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SvdNPD: a negative data publication method based on the sensitive value distribution

SvdNPD: a negative data publication method based on the sens...

引用

International Workshop on Artificial Immune Systems (AIS)

作者： Linli Wu Wenjian Luo Dongdong Zhao University of Science and Technology of China Hefei Anhui CN Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

Existing data publication methods retain the relationship between the quasi-identifier attributes and sensitive attributes of published data. We call them "positive data publication". However, it will lead to potential risk that attackers could deduce the privacy of the corresponding individuals from the published data. Recently, by combining the negative representation with k-anonymity and l-diversity, (k, m)- anonNPD and (l, m)-divNPD algorithms have been proposed, which improve the degree of privacy because the sensitive value of each individual is transformed into a negative value randomly. However, to reduce the average error of the reconstructed distribution, the data published by (k, m)-anonNPD and (l, m)-divNPD are often much larger than the original data. In this paper, we take the Sensitive Value Distribution into consideration, and propose a novel Negative Data Publication approach (i.e. SvdNPD), which is based on l-diversity. According to the sensitive value distribution, the negative selection probability of the sensitive attribute in each record can be calculated. Then the data could be published by transforming the sensitive value to a negative one with this probability. Experimental results show that the effective usage of the individual sensitive value distribution could enhance the utility of published data. Meanwhile, compared with (l, 1)-divNPD, SvdNPD just sacrifices a tiny privacy degree which is acceptable.

关键词： Data privacy Privacy Diseases Aggregates Databases Lungs Organizations

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General Sparse Normalization and Proportionate ASE Algorithms 5

General Sparse Normalization and Proportionate ASE Algorithm...

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5th IEEE International Conference on Electronic Information and communication Technology, ICEICT 2022

作者： Hadi, Abdul Peng, Yan Qadir, Abdul Li, Yingsong Khan, Khushal College of Information and Communication Engineering Harbin Engineering University Harbin China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn230088 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China College of Intelligent System and Control Science Engineering Harbin Engineering University China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

Andrew's Sine Estimator (ASE) has recently been used to invent adaptive filtering, which can combat more kind of noises than conventional estimators. Inspired by the LMS and its sparse forms, normalization and proportionate ASE algorithms with Lawson constraints are constructed with the respective given names of Lawson normalization ASE (LNASE) and Lawson proportionate NASE (LPNASE). Simulations are performed to analyze the performance of these algorithms under impulsive noise. © 2022 IEEE.

关键词： Impulse noise

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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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Sparse learning for face recognition with social context

Sparse learning for face recognition with social context

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Gui, Jie Mi, Jian-Xun Lei, Ying-Ke Wang, Hong-Qiang State Key Laboratory of Software Engineering Wuhan University 430072 China Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui China State Key Laboratory for Novel Software Technology Nanjing University China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen Guangdong Province China Electronic Engineering Institute Hefei Anhui 230037 China

ISBN: (纸本)9783642420566

Face recognition in uncontrolled environments, such as large pose variations, and extreme ambient illumination and expressions is a challenging task for traditional face recognition methods. Some recent works show that context information such as clothes and social relationships is very important for solving the problem. Furthermore, sparse representation-based method is very robust for face occlusion and pixel contamination. In this paper, the authors propose a sparse learning framework for face recognition with social context. First, sparse representation based dimensionality reduction method is used to find the low dimension representation of the face images. Second, sparse representation based classification is utilized to classify test face images as known label and unknown label. Third, for test images classified as unknown label, social context descriptor is constructed according to co-existence information. Finally, based on social context descriptor and the low dimension representation of the test images classified as unknown label, sparse representation based clustering is adopted to perform face recognition. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Face recognition

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Investigation on ULA Fitting Promoting Low Coupling Sparse Arrays

Investigation on ULA Fitting Promoting Low Coupling Sparse A...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Yao, Yichang Shi, Wanlu Li, Yingsong Huang, Zhixiang Yang, Guohui Zhang, Kuang Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn230088 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150086 China

ISBN: (纸本)9781665452366

A low coupling sparse array (LCSA) is presented, analyzed and discussed on the basis of the recent proposed uniform linear array (ULA) fitting scheme with close-expressions, and its performance with different uniform subarrays in the basic layer is investigated via parameter estimation like direction-of-arrival(DOA). The results gives a superior performance for the presented LCSA. © 2022 IEEE.

关键词： Low mutual coupling sparse array uniform linear array fitting

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An Energy-Aware Coverage Based Node Scheduling Scheme for Wireless Sensor Networks

An Energy-Aware Coverage Based Node Scheduling Scheme for Wi...

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The 9th International Conference for Young Computer Scientists(第九届国际青年计算机大会)

作者： Jinxia Liu Naijie Gu Songsong He Dept. of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China Anhui Province Key Laboratory of Computing and Communication Software Hefei Anhui 230027 China

A fundamental issue in wireless sensor network is to extend network lifetime while maintaining network coverage and connectivity. Protection for sensors themselves is another important concern. An Energyaware Coverage based Node Scheduling scheme (ECNS) is proposed to provide protection for sensors and guarantees network connectivity and desired coverage level. ECNS enables each node to decide whether it is eligible to turn off to conserve energy through local information exchange with its neighbors. Simulation results show that ECNS improves network performance with respect to energy conservation, load balance and network lifetime.

关键词： Sensor network coverage network connectivity lifetime node scheduling scheme.

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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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Infrared Facial Expression Recognition Using Wavelet Transform

Infrared Facial Expression Recognition Using Wavelet Transfo...

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International Symposium on Computer Science and Computational Technology, ISCSCT

作者： Shangfei Wang Siliang Lv Xufa Wang Department of Computer Science and Technology Key Laboratory of Software Computing and Communication Anhui University of Science and Technology Hefei Anhui China

Since infrared images reflect the temperature-field distributing of vein¿s embranchment of the face, expression recognition from them should focus on changes of thermal distribution on facial muscles and blood vessels, which caused by mood variety. These thermal changes can be regarded as texture features of images. Wavelet transform is a good tool to analyze multi-scale, multi- direction changes of texture. Therefore, this paper presented a facial expression recognition method from thermal images using wavelet transform. Firstly, the status quo of the researches on infrared facial expression recognitions was briefly surveyed and analyzed. Secondly, wavelet transforms were used to extract image features. Thirdly, the ¿Euclidian Distance Maximizing Method¿ we proposed was adopted to select features. Then principal component analysis was employed to reduce feature dimension and NN was used as a classifier. Finally, experiments on medium-wave thermal facial expressions database of Equinox evaluated the effectiveness of our approach.

关键词： Face recognition Wavelet transforms Image recognition Infrared imaging Emotion recognition Facial muscles Blood vessels Biomedical imaging Mood Wavelet analysis

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