Preserving Data Secrecy and Integrity for Cloud Storage Using Smart Contracts and Cryptographic Primitives

Cloud computing has emerged as a viable alternative to traditional computing infrastructures,offering various benefits.However,the adoption of cloud storage poses significant risks to data secrecy and integrity.This article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology,smart contracts,and cryptographic primitives.The proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced data.To preserve data secrecy,symmetric encryption systems are employed to encrypt user data before outsourcing it.An extensive performance analysis is conducted to illustrate the efficiency of the proposed mechanism.Additionally,a rigorous assessment is conducted to ensure that the developed smart contract is free from vulnerabilities and to measure its associated running costs.The security analysis of the proposed system confirms that our approach can securely maintain the confidentiality and integrity of cloud storage,even in the presence of malicious entities.The proposed mechanism contributes to enhancing data security in cloud computing environments and can be used as a foundation for developing more secure cloud storage systems.

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

Improved IChOA-Based Reinforcement Learning for Secrecy Rate Optimization in Smart Grid Communications

In the evolving landscape of the smart grid(SG),the integration of non-organic multiple access(NOMA)technology has emerged as a pivotal strategy for enhancing spectral efficiency and energy management.However,the open nature of wireless channels in SG raises significant concerns regarding the confidentiality of critical control messages,especially when broadcasted from a neighborhood gateway(NG)to smart meters(SMs).This paper introduces a novel approach based on reinforcement learning(RL)to fortify the performance of secrecy.Motivated by the need for efficient and effective training of the fully connected layers in the RL network,we employ an improved chimp optimization algorithm(IChOA)to update the parameters of the RL.By integrating the IChOA into the training process,the RL agent is expected to learn more robust policies faster and with better convergence properties compared to standard optimization algorithms.This can lead to improved performance in complex SG environments,where the agent must make decisions that enhance the security and efficiency of the network.We compared the performance of our proposed method(IChOA-RL)with several state-of-the-art machine learning(ML)algorithms,including recurrent neural network(RNN),long short-term memory(LSTM),K-nearest neighbors(KNN),support vector machine(SVM),improved crow search algorithm(I-CSA),and grey wolf optimizer(GWO).Extensive simulations demonstrate the efficacy of our approach compared to the related works,showcasing significant improvements in secrecy capacity rates under various network conditions.The proposed IChOA-RL exhibits superior performance compared to other algorithms in various aspects,including the scalability of the NOMA communication system,accuracy,coefficient of determination(R2),root mean square error(RMSE),and convergence trend.For our dataset,the IChOA-RL architecture achieved coefficient of determination of 95.77%and accuracy of 97.41%in validation dataset.This was accompanied by the lowest RMSE(0.95),indicating very precise predictions with minimal error.

Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

Leveraging UAV-assisted communications to improve secrecy for URLLC in 6G systems

Unmanned Aerial Vehicles(UAVs)will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication(URLLC)in futuristic Sixth-Generation(6G)networks.However,several security vulnerabilities and attacks have plagued previous generations of communication systems;thus,physical layer security,especially against eavesdroppers,is vital,especially for upcoming 6G networks.In this regard,UAVs have appeared as a winning candidate to mitigate security risks.In this paper,we leverage UAVs to propose two methods.The first method utilizes a UAV as Decode-and-Forward(DF)relay,whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver devices.Moreover,we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception,i.e.increasing secrecy rate,and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF relay.Additionally,simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height,blocklength,decoding error probability and transmitter-receiver separation distance.Lastly,we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

Secrecy Efficiency Maximization in Intelligent Reflective Surfaces Assisted UAV Communications

This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface(IRS)assisted unmanned aerial vehicle(UAV)communication.With the popularization of UAV technology,more and more communication scenarios need UAV support.We consider using IRS to improve the secrecy efficiency.Specifically,IRS and UAV trajectories work together to counter potential eavesdroppers,while balancing the secrecy rate and energy consumption.The original problem is difficult to solve due to the coupling of optimization variables.We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem,and then prove the equivalence between relaxation problem and the original problem.Then an iterative algorithm is proposed by applying the block coordinate descent(BCD)method and the inner approximationmethod.The simulation results show that the proposed algorithm converges fast and is superior to the existing schemes.In addition,in order to improve the robustness of the algorithm,we also pay attention to the case of obtaining imperfect channel state information(CSI).

Secrecy Outage Probability for Two-Way Integrated Satellite Unmanned Aerial Vehicle Relay Networks with Hardware Impairments

In this paper,we investigate the secrecy outage performance for the two-way integrated satellite unmanned aerial vehicle relay networks with hardware impairments.Particularly,the closed-form expression for the secrecy outage probability is obtained.Moreover,to get more information on the secrecy outage probability in a high signalto-noise regime,the asymptotic analysis along with the secrecy diversity order and secrecy coding gain for the secrecy outage probability are also further obtained,which presents a fast method to evaluate the impact of system parameters and hardware impairments on the considered network.Finally,Monte Carlo simulation results are provided to show the efficiency of the theoretical analysis.

Secrecy Capacity Maximization for a UAV-Assisted MEC System

Unmanned aerial vehicle(UAV)communication has attracted wide attentions in the mobile edge computing(MEC)system owing to its high-flexibility and simple operation auxiliary communication mode.Users can offload computing tasks to UAVs,which serves as edge nodes.Meanwhile,UAVs forward the tasks onto a cloud center or base station for processing,thereby shortening the implementation time of tasks.Nevertheless,the offloading links of an UAV-assisted MEC system adopt a radio broadcasting mode.Several eavesdroppers might be present in the environment to eavesdrop the data sent by users and UAVs,thereby causing significant effects on the secrecy performance.An optimized iterative algorithm is proposed in this paper to realize the maximum secrecy capacity of the MEC system and further improve the secrecy performance of an UAV-assisted MEC system and assure secrecy transmit.By doing so,the secrecy transmit problems of the two-staged offloading model of the UAV-assisted MEC system are solved.The maximum secrecy capacity of the system is obtained through joint optimization of the UAV positions,transmit power of the UAV,task offloading ratio,and allocation of offloading users considering the limited time and energy of an UAV.Simulation results demonstrate that the proposed iterative algorithm can effectively improve the secrecy capacity of the system.

Secrecy Performance of Untrusted Relay’s Cooperation under Fading Channels

The secrecy performance of cooperation with an untrusted relay under a quasi-static fading channel is analyzed in this paper. An achievable secrecy rate is provided and the influence of selfish behavior of untrusted relay is analyzed. Furthermore, the secrecy performance of the scheme is discussed and compared with that of the case where the relay is just an eavesdropper. Simulation results show that the untrusted relay's cooperation in the fading case reduces the outage probability from 1/2 to 1/3 and achieves a higher outage secrecy capacity.

Secrecy Rate Analysis for Reconfigurable Intelligent Surface-Assisted MIMO Communications with Statistical CSI

In this paper,a reconfigurable intelligent surface(RIS)-assisted MIMO wireless secure communication system is considered,in which a base station(BS)equipped with multiple antennas exploits statistical channel state information to communicate with a legitimate multi-antenna user,in the presence of an eavesdropper,also equipped with multiple antennas.We firstly obtain an analytical expression of the ergodic secrecy rate based on the results of largedimensional random matrix theory.Then,a jointly alternating optimization algorithm with the method of Taylor series expansion and the projected gradient ascent method is proposed to design the transmit covariance matrix at the BS,as well as the diagonal phaseshifting matrix to maximize the ergodic secrecy rate.Simulations are conducted to demonstrate the accuracy of the derived analytical expressions,as well as the superior performance of our proposed algorithm.

Improvements on robust email protocols with perfect forward secrecy

According to the security shortages of two robust practical email protocols with perfect forward secrecy, attacks on the two protocols are analyzed and corresponding improvements on the two protocols are proposed. First, by analyzing the two email protocols, the corresponding man-in-the-middle attacks are proposed, where the adversary forges the messages in the receiving phase to cheat the two communication participants and makes them share the wrong session keys with him. Consequently, the man-in-the-middle attacks can make the two protocols fail to provide perfect forward secrecy. Secondly, by adding corresponding signatures in the receiving phases of the two protocols, two corresponding improvements on the protocols are proposed to overcome the man-in-the-middle attacks on the two protocols and make them provide perfect forward secrecy. Moreover, the two improved protocols can retain all the merits of the former protocols.

On the Secrecy Rate of Limited Feedback Beamforming over Multiple-Input Single-Output Wiretap Channels

The secrecy rate of limited feedback beamforming is studied for a Multiple-Input Single-Output(MISO) wiretap channel with a multi-antenna eavesdropper.We first obtain the secrecy rate of limited feedback beamforming achieved at the legitimate receiver.We then derive a lower bound for the asymptotic secrecy rate in the large system limit.From this bound,we observe a threshold for the ratio of eavesdrop antennas to transmit antennas to obtain a positive secrecy rate.We further show that the secrecy rate loss due to limited feedback decays with the number of feedback bits per transmit antenna.

Guaranteeing Wireless Communication Secrecy via a WFRFT-Based Cooperative System

In this paper, a weighted fractional Fourier transform(WFRFT) based cooperative overlay system, aiming to guarantee physical layer(PHY) security, is proposed. The paper elaborates how WFRFT and physical layer properties of the wireless medium are collaborated to guarantee the secrecy of wireless transmissions. In the proposed system, WFRFT is first preform on the secret data, such that the transmitted signal is distorted and can only be neutralized by inverse-WFRFT with the same parameter. And then two streams of the transformed sequences that bearing different messages are cooperatively and simultaneously transmitted to two legitimate receivers via a beamforming-liked method, respectively. In general, both the rapid spatial decorrelation property and the inherent security features of WFRFT are leveraged, such that only the eavesdropper's is degraded, and hence, the wireless communication secrecy is reliably guaranteed. Numerical simulations are conducted to evaluate the performance of the proposed system in terms of the average bit error rate and the secrecy capacity.

A Forward Integrity and Itinerary Secrecy Protocol for Mobile Agents

The security problem of mobile agents is widely being discussed. The problem which protects mobile agents from malicious hosts is difficult to solve, because a host has access to the complete internal state of an agent. Forward integrity in mobile agents guarantees that offers contained in a mobile agent from previously visited host can not be modified by a malicious host. Itinerary secrecy can prevent mobile agent from being passively attack. This paper proposes a new forward integrity and itinerary secrecy protocol for mobile agent. The protocol can also resist collusion truncation attack.

An Anti-Eavesdrop Transmission Scheduling Scheme Based on Maximizing Secrecy Outage Probability in Ad Hoc Networks

In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their transmissions.We propose an optimal transmission scheduling scheme to defend against the eavesdropper,where a source node having the highest secrecy rate is scheduled to access the wireless medium for transmitting to its destination in an opportunistic manner.To be specific,the secrecy rate between a pair of the source and destination in the presence of an eavesdropper varies temporally due to the wireless fading effect.The proposed optimal transmission scheduling scheme opportunistically selects a source node with the highest secrecy rate to transmit its data for the sake of maximizing the security of the ad hoc network against eavesdropping attacks.For comparison purposes,we also consider the conventional round-robin scheduling as a benchmark,where multiple source nodes take turns in accessing their shared wireless medium for transmitting to their respective destinations.We derive closed-form secrecy outage probability expressions of both the round-robin scheduling and the proposed optimal scheduling schemes over Rayleigh fading environments.Numerical results show that the proposed transmission scheduling scheme outperforms the conventional round-robin method in terms of its secrecy outage probability.Additionally,upon increasing the number of source-destination pairs,the secrecy outage probability of the round-robin scheme keeps unchanged,whereas the secrecy outage performance of the proposed transmission scheduling significantly improves,showing the security benefits of exploiting transmission scheduling for protecting wireless ad hoc networks against eavesdropping.

Interference Coordination for Secrecy Enhancement in Random Wireless Networks

The co-channel interference modeling is vital for evaluating the secrecy performance in random wireless networks,where the legitimate nodes and eavesdroppers are randomly distributed.In this paper,a new interference model is proposed from the userdominant perspective.The model can provide a better analytical assessment of secrecy performance with interference coordination for the presence of eavesdroppers.The typical legitimate is assumed to be located at the origin,and chooses the closest base station(BS) as its serving BS.The field of interferers is obtained by excluding the desired BSs(including the serving BS and its cooperative BS(s)).In contract with the exiting interference model,it is assumed that desired BSs and interferers belong to the same Poisson Point Process(PPP),and eavesdroppers are distributed according to another independent PPP.Based on this model,the average secrecy transmission capacity is derived in simply analytical forms with interference coordination.Analysis and simulation results show that the secrecy performance can be significantly enhanced by exploiting interference coordination.Furthermore,the average secrecy transmission capacity increases with increasing number of cooperative BSs.

Secrecy-Enhancing Design for Two-Way Energy Harvesting Cooperative Networks with Full-Duplex Relay Jamming

To guarantee secure information transmission within two sources,a full-duplex(FD)relay jamming scheme for two-way energy harvesting(EH)cooperative networks is proposed,in which the relay can achieve simultaneous information reception and jamming transmission.The EH relay node scavenges energy from two source signals,and then,uses the harvested energy for information relaying and jamming transmission by the power splitting(PS)protocol.Considering multiple eavesdroppers,the nonconvex optimization for maximizing the smaller bidirectional secrecy rates is formulated by jointly optimizing the power allocation and PS factor.Furthermore,an iterative algorithm based on successive convex approximation and alternate search method is proposed to solve this non-convexity.Simulation results verify the proposed iterative algorithm and show that the proposed jamming scheme can achieve substantial performance gain than other conventional schemes.

Secrecy Outage Probability Analysis Based on Cognitive Decode-and-Forward Relaying

Wireless communications have to face to several different security issues in practice due to the nature of broadcast.The information theory is well known to provide efficient approaches to address security issues in wireless communications,which attracts much attention in both industry and academia in recent years.In this paper,inspired by information theory,we study the outage probability of the opportunistic relay selection based on cognitive decode-and-forward relaying with the secrecy consideration.Specifically,the closed-form expression of the outage probability is proposed.Moreover,the asymptotic performance evaluation on the basis of the analytical results is investigated.The simulation results show that the relay selection can reduce the outage probability in accordance with our theoretical analysis.

Enhancing secrecy rates in a wiretap channel

Reliable communication imposes an upper limit on the achievable rate,namely the Shannon capacity.Wyner's wiretap coding ensures a security constraint and reliability,but results in a decrease of achievable rate.To mitigate the loss in secrecy rate,we propose a coding scheme in which we use sufficiently old messages as key and prove that multiple messages are secure with respect to all the information possessed by the eavesdropper.We also show that we can achieve security in the strong sense.Next,we study a fading wiretap channel with full channel state information of the eavesdropper's channel and use our coding/decoding scheme to achieve a secrecy capacity close to the Shannon capacity of the main channel(in the ergodic sense).Finally,we study a case where the transmitter does not have instantaneous information of the channel state of the eavesdropper,but only its distribution.

Formal Verification of Secrecy in Group Key Protocols Using Event-B

Group key security protocols play an important role in today’s communication systems. Their verification, however, remains a great challenge because of the dynamic characteristics of group key construction and distribution protocols. Security properties that are well defined in normal two-party protocols have different meanings and different interpretations in group key distribution protocols, specifically, secrecy properties, such as group secrecy, forward secrecy, backward secrecy, and key independence. In this paper, we present a method to verify forward secrecy properties for group-oriented protocols. The method is based on a correct semantical link between group key protocols and event-B models and also uses the refinement process in the B method to model and verify group and forward secrecy. We use an event-B first-order theorem proving system to provide invariant checking for these secrecy properties. We illustrate our approach on the Tree based Group Diffie-Hellman protocol as case study.