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IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS)

作者： Ming Tan Zhen Wei School of Computer and Information Key Laboratory of Network and Intelligent Information Processing Hefei University of Technology Hefei China

ISBN: (纸本)9781424447374;9781424447541

To overcome the drawback that switched Ethernet does not guarantee the timely delivery of real-time messages in industrial communication, an improved FTT (flexible time-triggered communication) paradigm was proposed for hard real-time communications of periodic messages on switched Ethernet. In addition, an optimization condition for feasibility check of periodic messages was given. Particularly, we proposed an EDF-based algorithm to schedule periodic messages to be transmitted within their deadlines over COTS switched Ethernet running in the cut-through mode. Simulation results showed the advantages of the proposed real-time scheduling algorithm in terms of using the aggregated switch throughput.

关键词： Scheduling algorithm Communication industry Ethernet networks Communication switching Job shop scheduling Switches Protocols Processor scheduling Throughput Traffic control

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Improved differential fault attack on the AES-128

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Journal of Computational information Systems 2009年第1期5卷 223-228页

作者： Liu, Shuanggen Ni, Haiying Hu, Yupu Zhu, Hui College of Computer Information Engineering Jiangxi Normal University Nanchang 330022 China Key Laboratory of Computer Network and Information Security Xidian University Xi'an 710071 China

The differential fault attack is a kind of side channel attacks. This paper proposes a differential fault analysis on the AES key schedule and shows how an entire 128-bit AES key can be retrieved. In the workshop at FDTC 2007, it presented the DFA mechanism on the AES key schedule and proposed general attack rules. Using the FDTC 2007 proposed rules, it showed an efficient attack that can retrieve 80 bits of the 128-bit key. Recently, we have found a new attack that can obtain an additional 8 bits compared with the previous attack. As a result, we present the most efficient attack for retrieving 88 bits of the 128-bit key using approximately two pairs of correct and faulty ciphertexts. Copyright © 2009 Binary information Press.

关键词： Side channel attack

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Boundary recognition in sensor networks by building relative contours

Boundary recognition in sensor networks by building relative...

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Conference on Local computer networks (LCN)

作者： Kai Li Yun Wang School of Computer Science & Engineering Key Laboratory of Computer Network and Information MOE South-East University Nanjing China

Wireless sensor networks (WSN) are affected by underlying environments in which sensors are deployed randomly. Inevitably, there are many irregular holes in a WSN because of the existence of obstacles or the death of some sensors. To detect these holes is of great importance to both WSN applications and networking functionalities. Holes are described by a set of sensor nodes on their boundaries. In this paper, we study the problem of identifying boundaries of holes in a WSN. By extracting hidden geometric features in the topology of a WSN, we are able to recognize sensor nodes on both inner and outer boundaries of holes. Methods proposed in this paper relies on neither the knowledge of localization nor the unit-disk communication model. We also propose a distributed algorithm to discover holes and identify nodes on boundaries. Simulation results show that our method works well for WSNs with many inner holes and irregular outer boundaries.

关键词： Wireless sensor networks Sensor phenomena and characterization computer networks network topology Distributed algorithms Floods Iterative algorithms computer science Feature extraction Neodymium

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A method for constructing simplified kernel model based on Kernel-MSE

A method for constructing simplified kernel model based on K...

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2009 2nd Asia-Pacific Conference on Computational Intelligence and Industrial Applications, PACIIA 2009

作者： Zhu, Qi Xu, Yong Cui, JinRong Chen, ChangFeng Wang, JingHua Wu, XiangQian Zhao, YingNan Key Laboratory of network Oriented Intelligent Computation Harbin Institute of Technology Shenzhen Graduate School ShenZhen China Department of Computer Science and Technology Harbin Institute of Technology Harbin China Department of Computer Science and Technology Nanjing University of Information Science and Technology NanJing China

ISBN: (纸本)9781424446070

In this paper, we derive an efficient nonlinear feature extraction method from naive Kernel Minimum Squared Error (KMSE) method. The most contribution of the derived method is its feature extraction procedure that is much more computationally efficient than naive KMSE. Differing from naive KMSE that exploits some linear combination of the total training patterns to express the discriminant vector in feature space, the derived method attempts to select out a small number of patterns (referred to as "significant nodes" in this paper) from the training set and exploits some linear combination of "significant nodes" to approximate to the discriminant vector in feature space. According to the following two principles, an algorithm for producing "significant nodes" is designed. The "significant node" set should well represent the whole training patterns, and each "significant node" should contribute much for the feature extraction result. Experimental results on several benchmark datasets illustrate our method can efficiently classify the real-world data with the high recognition accuracy. ©2009 IEEE.

关键词： Feature extraction

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The Short Share Secret Sharing Agreement with Matrix Factorization

The Short Share Secret Sharing Agreement with Matrix Factori...

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International Conference on information Engineering and computer Science (ICIECS)

作者： XiaoYuan Yang Zhen Liu Key Laboratory of computer Network & Information Security of Engineering Institute of the Armed Police Xi'an Shanxi China

ISBN: (纸本)9781424449934

To make up the limitation of traditional secret sharing schemes that the length of secret can not be extremely great, we use the theory of Jordan matrix factorization and combine with the formulary of Lagrange putting forward an algorithm of (r, n) threshold secret sharing with short share and high efficiency. The length of secret share that each participator needs to conserve has no relation with the length of the secret. So our scheme has a very high space, computation and communication efficiency. It has a very important application when the secret is a big privacy file, a big message transmitting in an insecurity channel, a secret data base shared by several participant or magnanimity data in distributed storage.

关键词： Cryptography Switches Laboratories computer networks information security Lagrangian functions Application software Data privacy Partitioning algorithms Layout

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The Security Matrix Factorization Agreement with Two Parties

The Security Matrix Factorization Agreement with Two Parties

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International Conference on Computational Intelligence and Security

作者： XiaoYan Yang Zhen Liu Key Laboratory of computer Network & Information Security of Engineering Institute of the Armed Police Xi'an Shanxi China

In the confidential computing issues of scientific computing, the confidential computing of matrix factorization is still no fruit home and abroad. This paper using Data perturbation assumption and Oblivious Transfer 1 out of k protocol, successfully construct confidential computing protocols of matrix general factorization and QR factorization. On the model of semi-honest, it can meet the confidentiality. At the same time, the method of this protocol is also suitable for confidential computing of matrix other factorizations.

关键词： Protocols Scientific computing information security computer networks Equations Home computing Eigenvalues and eigenfunctions computer security Laboratories Data security

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Access model of web users based on multi-chains hidden Markov models

Access model of web users based on multi-chains hidden Marko...

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作者： Zheng, Kangfeng Yang, Yixian Wang, Xiujuan Guo, Shize Key Laboratory of Network and Information Attack and Defence Technology MOE Beijing University of Posts and Telecommunications Beijing China College of Computer Sciences Beijing University of Technology Beijing China No. 54 Research Institute of the General Staff PLA Beijing China

ISBN: (纸本)9780769540276

How to distinguish abnormal access from normal ones is the key problem in Distribution Denial of service(DDoS) attack detection. This research aims at finding out the major difference between the abnormal access and the normal ones in application layer. To this end , the paper conducts modeling on Web users' access behaviors based on hidden Markov model(HMM) with multiple chains and puts forward a method to identify abnormal access. Tests on simulation data indicate that this model can undo Web users access to a certain degree and discern the abnormal access well. © 2010 IEEE.

关键词： Hidden Markov models

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A static method for detection of information theft malware

A static method for detection of information theft malware

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2nd International Symposium on Electronic Commerce and Security, ISECS 2009

作者： Li, JiaJing Wei, Tao Zou, Wei Mao, Jian Key Laboratory of Network and Software Security Assurance Ministry of Education Peking University Beijing 100871 China Institute of Computer Science and Technology Peking University Beijing 100871 China Department of Electronic and Information Engineering BeiHang University Beijing 10083 China

ISBN: (纸本)9780769536439

Existing techniques based on behavior semantics for information theft malware detection have the main shortcomings of low path coverage and disability of finding hidden malicious behaviors. In this paper we propose a static method for the detection of information theft malware to overcome these shortcomings. It is particularly efficienct for inter-procedure taint analysis, and it is suitable for complicated malware detection, such as Trojan and Bot. Its static style makes it able to find hidden malicious behaviors. We also present an implementation of our method that works on x86 executables and a set of experimental studies validate its good efficiency and effectiveness. © 2009 IEEE.

关键词： Malware

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Efficient Mining of Strong Negative Association Rules in Multi-Database

Efficient Mining of Strong Negative Association Rules in Mul...

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International Conference on Computational Intelligence and Software Engineering (CiSE)

作者： Hong Li Xuegang Hu Key Laboratory of Network and Intelligent Information Processing Department of Computer Science and Tchnology Hefei University Hefei China School of Computer & Information Hefei University of technology Hefei China

Strong negative association rules can reveal irrelevances hidden between frequent itemsets. Existing research has made significant efforts in discovering both positive and negative association rules from single database. This paper presents an efficient method for mining strong negative association rules in multi-database. The method produces some strong negative relational patterns (a kind of infrequent itemsets) by pruning and scanning constructed multi-database frequent pattern tree, and extracts strong negative association rules according to the proposed correlation model. The experimental results show the effectiveness and efficiency of the proposed algorithm.

关键词： Data mining Association rules Itemsets Transaction databases Decision making Laboratories Intelligent networks information processing computer science Relational databases

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A novel mining Method of Global Negative Association Rules in Multi-Database

A novel mining Method of Global Negative Association Rules i...

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IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS)

作者： Hong Li Yijun Shen Xuegang Hu Key Laboratory of Network and Intelligent Information Processing Department of Computer Science and Technology Hefei University of Technology Hefei China School of Computer & Information Hefei University of technology Hefei China

ISBN: (纸本)9781424447374;9781424447541

Mining negative association rules in multi-database has attracted more and more attention. Most existing research focuses on unifying all negative rules discovered from different single databases into a single view. This paper presents a novel method for mining global negative association rules in multi-database. This method produces some infrequent itemsets of potential interest by scanning constructed multi-database frequent pattern tree, and extracts negative association rules of interest according to the proposed correlation model from multi-database. Experimental results show the effectiveness and efficiency of the proposed algorithm.

关键词： Data mining Association rules Itemsets Transaction databases Application software Laboratories Intelligent networks information processing computer science Tires

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