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A novel attack to track users based on the behavior patterns

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第6期29卷

作者： Gu, Xiaodan Yang, Ming Shi, Congcong Ling, Zhen Luo, Junzhou Southeast Univ Sch Comp Sci & Engn Nanjing Jiangsu Peoples R China Global Energy Interconnect Res Inst Nanjing Jiangsu Peoples R China

Currently, people around the world daily use the Internet to access various services, such as e-mail and online shopping. However, the behavior-based tracking attacks have posed a considerable threat to users' privacy. Relying on characteristic patterns within the Internet activities, this attack can link a user's multiple sessions. In this paper, we investigate the behavior-based tracking attack and propose some countermeasures to mitigate the threat. We preprocess the raw traffic data and then extract features ranging from lower layer network packets to high-level application-related traffic. Specifically, we focus on four types of application-level traffic to infer users' habits, including HTTP, IM, e-mail, and P2P. In addition, we extract the web queries entered into shopping websites and classify them to infer users' preferences. Then, we construct the preference models and propose an improved method. For evaluation, we collect traffic in the real-world environment to construct a large-scale dataset. Five hundred and nine users are selected in terms of the user's active degree. When the term frequency-inverse document frequency transformation is used, the improved method can identify an average of 93.79% instances correctly. Our extensive empirical experiments demonstrate the effectiveness and efficiency of our approaches. Finally, we discuss and evaluate several countermeasures. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： behavior-based tracking privacy traffic analysis pattern recognition preference model

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Homotopic thinning in 2D and 3D cubical complexes based on critical kernels 19th

Homotopic thinning in 2D and 3D cubical complexes based on c...

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19th iapr international conference on Discrete Geometry for Computer Imagery, DGCI 2016

作者： Couprie, Michel Bertrand, Gilles Université Paris-Est LIGM Équipe A3SI ESIEE Paris France

We propose a symmetric thinning scheme for cubical or simplicial complexes of dimension 2 or 3. We show how to obtain, with a same generic thinning scheme, ultimate, curve or surface skeletons that are uniquely define... 详细信息

ISBN: (纸本)9783319323596

关键词： Artificial intelligence

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A novel attack to track users based on the behavior patterns

A novel attack to track users based on the behavior patterns

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3rd international conference on Advanced Cloud and Big Data (CBD)

关键词： behavior-based tracking privacy traffic analysis pattern recognition preference model

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Interactive pattern recognition in Cardiovascular Disease Management. A Process Mining approach 3

Interactive Pattern Recognition in Cardiovascular Disease Ma...

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3rd IEEE EMBS international conference on Biomedical and Health Informatics (IEEE BHI)

作者： Fernandez-Llatas, Carlos Bayo, Jose Luis Martinez-Romero, Alvaro Benedi, Jose Miguel Traver, Vicente Univ Politecn Valencia ITACA Valencia Spain Univ Politecn Valencia PRHLT Valencia Spain

ISBN: (纸本)9781509024551

Cardiovascular diseases are one of the main causes of mortality in the European Union. Cardiovascular diseases require a continuous follow-up in order to prevent complications that produce a decrease on the quality of life of patients and can even lead to their death. According to the Evidence Based Medicine thesis, the involvement of the patient in the care process will improve the Quality of Care provided and the efficiency of Care Plans. However, there is controversy in the literature about the fact that the Care Plans that Evidence Based Medicine provides are based on strict clinical cases to generate scientific evidence that is unclear whether they can be applied to personalized medicine. The use of an Interactive pattern recognition approach can create models controlled by human experts based on the biomedical data provided, in addition to medical decisions and the patient personality, providing a better way to find more tailored models. However, the use of Interactive pattern recognition techniques still requires the application of Human Understandable pattern recognition techniques. In this paper, an Interactive pattern recognition technique based on Process Mining technology is presented as a solution to deal with this problem.

关键词： Diseases

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A Method to Improve the Robustness of Grasping pattern recognition for Prosthetic Hands 3

A Method to Improve the Robustness of Grasping Pattern Recog...

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3rd international conference on Systems and Informatics (ICSAI)

作者： Zhu, Gaoke Zhong, Guoliang Deng, Hua Cent S Univ Sch Mech & Elect Engn Changsha 410083 Hunan Peoples R China Cent S Univ State Key Lab High Performance Complex Mfg Changsha 410083 Hunan Peoples R China

ISBN: (纸本)9781509055210

Myoelectric control can achieve the bionic motion function of prosthetic hand by using the subjective thinking of upper limb amputation patients. To implement different grasping forces by prosthetic hand users usually needs to change the muscle contraction evaluate (MCE) of residual limb. MCE change causes the enhancements of the non-stationary of surface electromyographic (sEMG), which leads to the reduction of grasping pattern recognition rate. According to the above problem, considering the variation of MCE in the experiment, ten subjects grasp objects by employing eight grasping patterns with small, medium, and big forces respectively and the corresponding sEMG is collected. It is found that the grasping pattern recognition rate is declined after adding disturbances. This paper considers three solutions, namely, increasing the range of training sample set, choosing the characteristics of stability, and choosing robust classifier. The increase of training sample range can improve the effect of classification but increase the training time and complexity. In this paper, robustness index of sEMG pattern recognition method is proposed under the small training sets, based on which the characteristics of stability and robustness of the classifier are chosen in 102 groups of characteristics.

关键词： prosthetic hand myoelectric control grasping pattern recognition surface electromyographic

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Analysis of Local Descriptors for Human Face recognition 3rd

Analysis of Local Descriptors for Human Face Recognition

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3rd international conference on Advanced Computing, Networking, and Informatics (ICACNI)

作者： Shyam, Radhey Singh, Yogendra Narain Inst Engn & Technol Dept Comp Sci & Engn Lucknow 226021 Uttar Pradesh India

ISBN: (纸本)9788132225386;9788132225379

Facial image analysis is an important and profound research in the field of computer vision. The prime issue of the face recognition is to develop the robust descriptors that discriminate facial features. In recent years, the local binary pattern (LBP) has attained a big attention of the biometric researchers, for facial image analysis due to its robustness shown for the challenging databases. This paper presents a novel method for facial image representation using local binary pattern, called augmented local binary pattern (A-LBP) which works on the consolidation of the principle of locality of uniform and non-uniform patterns. It replaces the non-uniform patterns with the mod value of the uniform patterns that are consolidated with the neighboring uniform patterns and extract pertinent information from the local descriptors. The experimental results prove the efficacy of the proposed method over LBP on the publicly available face databases, such as AT & T-ORL, extended Yale B, and Yale A.

关键词： Face recognition Local binary pattern Histogram Descriptor

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Automated Patient Handling Activity recognition for At-Risk Caregivers Using an Unobtrusive Wearable Sensor 3

Automated Patient Handling Activity Recognition for At-Risk ...

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3rd IEEE EMBS international conference on Biomedical and Health Informatics (IEEE BHI)

作者： Lin, Feng Xu, Xiaowei Wang, Aosen Cavuoto, Lora Xu, Wenyao Univ Buffalo SUNY Dept Comp Sci & Engn Buffalo NY 14260 USA Univ Buffalo SUNY Dept Ind & Syst Engn Buffalo NY 14260 USA

ISBN: (纸本)9781509024551

Patient handling activities with awkward postures expose healthcare providers to a high risk of overexertion injury. The recognition of patient handling activities (PHA) is the first step to reduce injury risk for caregivers. In this paper, we propose a system to solve the problem, which comprises an unobtrusive wearable device and a novel spatio-temporal warping (STW) pattern recognition framework. The wearable device, named Smart Insole 2.0, is equipped with a rich set of sensors and can capture the information of patient handling activities. The STW pattern recognition framework fully exploits the spatial and temporal characteristics of plantar pressure, to quantify the similarity for the purpose of activity recognition. we perform a pilot study with eight subjects, including eight common activities in a nursing room. The experimental results show the overall classification accuracy achieves 91.7%. Meanwhile, the qualitative profile and load level can also be classified with accuracies of 98.3% and 92.5%, respectively.

关键词： pattern recognition

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Shape classification according to LBP persistence of critical points 19th

Shape classification according to LBP persistence of critica...

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19th iapr international conference on Discrete Geometry for Computer Imagery, DGCI 2016

作者： Janusch, Ines Kropatsch, Walter G. Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms TU Wien Vienna Austria

ISBN: (纸本)9783319323596

This paper introduces a shape descriptor based on a combination of topological image analysis and texture information. Critical points of a shape’s skeleton are determined first. The shape is described according to persistence of the local topology at these critical points over a range of scales. The local topology over scale-space is derived using the local binary pattern texture operator with varying radii. To visualise the descriptor, a new type of persistence graph is defined which captures the evolution, respectively persistence, of the local topology. The presented shape descriptor may be used in shape classification or the grouping of shapes into equivalence classes. Classification experiments were conducted for a binary image dataset and the promising results are presented. Because of the use of persistence, the influence of noise or irregular shape boundaries (e.g. due to segmentation artefacts) on the result of such a classification or grouping is bounded. © Springer international Publishing Switzerland 2016.

关键词： Local binary pattern

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pattern recognition on Herbs Leaves Using Region-Based Invariants Feature Extraction 3

Pattern Recognition on Herbs Leaves Using Region-Based Invar...

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3rd international conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)

作者： Isnanto, R. Rizal Zahra, Ajub Ajulian Julietta, Patricia Diponegoro Univ Dept Comp Engn Semarang Indonesia Diponegoro Univ Dept Elect Engn Semarang Indonesia

ISBN: (纸本)9781509008902

As medicine, herbal plants have been widely used since ancient times, and are still used today. There are various types of herbal plants that can be used as medicine but due to the limited ability of communities to recognize the type of plants and the lack of information, both cause the limited use of plants as medicine. In this research, an herbal plants identification system based on leaves pattern was developed. This identification system is based on the shape of the herbal plants' leaves. Before identification, preprocessing stages should be performed such as conversion to grayscale image, conversion to binary image, and image segmentation using Otsu's method. Feature extraction method used in this system is one kind of region-based invariant feature extraction, which is well-known as Hu's seven moments invariant and the Euclidean or Canberra distance as a recognition method. The research was conducted on 15 types of herbal plants. Based on the research, the percentage of recognition in this identification system using Euclidean Distance reached 86.67% with the lowest recognition rate is 40% for mangkokan leaf. While using Canberra distance for recognizing, the percentage of recognition is 72% and the lowest recognition rate is 20% for keji beling leaf. The best recognition rate of 100% for Euclidean distance similarity measure is reached when 9 (nine) types of leaves were implemented, i.e. banyan (beringin), binahong, dolar, keji-beling, laos, noni (mengkudu), papaya, red betel (sirih merah), and soursop (sirsak) leaves. When Canberra distance used, 100% recognition rate was reached by 5 (five) leaves types, i.e. binahong, dolar, pecut-kuda, papaya, and red betel (sirih merah) leaves.

关键词： Identification System herbal plant leaves pattern Hu's seven moments invariant Euclidean distance

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Mining useful Macro-actions in Planning 3

Mining useful Macro-actions in Planning

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3rd international conference on Artificial Intelligence and pattern recognition (AIPR)

作者： Castellanos-Paez, Sandra Pellier, Damien Fiorino, Humbert Pesty, Sylvie Univ Grenoble Alpes LIG F-38000 Grenoble France

ISBN: (纸本)9781467391870

Planning has achieved significant progress in recent years. Among the various approaches to scale up plan synthesis, the use of macro-actions has been widely explored. As a first stage towards the development of a solution to learn on-line macro-actions, we propose an algorithm to identify useful macroactions based on data mining techniques. The integration in the planning search of these learned macro-actions shows significant improvements over six classical planning benchmarks.

关键词： automated planning macro actions pattern mining data mining learning

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