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An improved differential fault analysis attack to AES using reduced searching space

An improved differential fault analysis attack to AES using ...

引用

5th International Symposium on Cyberspace Safety and Security, CSS 2013

作者： Cai, Zemin Wang, Yi Li, Renfa Embedded Systems and Networking Laboratory Hunan University China Hunan Provincial Key Laboratory of Network and Information Security Hunan University Changsha China

ISBN: (纸本)9783319035833

Differential Power Analysis against AES proved to be effective, with use mask techniques, we can truncate the relevance and defense DPA attacks successfully. In this paper, we introduce a new mean called DFA (Differential Fault Attack), DFA has been shown successfully to attack AES algorithm with masking. We inject a fault to the intermediate results and other general form to obtain the ciphertext with faults, using the ciphertext we can recover the keys. Firstly, we construct the Sbox/InvSbox distribution tables to make the results sets space is less than 28 with two correct/fault ciphertexts pairs, even, in most cases, the set space are strict in 22. Secondly, we also demonstrated that the model of DFA we constructed can ignore the masking techniques and propose some methods to recover the keys with less time consuming and reduced searching space. Lastly, we make the module into an application and prove the module is effective. © Springer International Publishing Switzerland 2013.

关键词： Side channel attack

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A unified architecture for supporting operations of AES and ECC

A unified architecture for supporting operations of AES and ...

引用

2011 4th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2011

作者： Wang, Yi Li, Renfa Embedded Systems and Networking Laboratory Hunan Province Key Laboratory of Network and Information Security Hunan University Changsha 410082 China

ISBN: (纸本)9780769545752

In the recent years, embedded systems began to be used in sensitive applications such as personal digital assistants and smart cards. Due to very strict cost and power constrains, the support for cryptography provided by these devices is often limited to either public or private key primitives. This limitation is much more evident in devices where the cryptographic algorithms are implemented using hardware resources. In this paper, we propose an extension of a public-key cryptosystem to support also private-key, and we evaluate our architecture on FPGA platforms. In particular, we propose a new arithmetic unit in which the polynomial modular multiplication of ECC is extended to compute also the polynomial arithmetic operations over binary extended field of AES. We compare our design with an architecture obtained by instantiating state of the art implementation of AES and ECC and we evaluate the trade-offs. The experimental results show that our proposed architecture takes up less hardware resources. Nevertheless, the achieved performances are better compared to the ECC reference core, while the ones compared to AES only implementation are comparable with the state of the art.1 © 2011 IEEE.

关键词： Smart cards

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A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor Data and Periodic Sampling

A Rolling Bearing Fault Diagnosis Method Using Multi-Sensor ...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Zheng, Jianbo Yang, Chao Zheng, Fangrong Jiang, Bin College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China School of Computational Science and Electronics Hunan Institute of Engineering China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

In recent years, bearing fault diagnosis based on deep learning has gradually become the mainstream. However, the existing studies still have some defects, such as unreasonable sampling and incomplete utilization of bearing data, limiting the further improvement of the performance of the fault diagnosis model. This paper proposes a fault diagnosis method using multi-sensor data and periodic sampling to solve the problems above. First, the vibration data of different bearing positions are fused into multi-channel fusion data to improve the defect of insufficient data utilization. Second, based on the sampling length and sampling stride, periodic sampling is carried out for the fusion data to solve the problem of unreasonable sampling. Third, the traditional convolutional neural network is adjusted to extract more detailed fault features and obtain the best recognition effect. Finally, the experimental results verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Failure analysis

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A decomposition based evolutionary algorithm with angle penalty selection strategy for many-objective optimization 9th

A decomposition based evolutionary algorithm with angle pena...

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9th International Conference on Swarm Intelligence, ICSI 2018

作者： Li, Zhiyong Lin, Ke Nouioua, Mourad Jiang, Shilong Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha China PKU-HKUST Shenzhen-HongKong Institution Shenzhen China

ISBN: (纸本)9783319938141

Evolutionary algorithms (EAs) based on decomposition have shown to be promising in solving many-objective optimization problems (MaOPs). First, the population (or objective space) is divided into K subpopulations (or subregions) by a group of uniform distribution reference vectors. Later, subpopulations are optimized simultaneously. In this paper, we propose a new decomposition based evolutionary algorithm with angle penalty selection strategy for MaOPs (MOEA-APS). In the environmental selection process, in order to prevent the solutions located around the boundary of the subregion from being simultaneously selected into the next generation which will affect negatively on the performance of the algorithm, a new angle similarity measure (AS) is calculated and used to punish the dense solutions. More precisely, after selecting a good solution x for a sub population, the solutions whose angle similarity with x exceeding η or pareto dominated by x will be directly punished. Moreover, The threshold η is not fixed, but decided by the distribution of the solutions around x. This mechanism allows to improve diversity of population. The experimental results on DTLZ benchmark test problems show that the results of the proposed algorithm are very competitive comparing with four other state-of-the-art EAs for MaOPs. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Evolutionary algorithms

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Neighbor Diversification-Based Collaborative Filtering for Improving Recommendation Lists

Neighbor Diversification-Based Collaborative Filtering for I...

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International Workshop on Intelligent Communication and Social networks

作者： Chao Yang Cong Cong Ai Renfa Li Key Laboratory for Embedded and Network Computing of Hunan University

ISBN: (纸本)9781479909735

Recommendation systems are popular information filtering tools that help people find what they want. Accuracy is the most widely used metric for evaluating recommendation systems. Recently, many research works have focused on new measurements beyond the accuracy of recommendation systems. In this paper, we propose a neighbor diversification collaborative filtering algorithm to improve the recommendation lists. By using Movielens dataset for empirical analysis, we investigated the influence of neighbor diversity to the recommendation accuracy, diversity, novelty and coverage. Intensive experimental results proved the efficiency of our proposed algorithm for improving recommendation lists.

关键词： Recommendation System Neighbor Diversification Diversity Novelty Coverage

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An Improved algorithm of parameters reconfiguration in cognitive radio networks using ant colony optimization

An Improved algorithm of parameters reconfiguration in cogni...

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2015 3rd International Conference on Manufacturing Engineering and Technology for Manufacturing Growth(METMG 2015)

作者： Shaoyuan Liu Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University

Recent years, cognitive radio techniques have becoming a promising solution to tackle the bottleneck of spectrum scarcity. As an essential characteristics for CRN, the cognitive parameter reconfiguration can automatically adjust the parameters to meet the user demands and adapt to the timevarying environment. However parameter reconfiguration and complex environment cognition are still challenging due to their need for high speed parallel computation and multi-objects optimization. In this aspect, ant colony optimization(ACO) technique, as an intelligent technology to solve the complex issues, is introduced to the reconfiguration process to achieve the assignment. The goal of this paper is to present a parameters reconfiguration scenario using ACO with a comprehensive fitness function for reconfiguration decision making with regard to the multiple and complex objectives. Finally, series of results have demonstrated the stability and validity of the ACO based reconfiguration algorithm in CRN.

关键词： ACO simulation An Improved algorithm of parameters reconfiguration in cognitive radio networks using ant colony optimization

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Multi-Users Cooperative Spectrum Sensing in Distributed Cognitive Radio networks with Energy Harvesting

Multi-Users Cooperative Spectrum Sensing in Distributed Cogn...

引用

2nd International Conference on Simulation and Modeling Methodologies,Technologies and Applications(SMTA 2015)

作者： H.Wang F.Z.Zeng Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University

In this paper we propose an improved sensing scheme in cognitive radio networks, which allows the secondary users to utilize the spectrum of primary users when these resources are not being used currently. We first apply multi-user cooperative spectrum sensing in cognitive radio networks to improve both energy efficiency and spectrum utility. Secondly, we investigate the energy harvesting communication model. Finally, we analysis the probability of the proposed spectrum sensing scheme, and obtain an optimal solution under the scenarios of non-energy harvesting scheme and energy harvesting scheme respectively. The simulation results demonstrate the high performance of our proposed scheme.

关键词： Multi-Users Cooperative Spectrum Sensing in Distributed Cognitive Radio networks with Energy Harvesting Radio

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Cyber-Physical Systems Design in An Uncertain Environment with Time Uncertainty Concern 29

Cyber-Physical Systems Design in An Uncertain Environment wi...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Chen, Si Huang, Lida Xiao, Xiongren Liu, Yan Xie, Guoqi Li, Renfa Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Changsha China Research Institute of Hunan University in Chongqing Center for Convergence of Automobile and Cyberspace Chongqing China

ISBN: (纸本)9798350330717

Multiple processors system on chip (MPSoC) has been the trend in cyber-physical systems (CPSs), and reasonable partitioning for MPSoC resources is a critical step in CPSs design. The uncertainties of environment and time are both important factors that need to be considered in the design, but none of the previous work pays attention to two uncertainties at the same time. The state-of-the-art work presented a detailed process of applying uncertain programming to solve the partitioning problem, which provides a solution for designing in an uncertain environment. However, this work only considers the bipartition scenario which cannot be directly applied to MPSoC, and it does not focus specifically on time uncertainty. In this paper, we propose a method for modeling the MPSoC partitioning problem in an uncertain environment, with the time uncertainty concern. We present the uncertain model that can be applied to the multiple optional resources scenario. We build the optimization model with the objective of minimizing time, analyze two different cases of minimizing the uncertain time, and finally prove a unified deterministic model to solve. We come up with three algorithms, including the heuristic algorithm, the genetic algorithm, and the exact algorithm, and experiments show that the heuristic algorithm and the genetic algorithm can obtain good approximate solutions compared with the exact algorithm. © 2023 IEEE.

关键词： Cyber-physical systems (CPSs) design multiple processors system on chip (MPSoC) partitioning time uncertainty uncertain environment

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ACWB: Access-characteristic write buffer management scheme for flash memory 21

ACWB: Access-characteristic write buffer management scheme f...

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21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Zhu, Lei Liu, Yan Zhang, Zaimei Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha Hunan410082 China School of Economics and Management Changsha University of Science and Technology Changsha Hunan410076 China

ISBN: (纸本)9781728120584

Compared with traditional hard disk drives (HDD), solid state drives (SDD) have distinct characteristics, such as efficient continuous access and random reading capability. Using of SSD is greatly limited due to the out-of-place update and endurance problem. Many flash-aware buffer schemes have been proposed to reduce write and erase operations. However, a good buffer management scheme should reduce the effects of random writes and suit access patterns. In this paper, we propose an access characteristic write buffer management scheme (ACWB) on flash memory that integrates write buffer and cost regulation based on access characteristic. Experimental results show that ACWB increases the response time by 35%, reduces erase times by 25%, and improves the hit ratio by 27% on the average compared with current flash-aware write buffer schemes. © 2019 IEEE.

关键词： Flash memory

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Adaptive Compressed Classification for Energy Efficient Activity Recognition in Wireless Body Sensor networks

Adaptive Compressed Classification for Energy Efficient Acti...

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International Conference on Big Data computing and Communications (BIGCOM)

作者： Ling Xiao Yu Meng Kai Wu Key Laboratory for Embedded and Network Computing of Hunan Province China

Energy efficiency for activity recognition is a challenging task in the long-term health monitoring applications. To save the energy in wireless body sensor networks, the adaptive compressed classification framework for activity recognition is proposed. The proposed mechanism estimates the minimum activity-specific compression ratio subject to given recognition accuracy and adaptively adjusts the number of samples taken by sensor nodes based on the feedback from the result of activity recognition. A brute force algorithm is utilized to quickly find the optimal trade-off the power consumption and classification performance. With experiments on real-world activity datasets, we demonstrate 90.5% recognition accuracy with energy consumption reduced 28%.

关键词： Activity recognition Energy consumption Optimized production technology Wireless communication Base stations Body sensor networks

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