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Accurate classification of time series based on a new robust similarity measure

Journal of computational Information Systems 2013年第9期9卷 3521-3528页

作者： He, Xiaoxu Shao, Chenxi Xiong, Yan School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Anhui Province Key Laboratory of Software in Computing and Communication Hefei 230027 China

Among different time series data mining, time series classification is one of the most important aspects. How to design a suitable similarity measure of similarity is a burning issue for accurate time series classification. In this paper, we propose a new similarity measure based on feature exaction of the original time series. The new similarity measure is used in classification with the nearest neighbor rule. In order to provide a comprehensive comparison, we conducted three sets of experiments, testing effectiveness on different time series datasets from a wide variety of application domains. Experimental evaluations show that the proposed similarity measure can tolerate the most distortions than other three typical similarity;besides, the new classifier is not only superior to other conventional classifier, but also more excellent in 1nn classifier than other similarity measure. © 2013 by Binary Information Press.

关键词： Data mining

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Directed differential evolution based on directional derivative for numerical optimization problems

Directed differential evolution based on directional derivat...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Jun Zhang Wenjian Luo School of Computer Science and Technology University of Science and Technology Hefei Anhui China Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology Hefei Anhui China

Differential Evolution is one kind of Evolutionary Algorithms, which has been successfully applied to solve many optimization problems. In this paper, a directed differential mutation (DDM), which utilizes the directional derivative to decide a suitable search direction and a proper mutation step size, is proposed. It is merged into the classical DE to form a new algorithm, named directed differential evolution (DDE). The performance of the DDE is tested on 23 classical problems for numerical optimization. The experimental results demonstrate that the performance of the DDE outperforms the classical DE on most functions.

关键词： Optimization Vectors Equations Hybrid intelligent systems Algorithms Programming Maintenance engineering

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An Authentication Mechanism for IoT Devices Based on Traceable and Revocable Identity-Based Encryption 7th

An Authentication Mechanism for IoT Devices Based on Tra...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Xia, Fei Mao, Jiaming Shao, Zhipeng Xu, Liangjie Zhao, Ran Yang, Yunzhi State Grid Jiangsu Electric Power Co Ltd. Information and Telecommunication Branch Nanjing210024 China Institute of Information and Communication State Grid Key Laboratory of Information and Network Security Global Energy Interconnection Research Institute Nanjing Jiangsu210003 China Anhui Jiyuan Software Co. Ltd SGITG Hefei Anhui230088 China

ISBN: (纸本)9783030786113

To solve low computing efficiency and high computational energy consumption in the traditional Public-key Infrastructure cryptosystem in the authentication of IoT devices, an authentication scheme for IoT devices based on the Identity-based Encryption is proposed in this paper, which is realized by introducing traceable and revocable mechanisms. The effective management of the secret key of the suspicious devices by the authentication center and the reasonable accountability of the dishonest private key generator (PKG) are realized. Finally, through the security proof, it is verified that the Identity-based Encryption designed in this paper can meet the security of the Chosen Ciphertext Attack (CCA), indicating that the scheme has high practicability and security. © 2021, Springer Nature Switzerland AG.

关键词： Authentication

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Representative Template Set Generation Method for Pedestrian Detection

Representative Template Set Generation Method for Pedestrian...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Pei Wu Xian-Bin Cao Yan-Wu Xu Hong Qiao Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China Institute of Automation Chinese Academy and Sciences Beijing China

Template matching is an effective approach for pedestrian detection. In order to achieve real-time and accurate detection, how to obtain a suitable representative template set is still an open problem due to the large variety of pedestrian shape. This paper introduced a representative template generation method for a template matching based pedestrian detection system (PDS). Based on nonlinear manifold learning and clustering, the new approach can generate a suitable representative template subset from a large amount of original templates. First, an improved nonlinear dimensionality reduction method was proposed to map original templates to feature vectors (points) in the low-dimensional embedding space; second, representative points were generated in the embedding space by clustering; at the end, corresponding representative template set were synthesized by mapping inversely the newly generated points from the embedding space to the visual input *** experimental results showed that the template generation method speeds up detection procedure without considerable loss of performance.

关键词： Shape Laboratories communication system software Vehicle detection Fuzzy systems Automation Performance loss Vehicles Object detection Pattern matching

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PN-HASH: An Immune-Inspired Scheme for Data Integrity Check

PN-HASH: An Immune-Inspired Scheme for Data Integrity Check

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International Workshop on Advanced computational Intelligence (IWACI)

作者： Junteng Wang Wenjian Luo Yamin Hu Hao Jiang Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (数字)9781728142487

ISBN: (纸本)9781728142494

Cryptographic hash functions play significant roles in information security applications, including data integrity. Facing hash collision attacks, several prevalent cryptographic hash functions have been proved not safe enough. In this paper, we propose a simple scheme for data integrity check called PN-HASH (Positive hash and Negative hash). PN-HASH is inspired by the negative representation of information, which is a research branch in the field of immune computation. This scheme computes two hash values of the input message and its negative representation. The resulting hashes are called the positive hash and the negative hash, respectively. The proposed scheme is simple but can improve the resistance to hash collision attacks. Furthermore, for more flexibility and higher security, we propose three extensions of PN-HASH. Security and complexity analyses show that PN-HASH could improve the security of underlying cryptographic hash functions, with approximately twice cost of them. To give exact examples, we present PN-MD5, an implementation of PN-HASH based on MD5.

关键词： Cryptography Data integrity Databases Resistance Complexity theory Face

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DFTCP: A TCP-friendly delay-based high-speed TCP variant

DFTCP: A TCP-friendly delay-based high-speed TCP variant

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International Conference on Networking and Network Applications (NaNA)

作者： Xu Zhang Naijie Gu Junjie Su Kaixin Ren Anhui Province Key Laboratory of Computing and Communication Software Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei China

Due to the conservative additive increase and multiplicative decrease strategy, traditional TCP has a severe problem in utilizing bandwidth over high-speed long-distance networks. This paper proposes a delay-based congestion control algorithm, named DFTCP, for these networks. DFTCP calculates a reasonable equilibrium point for a network flow based on the estimation of the maximum size of available buffers along its network path, and adjusts the congestion window size according to the distance between the equilibrium point and the current network state. The experimental results demonstrate that, the new algorithm performs well in terms of bandwidth utilization, intra-protocol fairness and RTT fairness, and exhibits reasonable friendliness to standard TCP.

关键词： Delays Standards Packet loss Throughput Bandwidth Convergence

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The Learning-Bargaining Algorithm Used in Unlicensed Spectrum Pre-Allocation

The Learning-Bargaining Algorithm Used in Unlicensed Spectru...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Kun Han Jinlong Li Ping Zhu Xufa Wang Anhui Province Key Laboratory of Software in Computing and Communication Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China

In the wireless network of finite spectrum resource, some communication users probably do not allocate the spectrum so that their communication should be delayed. Thus it is necessary to arrange the communication time of the systems when we allocate the communication spectrum. We propose a games learning-bargaining algorithm to pre-allocate the communication resources in the frequency-time space. Through this distributed games learning, each user obtains its communication schedule, and the result of allocation is further improved by the bargaining process. The result of this algorithm makes the bandwidth utilization achieve a quite high level and arranges the global communication time as short as possible. Comparing with the centralized algorithm of NP-hard, this distributed algorithm has low time complexity. The experiments verify the convergence of the algorithm and present the superiorities of our results to other allocation algorithms.

关键词： Cognitive Radio Spectrum Allocation Game Theory Learning-Bargaining Time Complexity.

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High Capacity Reversible Data Hiding in Encrypted 3D Mesh Models Based on Multi-MSB Prediction

arXiv

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arXiv 2021年

作者： Lyu, Wan-Li Cheng, Lulu Yin, Zhaoxia Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University 230601 China School of Communication & Electronic Engineering East China Normal University Shanghai200241 China

The interaction of massive data in the network world poses an enormous threat to data security. Reversible data hiding in encrypted domain (RDH-ED) technology ensures the security of data storage. Extensive works of RDH-ED take digital images as the cover mediums. With the advancement of multimedia technology, three-dimensional (3D) models are widely used on the network. In recent years, 3D models have also been used by researchers as cover mediums for RDH-ED technology. However, it is still challenging to improve the embedding rate under the premise of ensuring reversibility. This paper proposes an RDH-ED method to improve the embedding rate significantly, and the 3D mesh model can be restored after data extraction. Firstly, the vertices of the 3D mesh models are classified into "embedded set" and "prediction set" based on odd-even property of indices. Based on the high correlation of the two sets, multiple most significant bit (multi-MSB) prediction is adopted to calculate room redundancy. Arithmetic coding compresses auxiliary information generated during the reserved room phase to further free up space. In addition, the correlation between two sets is used to recover vertices that were modified due to data hiding. Experimental results show the proposed method greatly improves the embedding rate compared with state-of-the-art methods and guarantees model recovery with high quality. Copyright © 2021, The Authors. All rights reserved.

关键词： Forecasting

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High Capacity Reversible Data Hiding for Encrypted 3D Mesh Models Based on Topology

arXiv

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arXiv 2022年

作者： Tang, Yun Cheng, Lulu Lyv, Wanli Yin, Zhaoxia Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University 230601 China School of Communication & Electronic Engineering East China Normal University Shanghai200241 China

Reversible data hiding in encrypted domain(RDH-ED) can not only protect the privacy of 3D mesh models and embed additional data, but also recover original models and extract additional data losslessly. However, due to the insufficient use of model topology, the existing methods have not achieved satisfactory results in terms of embedding capacity. To further improve the capacity, a RDH-ED method is proposed based on the topology of the 3D mesh models, which divides the vertices into two parts: embedding set and prediction set. And after integer mapping, the embedding ability of the embedding set is calculated by the prediction set. It is then passed to the data hider for embedding additional data. Finally, the additional data and the original models can be extracted and recovered respectively by the receiver with the correct keys. Experiments declare that compared with the existing methods, this method can obtain the highest embedding capacity. Copyright © 2022, The Authors. All rights reserved.

关键词： Embeddings

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High-Capacity Reversible Data Hiding in Encrypted 3d Mesh Models Based on Multi-Msb Prediction

SSRN

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SSRN 2022年

The interaction of massive data in the network world poses a enormous threat to data security. Reversible data hiding in encrypted domain (RDH-ED) technology ensures the security of data storage. With the advancement of multimedia technology, three-dimensional (3D) models are widely used on the network. Recently, 3D models have also been used by researchers as cover mediums for RDH-ED technology. However, it is still challenging to improve the embedding rate under the premise of ensuring reversibility. This paper proposes an RDH-ED method to improve the embedding rate significantly, and the 3D mesh model can be restored after data extraction. Firstly, the vertices of the 3D mesh models are classified into "embedded set" and prediction set" based on odd-even property of indices. Based on the high correlation of the two sets, multiple most significant bit (multi-MSB) prediction is adopted to calculate room redundancy. Arithmetic coding compresses auxiliary information generated during the reserved room phase to further free up space. In addition, the correlation between two sets is used to recover vertices that were modified due to data hiding. Experimental results show the proposed method greatly improves the embedding rate compared with state-of-the-art methods and guarantees model recovery with high quality. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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