted data to the OSNs service provider. Our scheme presents a multiparty access control model, which enables the disseminator to update the access policy of ciphertext if their attributes satisfy the existing access policy. Further, we present a partial decryption construction in which the computation overhead of user is largely reduced by delegating most of the decryption operations to the OSNs service provider. We also provide checkability on the results returned from the OSNs service provider to guarantee the correctness of partial decrypted ciphertext. Moreover, our scheme presents an efficient attribute revocation method that achieves both forward and backward secrecy. The security and performance analysis results indicate that the proposed scheme is secure and efficient in OSNs.

A novel quantum information hiding protocol based on entanglement swapping of high-level Bell states

Using entanglement swapping of high-level Bell states, we first derive a covert layer between the secret message and the possible output results of the entanglement swapping between any two generalized Bell states, and then propose a novel high-efficiency quantum information hiding protocol based on the covert layer. In the proposed scheme, a covert channel can be built up under the cover of a high-level quantum secure direct communication （QSDC） channel for securely transmitting secret messages without consuming any auxiliary quantum state or any extra communication resource. It is shown that this protocol not only has a high embedding efficiency but also achieves a good imperceptibility as well as a high security.

Controlled Quantum Network Coding Without Loss of Information

Quantum network coding is used to solve the congestion problem in quantum communication,which will promote the transmission efficiency of quantum information and the total throughput of quantum network.We propose a novel controlled quantum network coding without information loss.The effective transmission of quantum states on the butterfly network requires the consent form a third-party controller Charlie.Firstly,two pairs of threeparticle non-maximum entangled states are pre-shared between senders and controller.By adding auxiliary particles and local operations,the senders can predict whether a certain quantum state can be successfully transmitted within the butterfly network based on the Z-{10>,|1>}basis.Secondly,when trans-mission fails upon prediction,the quantum state will not be lost,and it will sill be held by the sender.Subsequently,the controller Charlie re-prepares another three-particle non-maximum entangled state to start a new round.When the predicted transmission is successful,the quantum state can be transmitted successfully within the butterfly network.If the receiver wants to receive the effective quantum state,the quantum measurements from Charlie are needed.Thirdly,when the transmission fails,Charlie does not need to integrate the X-{1+>,1->}basis to measure its own particles,by which quantum resources are saved.Charlie not only controls the effective transmission of quantum states,but also the usage of classical and quantum channels.Finally,the implementation of the quantum circuits,as well as a flow chart and safety analysis of our scheme,is proposed.

An Overview of General Theory of Security

Cyber security lacks comprehensive theoretical guidance. General security theory, as a set of basic security theory concepts, is intended to guide cyber security and all the other security work. The general theory of security aims to unify the main branches of cyber security and establish a unified basic theory. This paper proposal an overview on the general theory of security, which is devoted to constructing a comprehensive model of network security. The hierarchical structure of the meridian-collateral tree is described. Shannon information theory is employed to build a cyberspace security model. Some central concepts of security, i.e., the attack and defense, are discussed and several general theorems on security are presented.

Probabilistic and Hierarchical Quantum Information Splitting Based on the Non-Maximally Entangled Cluster State

With the emergence of classical communication security problems,quantum communication has been studied more extensively.In this paper,a novel probabilistic hierarchical quantum information splitting protocol is designed by using a non-maximally entangled four-qubit cluster state.Firstly,the sender Alice splits and teleports an arbitrary one-qubit secret state invisibly to three remote agents Bob,Charlie,and David.One agent David is in high grade,the other two agents Bob and Charlie are in low grade.Secondly,the receiver in high grade needs the assistance of one agent in low grade,while the receiver in low grade needs the aid of all agents.While introducing an ancillary qubit,the receiver’s state can be inferred from the POVM measurement result of the ancillary qubit.Finally,with the help of other agents,the receiver can recover the secret state probabilistically by performing certain unitary operation on his own qubit.In addition,the security of the protocol under eavesdropping attacks is analyzed.In this proposed protocol,the agents need only single-qubit measurements to achieve probabilistic hierarchical quantum information splitting,which has appealing advantages in actual experiments.Such a probabilistic hierarchical quantum information splitting protocol hierarchical is expected to be more practical in multipartite quantum cryptography.

Security Service Technology for Mobile Networks

As mobile networks become high speed and attain an all-IP structure, more services are possible. This brings about many new security requirements that traditional security programs cannot handle. This paper analyzes security threats and the needs of 3G/4G mobile networks, and then proposes a novel protection scheme for them based on their whole structure. In this scheme, a trusted computing environment is constructed on the mobile terminal side by combining software validity verification with access control. At the security management center, security services such as validity verification and integrity check are provided to mobile terminals. In this way, terminals and the network as a whole are secured to a much greater extent. This paper also highlights problems to be addressed in future research and development.

Research on virtual node placement optimization strategy of cloud platform for information acquisition

A virtual node placement strategy based on service-aware is proposed for an information acquisition platform. The performance preferences and types of services in the information acquisition platform are analyzed as well as a comparison of the running time of services both in virtual node centralized and decentralized placing. All physical hosts are divided into different sub-clusters by using the analytic hierarchy process( AHP),in order to fit service of different performance preferences. In the sub-cluster,both load balance and quality of service are taken into account. Comparing with the heuristic algorithm,the experiment results show that the proposed placement strategy is running for a shorter time. And comparing with the virtual node placement strategy provided by OpenStack,the experiment results show that the proposed placement strategy can improve the execution speed of service in the information acquisition platform,and also can balance the load which improves resources utilization.

Physical Layer Security for Wireless and Quantum Communications

his special issue is dedicated to security problems in wireless and quan-turn communications. Papers for this issue were invited, and after peer review, eight were selected for publication. The first part of this issue comprises four papers on recent advances in physical layer security forwireless networks. The second Part comprises another four papers on quantum com- munications.

Adaptive Energy-Efficient Power Allocation for DAS with Imperfect Channel State Information and Antenna Selection

Considering that perfect channel state information(CSI) is difficult to obtain in practice,energy efficiency(EE) for distributed antenna systems(DAS) based on imperfect CSI and antennas selection is investigated in Rayleigh fading channel.A novel EE that is defined as the average transmission rate divided by the total consumed power is introduced.In accordance with this definition,an adaptive power allocation(PA) scheme for DAS is proposed to maximize the EE under the maximum transmit power constraint.The solution of PA in the constrained EE optimization does exist and is unique.A practical iterative algorithm with Newton method is presented to obtain the solution of PA.The proposed scheme includes the one under perfect CSI as a special case,and it only needs large scale and statistical information.As a result,the scheme has low overhead and good robustness.The theoretical EE is also derived for performance evaluation,and simulation result shows the validity of the theoretical analysis.Moreover,EE can be enhanced by decreasing the estimation error and/or path loss exponents.

A Secure Energy Internet Scheme for IoV Based on Post-Quantum Blockchain

With the increasing use of distributed electric vehicles(EV),energy management in the Internet of vehicles(IoV)has attracted more attention,especially demand response(DR)management to achieve efficient energy management in IoV.Therefore,it is a tendency to introduce distributed energy such as renewable energy into the existing supply system.For optimizing the energy internet(EI)for IoV,in this paper,we introduce blockchain into energy internet and propose a secure EI scheme for IoV based on post-quantum blockchain,which provides the new information services and an incentive cooperation mechanism for the current energy IoV system.Firstly,based on the principles of constructing a short lattice basis and preimage sampling,a lattice signature scheme is proposed and used in blockchain for authentication,which provides anti-quantum security.Secondly,we design the EI based on the post-quantum blockchain model.Lastly,based on this model,we design a secure EI scheme for IoV based on post-quantum blockchain.Through our analysis and experiment,this new scheme can increase the efficiency of energy utilization and enrich EI’s application in IoV.In particular,we further illustrate and analyze its performance.It is shown that EI based on post-quantum blockchain is more secure and efficient in information communications and energy trading.

Quantum-Enhanced Blockchain: A Secure and Practical Blockchain Scheme

The rapid advancement of quantum technology poses significant security risks to blockchain systems.However,quantum technology can also provide solutions for enhancing blockchain security.In this paper,we propose a quantum-enhanced blockchain scheme to achieve a high level of security against quantum computing attacks.We first discuss quantum computing attacks on classic blockchains,including attacks on hash functions,digital signatures,and consensus mechanisms.We then introduce quantum technologies,such as a quantum hash function(QHF),a quantum digital signature(QDS),and proof of authority(PoA)consensus mechanism,into our scheme to improve the security of the blockchain system.Our security analysis demonstrates that our scheme offers superior security against quantum and classic attacks.Finally,we compare our scheme with previous works,showing that our scheme has achieved a perfect balance in terms of practicality,reliability,scalability,and efficiency.Overall,this work contributes to the ongoing research on quantum blockchain in the quantum era.

Efficient semi-quantum secret sharing protocol using single particles

Semi-quantum secret sharing(SQSS)is a branch of quantum cryptography which only requires the dealer to have quantum capabilities,reducing the difficulty of protocol implementation.However,the efficiency of the SQSS protocol still needs to be further studied.In this paper,we propose a semi-quantum secret sharing protocol,whose efficiency can approach 100%as the length of message increases.The protocol is based on single particles to reduce the difficulty of resource preparation.Particle reordering,a simple but effective operation,is used in the protocol to improve efficiency and ensure security.Furthermore,our protocol can share specific secrets while most SQSS protocols could not.We also prove that the protocol is secure against common attacks.

Secure Blockchain-Enabled Internet of Vehicles Scheme with Privacy Protection

The car-hailing platform based on Internet of Vehicles(IoV)tech-nology greatly facilitates passengers’daily car-hailing,enabling drivers to obtain orders more efficiently and obtain more significant benefits.However,to match the driver closest to the passenger,it is often necessary to process the location information of the passenger and driver,which poses a considerable threat to privacy disclosure to the passenger and driver.Targeting these issues,in this paper,by combining blockchain and Paillier homomorphic encryption algorithm,we design a secure blockchain-enabled IoV scheme with privacy protection for online car-hailing.In this scheme,firstly,we propose an encryp-tion scheme based on the lattice.Thus,the location information of passengers and drivers is encrypted in this system.Secondly,by introducing Paillier homomorphic encryption algorithm,the location matching of passengers and drivers is carried out in the ciphertext state to protect their location privacy.At last,blockchain technology is used to record the transactions in online car-hailing,which can provide a security guarantee for passengers and drivers.And we further analyze the security and performance of this scheme.Compared with other schemes,the experimental results show that the proposed scheme can protect the user’s location privacy and have a better performance.

Variational quantum semi-supervised classifier based on label propagation

Label propagation is an essential semi-supervised learning method based on graphs,which has a broad spectrum of applications in pattern recognition and data mining.This paper proposes a quantum semi-supervised classifier based on label propagation.Considering the difficulty of graph construction,we develop a variational quantum label propagation(VQLP)method.In this method,a locally parameterized quantum circuit is created to reduce the parameters required in the optimization.Furthermore,we design a quantum semi-supervised binary classifier based on hybrid Bell and Z bases measurement,which has a shallower circuit depth and is more suitable for implementation on near-term quantum devices.We demonstrate the performance of the quantum semi-supervised classifier on the Iris data set,and the simulation results show that the quantum semi-supervised classifier has higher classification accuracy than the swap test classifier.This work opens a new path to quantum machine learning based on graphs.

MTBAC： A Mutual Trust Based Access Control Model in Cloud Computing

As a new computing mode,cloud computing can provide users with virtualized and scalable web services,which faced with serious security challenges,however.Access control is one of the most important measures to ensure the security of cloud computing.But applying traditional access control model into the Cloud directly could not solve the uncertainty and vulnerability caused by the open conditions of cloud computing.In cloud computing environment,only when the security and reliability of both interaction parties are ensured,data security can be effectively guaranteed during interactions between users and the Cloud.Therefore,building a mutual trust relationship between users and cloud platform is the key to implement new kinds of access control method in cloud computing environment.Combining with Trust Management(TM),a mutual trust based access control(MTBAC) model is proposed in this paper.MTBAC model take both user's behavior trust and cloud services node's credibility into consideration.Trust relationships between users and cloud service nodes are established by mutual trust mechanism.Security problems of access control are solved by implementing MTBAC model into cloud computing environment.Simulation experiments show that MTBAC model can guarantee the interaction between users and cloud service nodes.

Trust Management Mechanism for Internet of Things

Trust management has been proven to be a useful technology for providing security service and as a consequence has been used in many applications such as P2P, Grid, ad hoc network and so on. However, few researches about trust mechanism for Internet of Things （IoT） could be found in the literature, though we argue that considerable necessity is held for applying trust mechanism to IoT. In this paper, we establish a formal trust management control mechanism based on architecture modeling of IoT. We decompose the IoT into three layers, which are sensor layer, core layer and application layer, from aspects of network composition of loT. Each layer is controlled by trust management for special purpose： self-organized, affective routing and multi-service respectively. And the final decision-making is performed by service requester according to the collected trust information as well as requester＇ policy. Finally, we use a formal semantics-based and fuzzy set theory to realize all above trust mechanism, the result of which provides a general framework for the development of trust models of IoT.