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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： He, Shiming Zeng, Weini Xie, Kun Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China The 716th Research Institute China Shipbuilding Industry Corporation Lianyungang222061 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook New York United States

ISBN: (纸本)9783319271361

In smart grid, privacy implications to individuals and their family is an important issue, due to the fine-grained usage data collection. Wireless communications are considered by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, Network Coding introduces new challenge for privacy preserving due to the encoding of packet in forwarder nodes. We propose a distributed privacy preserving scheme for network coding in smart grid, which considers the converged flows character of smart grid and exploits a homomorphic encryption function to decrease the complex in forwarder node. The message content of packet is encrypted and the tag of packet is encrypted by homomorphic encryption function. Then the forwarder node linear random codes the encrypted message contents and directly processes the tags cryptotext based on the homomorphism feature. It offers message content confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme. © Springer International Publishing Switzerland 2015.

关键词： Smart power grids

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A note on weight distributions of irreducible cyclic codes

A note on weight distributions of irreducible cyclic codes

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2014 International Conference on Information and Communications Technologies, ICT 2014

作者： Tang, Chunming Qi, Yanfeng Xu, Maozhi Wang, Baocheng Yang, Yixian School of Mathematics and Information China West Normal University Sichuan Nanchong 637002 China LMAM School of Mathematical Sciences Peking University Beijing 100871 China Aisino Corporation Inc Beijing 100195 China College of Information Engineering North China University of Technology Beijing 100144 China Information Security Center Beijing University of Posts and Telecommunications Beijing 100876 China Research Center on fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781849198431

Usually, it is difficult to determine the weight distribution of an irreducible cyclic code. In this paper, we discuss the case that an irreducible cyclic code has the maximal number of distinct nonzero weights and give a necessary and sufficient condition. In this case, we also obtain a divisible property for the weight of a codeword. Further, we present a necessary and sufficient condition for an irreducible cyclic code with only one nonzero weight. Finally, we determine the weight distribution of an irreducible cyclic code for some cases.

关键词： Codes (symbols)

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research on the E-commerce's user experience evaluation model

Research on the E-commerce's user experience evaluation mode...

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2nd International Conference on Mechanical engineering, Industrial Electronics and Informatization, MEIEI 2013

作者： Liu, Xin Xiong Liu, Qing Yun Wang, Wei Huang, Cong Mei Li, Wen Si School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Automotive Data Center China Automotive Technology and Research Center Beijing 100176 China

ISBN: (纸本)9783037858905

Firstly, the current situations of E-commerce's user experience evaluation model were analyzed. And then, fuzzy comprehensive analyses were introduced. After that, an improved E-commerce's user experience evaluation model based on fuzzy comprehensive analysis was established. In improved model, user experience hierarchy model was created based on psychological-stratification, experts' fuzzy evaluations of evaluation factors were integrated into fuzzy matrix by using the theory of Triangular Fuzzy Numbers. Finally an example is given to show the rationality and the effectiveness of the method. © (2013) Trans Tech Publications, Switzerland.

关键词： Electronic commerce

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research on the Operational Characteristics of Diverging Area on Expressway Off-ramp based on Different Restricted Strategy of Lane

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Procedia - Social and Behavioral sciences 2013年 96卷 1156-1164页

作者： Jianguo Gong Xiucheng Guo Shuai Dai Li Duan Road Traffic Safety Research Center of the Ministry of Public Security 14th floor B Buidlingsthe center of Xinshijie No.3 DongCheng District Beijing 100062 China School of Transportation Southeast UniversityRoom 327 1th Buildings No.35 Jinxianghe Road Nanjing Jiangsu 210096 School of Civil Engineering and Mechanics Huazhong University of Science & Technology Room201 the West Building No.6 No.1037 Luoyu Road Wuhan 430074

In order to find the operational characteristics of diverging area on expressway off-ramp with Vehicle Type Restricted Strategy(VTRS) and Vehicle Type Unrestricted Strategy(VTUS) in different lane, this paper analyzed the distribution of vehicle type in the each lane, in use of the data which is investigated from diverging area on the two expressway off-ramp with different operational strategy of lane. Furthermore, the χ 2 test technology was used to do the hypothesis test on the headway distribution. The result shows that the shift-negative- exponential distribution can well reflect the headway distribution of deceleration lane, and the first-order or the second-order Erlang distribution can well reflect the headway distribution of mainline. Finally, the conclusion can provide an important theoretical basis for the freeway off-ramp planning, designing, and management.

关键词： Expressway Off-Ramp Diverging Area Operational Strategy of Lane Headway

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On the security of a certificateless signature scheme

On the security of a certificateless signature scheme

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2010 2nd International Conference on Signal Processing Systems, ICSPS 2010

作者： Miao, Songqin Zhang, Futai Zhang, Lei School of Computer Science and Technology Nanjing Normal University Nanjing China Jiangsu Engineering Research Center on Information Security and Privacy Protection Technology Nanjing China UNESCO in Data Privacy Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Av. Països Catalans 26 E-43007 Tarragona Catalonia Spain

ISBN: (纸本)9781424468911

Certificateless public key cryptography (CLPKC) eliminates certificate management in traditional public key infrastructure and solves the problem of the key escrow in identity-based cryptography. Certificateless signature is one of the most important primitives in CLPKC. Many certificateless signature (CLS) schemes have been proposed these years. For a CLS scheme to be secure, it should be resistant to the attacks of both Type I Adversary and Type II Adversary. In this paper, we give cryptanalysis to a recently proposed certificateless signature scheme. We show it is insecure against a Type II adversary who models a malicious-but-passive key generation center (KGC). An attack is described which reveals that a Type II adversary can successfully forge a certificateless signature of any signer upon obtaining two valid signatures of that signer. © 2010 IEEE.

关键词： Authentication

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Price naming on home appliance load controls in real-time pricing environment

Price naming on home appliance load controls in real-time pr...

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IEEE General Meeting Power& Energy Society

作者： S. Tiptipakorn W.-J. Lee C. Mao J. Lu ERCOT ISO Taylor TX USA Energy Systems Research Center (ESRC) University of Texas Arlington Arlington TX USA Department of Electrical Engineering Hubei Electric Power Security and High Efficiency Key Laboratory Huazhong University of Science and Technology Wuhan China

The EPAct 2005 expresses the Federal Government's commitment to provide supporting infrastructures for electricity demand response to all classes of customers. Most end-use residential consumers are not able to participate in such program under current price structure. They are billed monthly with a static constant rate regardless of fluctuating true costs of electricity in real-time. With the increased participation from residential customers, problems leading to electricity crises can be lessened. Our research introduces a load control strategy, applying the familiar “price naming” concept, as a supporting tool for the forthcoming developments of the residential consumer's demand response. Samples of hourly home appliance load profiles are simulated using the Market Clearing Price Energy (MCPE) of ERCOT as pseudo real-time prices. The resulting cost savings and their corresponding waiting times are discussed to exhibit the trade-offs between the twos. The results show that our proposed strategy is promising and simple enough to be applicable for end-use residential consumers.

关键词： Real time systems Load flow control Home appliances Electricity Aggregates Load management Pricing

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ESALP2: Efficient Signature Aggregation with Location Privacy Preservation in Wireless Body Area Networks

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ACM Transactions on Sensor Networks 1000年

作者： Arun Sekar Rajasekaran Azees Maria Basker Palaniswamy Ashok Kumar Das Mohammed J.F. Alenazi Department of Electronics and Communication Engineering SR University Hanamakonda India School of Computer Science and Engineering VIT-AP University Amaravati India Insight Centre for Data Analytics School of Computer Science and Information Technology University College Cork Cork Ireland Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad Hyderabad India Department of Computer Engineering College of Computer and Information Sciences CCIS) King Saud University Riyadh Saudi Arabia

For Wireless Body Area Networks (WBANs), the security of sensitive data of patients is of the utmost importance, particularly in healthcare environments. This study presents a novel methodology for improving the efficacy of signature aggregation in a scenario involving doctors and patients while mitigating concerns about location privacy. Though there have been prior proposals for signature aggregation schemes, the proposed approach seeks to optimize the aggregation process within the considered scenario, thereby improving performance and reducing computational and communication burden. In addition, the proposed scheme integrates a resilient mechanism that safeguards the doctor’s location privacy by utilizing the Chinese Remainder Theorem (CRT). Advanced cryptographic algorithms and location-anonymization techniques are employed in the proposed method to safeguard the confidentiality of the doctors’ location. The security of the proposed scheme is formally analyzed using the Burrows-Abadi-Needham (BAN) logic and formally verified using the automated software validation tool, known as the Scyther tool, and an informal analysis of various security attributes confirms the security robustness of the proposed scheme. The efficacy is evaluated in comparison to analogous works utilizing the Cygwin software. The performance evaluation shows that the proposed scheme has lower communication costs as compared to existing competing schemes. Moreover, the serving ratio in the proposed scheme is high even if the number of patients is low for doctors.

关键词： Wireless Body Area Networks (WBAN) Authentication Aggregate signature Location privacy security Scyther Smart healthcare.

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Correlation-aware Cross-modal Attention Network for Fashion Compatibility Modeling in UGC Systems

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Kai Cui Shenghao Liu Wei Feng Xianjun Deng Liangbin Gao Minmin Cheng Hongwei Lu Laurence T. Yang Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China China Nuclear Power Operation Technology Corporation Ltd. China

Empowered by the continuous integration of social multimedia and artificial intelligence, the application scenarios of information retrieval (IR) progressively tend to be diversified and personalized. Currently, User-Generated Content (UGC) systems have great potential to handle the interactions between large-scale users and massive media contents. As an emerging multimedia IR, Fashion Compatibility Modeling (FCM) aims to predict the matching degree of each given outfit and provide complementary item recommendation for user queries. Although existing studies attempt to explore the FCM task from a multimodal perspective with promising progress, they still fail to fully leverage the interactions between multimodal information or ignore the item-item contextual connectivities of intra-outfit. In this paper, a novel fashion compatibility modeling scheme is proposed based on Correlation-aware Cross-modal Attention Network. To better tackle these issues, our work mainly focuses on enhancing comprehensive multimodal representations of fashion items by integrating the cross-modal collaborative contents and uncovering the contextual correlations. Since the multimodal information of fashion items can deliver various semantic clues from multiple aspects, a modality-driven collaborative learning module is presented to explicitly model the interactions of modal consistency and complementarity via a co-attention mechanism. Considering the rich connections among numerous items in each outfit as contextual cues, a correlation-aware information aggregation module is further designed to adaptively capture significant intra-correlations of item-item for characterizing the content-aware outfit representations. Experiments conducted on two real-world fashion datasets demonstrate the superiority of our approach over state-of-the-art methods.

关键词： User-Generated Contents fashion intelligent analysis complementary compatibility modeling multimodal representation learning correlation-aware integration strategy

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AMSPM: Adaptive Model Selection and Partition Mechanism for Edge Intelligence-driven 5G Smart City with Dynamic Computing Resources

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ACM Transactions on Sensor Networks 1000年

作者： Xin Niu Xuejiao Cao Chen Yu Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

With the help of 5G network, edge intelligence (EI) can not only provide distributed, low-latency, and high-reliable intelligent services, but also enable intelligent maintenance and management of smart city. However, the constantly changing available computing resources of end devices and edge servers cannot continuously guarantee the performance of intelligent inference. In order to guarantee the sustainability of intelligent services in smart city, we propose the Adaptive Model Selection and Partition Mechanism (AMSPM) in 5G smart city where EI provides services, which mainly consists of Adaptive Model Selection (AMS) and Adaptive Model Partition (AMP). In AMSPM, the model selection and partition of deep neural network (DNN) are formulated as an optimization problem. Firstly, we propose a recursive-based algorithm named AMS based on the computing resources of edge devices to derive an appropriate DNN model that satisfies the latency demand of intelligent services. Then, we adaptively partition the selected DNN model according to the computing resources of edge devices. The experimental results demonstrate that, when compared with state-of-the-art model selection and partition mechanisms, AMSPM not only reduces latency but also enhances computing resource utilization.

关键词： Edge intelligence changing available computing resources adaptive model selection and partition smart city sustainable intelligent services

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Contrastive Learning based Speech Spoofing Detection for Multimedia security in Edge Intelligence

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Jiaqi Sun Xianjun Deng Shenghao liu Xiaoxuan Fan Yongling Huang Yuanyuan He Celimuge Wu Jong Hyuk Park Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China The University of Electro-Communications Japan Seoul National University of Science and Technology South Korea

Artificial intelligence (AI) empowered edge computing has given rise to a new paradigm and effectively facilitated the promotion and development of multimedia applications. The speech assistant is one of the significant services provided by multimedia applications, which aims to offer intelligent interactive experiences between humans and machines. However, malicious attackers may exploit spoofed speeches to deceive speech assistants, posing great challenges to the security of multimedia applications. The limited resources of multimedia terminal devices hinder their ability to effectively load speech spoofing detection models. Furthermore, processing and analyzing speech in the cloud can result in poor real-time performance and potential privacy risks. Existing speech spoofing detection methods rely heavily on annotated data and exhibit poor generalization capabilities for unseen spoofed speeches. To address these challenges, this paper first proposes the Coordinate Attention Network (CA2Net) that consists of coordinate attention blocks and Res2Net blocks. CA2Net can simultaneously extract temporal and spectral speech feature information and represent multi-scale speech features at a granularity level. Besides, a contrastive learning-based speech spoofing detection framework named GEMINI is proposed. GEMINI can be effectively deployed on edge nodes and autonomously learn speech features with strong generalization capabilities. GEMINI first performs data augmentation on speech signals and extracts conventional acoustic features to enhance the feature robustness. Subsequently, GEMINI utilizes the proposed CA2Net to further explore the discriminative speech features. Then, a tensor-based multi-attention comparison model is employed to maximize the consistency between speech contexts. GEMINI continuously updates CA2Net with contrastive learning, which enables CA2Net to effectively represent speech signals and accurately detect spoofed speeches. Extensive experiments on

关键词： Edge intelligence Multimedia applications Speech spoofing detection Contrastive learning Coordinate attention

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