A New Energy-Efficient and Reliable Protocol for Stochastic WSNs Based on Back-Pressure and Entropy of Residual Energy

In this paper, a new energy-efficient and reliable routing protocol is introduced for WSNs including a stochastic traffic generation model and a wakeup/sleep mechanism. Our objective is to improve the longevity of the WSNs by energy balancing but providing reliable packet transfer to the Base Station at the same time. The proposed protocol is based on the principle of the back-pressure method and besides the difference of backlogs, in order to optimize energy consumption, we use a cost function related to an entropy like function defined over the residual energies of the nodes. In the case of two-hop routing the optimal relay node is selected as the one which has maximum backlog difference and keeps the distribution of residual energy as close to uniform as possible where the uniformity is measured by the change of the entropy of the residual energy of the nodes. The protocol assumes Rayleigh fading model. Simulation results show that the proposed algorithm significantly improves the performance of traditional back-pressure protocol with respect to energy efficiency, E2E delay and throughput, respectively.

Quantile Version of Mathai-Haubold Entropy of Order Statistics

Many researchers measure the uncertainty of a random variable using quantile-based entropy techniques.These techniques are useful in engineering applications and have some exceptional characteristics than their distribution function method.Considering order statistics,the key focus of this article is to propose new quantile-based Mathai-Haubold entropy and investigate its characteristics.The divergence measure of theMathai-Haubold is also considered and some of its properties are established.Further,based on order statistics,we propose the residual entropy of the quantile-based Mathai-Haubold and some of its property results are proved.The performance of the proposed quantile-based Mathai-Haubold entropy is investigated by simulation studies.Finally,a real data application is used to compare our proposed quantile-based entropy to the existing quantile entropies.The results reveal the outperformance of our proposed entropy to the other entropies.

Temperature-Triggered Hardware Trojan Based Algebraic Fault Analysis of SKINNY-64-64 Lightweight Block Cipher

SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length,and it is mainly used on the Internet of Things(IoT).Currently,faults can be injected into cryptographic devices by attackers in a variety of ways,but it is still difficult to achieve a precisely located fault attacks at a low cost,whereas a Hardware Trojan(HT)can realize this.Temperature,as a physical quantity incidental to the operation of a cryptographic device,is easily overlooked.In this paper,a temperature-triggered HT(THT)is designed,which,when activated,causes a specific bit of the intermediate state of the SKINNY-64-64 to be flipped.Further,in this paper,a THT-based algebraic fault analysis(THT-AFA)method is proposed.To demonstrate the effectiveness of the method,experiments on algebraic fault analysis(AFA)and THT-AFA have been carried out on SKINNY-64-64.In the THT-AFA for SKINNY-64-64,it is only required to activate the THT 3 times to obtain the master key with a 100%success rate,and the average time for the attack is 64.57 s.However,when performing AFA on this cipher,we provide a relation-ship between the number of different faults and the residual entropy of the key.In comparison,our proposed THT-AFA method has better performance in terms of attack efficiency.To the best of our knowledge,this is the first HT attack on SKINNY-64-64.

On Renyi entropies of order statistics

In this paper we consider a generalize dynamic entropy measure and prove that this mea- sure characterizes the distribution function uniquely. Also we propose cumulative resi- dual R^nyi entropy of order statistics and prove that it also determines the distribution function uniquely. Applications of entropy concepts to DNA sequence analysis, the ulti- mate support for the biological systems, have been widely explored by researchers. The entropy measures discussed here can be applied for analysis of ordered DNA sequences.