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2017 International Conference on Research in Adaptive and Convergent Systems, RACS 2017

作者： Lim, Kyeonghwan Jeong, Jaemin Cho, Seong-Je Choi, Jongmoo Park, Minkyu Han, Sangchul Jhang, Seongtae Dept. of Computer Science Dankook University Yongin448-701 Korea Republic of Dept. of Software Dankook University Yongin448-701 Korea Republic of Dept. of Computer Engineering Konkuk University Chungbuk380-701 Korea Republic of Dept. of Computer Suwon University Suwon445-743 Korea Republic of

ISBN: (纸本)9781450350273

Android applications are exposed to reverse engineering attacks. In particular, the applications written in Java are more prone to reverse engineering in comparison to the applications written in native-code languages such as C or C++ on the Android platform. This is because Java applications are distributed as byte codes, while applications written in native-code languages are distributed as low-level binary codes. In this paper, we propose a new technique to protect Android applications against reverse engineering. Three key characteristics of the proposed approach are as follows. First, we write the main parts of the application in native-code using Android NDK. This not only makes reverse engineering more difficult, but it is also more effective in terms of code reuse. Second, we introduce obfuscation, which hides the intent of the native codes and obscures theirs structure, at the intermediate representation (IR) level. Finally, we integrate an integrity verification scheme which detects whether the critical module of the application has been modified prior to execution of the application. Based on the results of experimentation on five known Android applications, we show that the proposed techniques can be applied without a significant effect on performance. © 2017 Association for Computing Machinery.

关键词： Reverse engineering

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A security analysis and reinforcement design adopting fingerprints over drawbacks of passwords based authentication in remote home automation control system 17

A security analysis and reinforcement design adopting finger...

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6th International Conference on Informatics, Environment, Energy and Applications, IEEA 2017

作者： Mukundwa, Chantal Lee, Seok Won Kim, Ki Hyung Computer Engineering Ajou University Korea Republic of Depts. of Software Convergence Technology Information and Computer Engineering Ajou University Korea Republic of Dept. of Knowledge and Information Engineering Ajou University Korea Republic of

ISBN: (纸本)9781450352307

Privacy has been one of the focus in information security discussion over years and it has become an issue everyone would like to protect though sometime people end up giving up some of their privacy in exchange of other services;however, the privacy in home automation is still crucial as ensuring only allowed users can access the appliances within the house. In this research, we evaluated the drawbacks of using passwords for authentication on mobile application used for home automation and provided and analyzed a more robust system design using fingerprints to take the advantage over uniqueness of fingerprint to identify humans. © 2017 ACM.

关键词： Authentication

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Conducting Online Lab Experiments with Blockly

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IFAC-PapersOnLine 2017年第1期50卷 13474-13479页

作者： Galan, Daniel Heradio, Ruben de la Torre, Luis Dormido, Sebastian Esquembre, Francisco Dept. of Computer Science and Automatic Control Universidad Nacional de Educación a Distancia Juan del Rosal 16 MadridE-28040 Spain Dept. of Software Engineering and Computer Systems Universidad Nacional de Educación a Distancia Juan del Rosal 16 MadridE-28040 Spain Dept. of Mathematics Universidad de Murcia Campus de Espinardo MurciaE-30071 Spain

Laboratory experimentation plays an essential role in control education. To reduce the high costs of maintaining apparatus in traditional labs and to support distance and blended learning, online laboratories are used as a possible alternative to conventional hands-on labs. In these labs it is often desirable to allow students to define their own experiments. This paper presents the definition and implementation of a generic experimentation language for conducting automatic experiments on existing online laboratories. The main objective is to use an online lab, created independently, as a component in which users can perform experiments. To achieve it, authors present the Experiment Application. It is composed by Blockly, to define and design the experiments, and Google Chart, review and visualize the experiment results. This tool offers benefits to students, teachers and, even, lab designers. For the moment, it can be used with any existing lab or simulation created with the authoring tool Easy Java(script) Simulations. Since there are repositories with hundreds of free available labs created with this tool, the potential applicability of the described tool is considerable. To illustrate the utility of the Experiment Application a very well-known system is used: the Simple Harmonic Oscillator system. © 2017

关键词： computer software Experiments Research laboratories Teaching Blockly Easy java(script) Simulations Experimentation Language Javascript Remote laboratories Virtual laboratories

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Android Malware Detection Based on Useful API Calls and Machine Learning

Android Malware Detection Based on Useful API Calls and Mach...

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Artificial Intelligence and Knowledge engineering (AIKE)

作者： Jaemin Jung Hyunjin Kim Dongjin Shin Myeonggeon Lee Hyunjae Lee Seong-je Cho Kyoungwon Suh Dept. of Computer Science and Engineering Dankook University Yongin South Korea Dept. of Datascience Dankook University Yongin South Korea Dept. of Information Statistics Dankook University Yongin South Korea Dept. of Software Science Dankook University Yongin South Korea School of Information Technology Illinois State University Normal IL USA

Accurate malware detection can benefit Android users significantly considering the growing number of sophisticated malwares recently. In this paper, we propose a machine learning based malware detection methodology that identifies the subset of Android APIs that is effective as features and classifies Android apps as benign or malicious apps. The proposed methodology first constructs two ranked lists of popular Android APIs. One is benign_API_list that contains the top popular APIs commonly used in benign apps, and the other malicious_API_list that contains the top popular APIs commonly used in malicious apps. We observe that the set of APIs in benign_API_list is quite different from the set of APIs in malicious_API_list. We apply Random Forest classifier on a dataset of 60,243 apps by using each list as the features of the classifier. To evaluate the proposed methodology, we build top50_benign_API_list and top50_malicious_API_list by only selecting the first 50 APIs in each ranked list. Our evaluation shows that the Random Forest classifier with top50_benign_API_list is more accurate than the one with top50_malicious_API_list. The Random Forest classifier with top50_benign_API_list can achieve high accuracy of 99.98%.

关键词： Malware Forestry Feature extraction Machine learning Training Machine learning algorithms computer science

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3D face recognition via discriminative keypoint selection 14

3D face recognition via discriminative keypoint selection

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14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017

作者： Kim, Jiwhan Han, Dongyoon Hwang, Wonjun Kim, Junmo School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Dept. of Software and Computer Engineering Ajou University Suwon Korea Republic of

ISBN: (纸本)9781509030552

In this paper, we propose a discriminative keypoint selection-based 3D face recognition method that is superior to prevalent techniques in terms of both computational complexity and performance. We use the average face model (AFM) for face registration to efficiently locate the axis of symmetry in the rotated face mesh and recover a full frontal face from a 3D face model commonly corrupted due to pose variances. Instead of using the keypoint detection method, we use the feature selection algorithm to find the most discriminant keypoints for face identification and reduce computational time for not only feature extraction but also keypoint matching. The results of the experiments conducted on the Bosphorus database and the UMB-DB show that our algorithm can improve rank-1 identification accuracy, thus confirming its robustness against pose variances, expressions, and occlusions. © 2017 IEEE.

关键词： Face recognition

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Behavior Recognition of a Person in a Daily Video Using Joint Position Information

Behavior Recognition of a Person in a Daily Video Using Join...

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Artificial Intelligence and Knowledge engineering (AIKE)

作者： Jeong-Min Seo Haanju Yoo Kimin Yun Hyunil Kim Sang-Il Choi Dept. Data Science (of Dankook University) Yongin-si South Korea Dept. Computer Science and Engineering (of Dankook University) Yongin-si South Korea Electronics and Telecommunications Research Institute (ETRI) Daejeon South Korea Dept. Software Science (of Dankook University) Yongin-si South Korea

ISBN: (纸本)9781538695562;9781538660843

In this paper, we propose a method to recognize people's specific behaviors in images acquired in everyday life. The poses that occur when taking a specific action are represented using the joint coordinates of the body. To reduce the influence of the perspective effect on the locations in an image, the coordinates of joints for each person were normalized and the pose was classified using SVM with the normalized coordinates. Experimental results on video images of CCTV camera on ordinary alleys showed that the proposed method relatively recognized a specific behavior.

关键词： Image recognition Support vector machines Cameras Neck Benchmark testing Data mining Legged locomotion

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Considerations regarding security issues impact on systems availability

arXiv

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arXiv 2018年

作者： Pricop, Emil Mihalache, Sanda Florentina Paraschiv, Nicolae Fattahi, Jaouhar Zamfir, Florin Automatic Control Computers and Electronics Department Petroleum-Gas University of Ploiesti Ploiesti Romania Dept. of Computer Science and Software Engineering Université Laval QC Canada Automatic Control Computers and Electronics Dept. Petroleum-Gas University of Ploiesti Ploiesti Romania

Control systems behavior can be analyzed taking into account a large number of parameters: Performances, reliability, availability, security. Each control system presents various security vulnerabilities that affect in lower or higher measure its functioning. In this paper the authors present a method to assess the impact of security issues on the systems availability. A fuzzy model for estimating the availability of the system based on the security level and achieved availability coefficient (depending on MTBF and MTR) is developed and described. The results of the fuzzy inference system (FIS) are presented in the last section of the paper. Copyright © 2018, The Authors. All rights reserved.

关键词： Availability

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Joint optimization of sensing period and transmission time for energy-efficient CRSNs 11

Joint optimization of sensing period and transmission time f...

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11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017

作者： Jin, Zilong Jinsung, Cho Kong, Fanhua Kim, Chang-Woo Na, Sangyeob School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Cho Dept. of Computer Science and Engineering Kyung Hee University Yongin17104 Korea Republic of Dept. of Electronics and Radio Engineering Kyung Hee University Yongin17104 Korea Republic of Dept. of Computer Science Namseoul University Cheonan31020 Korea Republic of

ISBN: (纸本)9781450348881

Cognitive radio technology can enable secondary users (SUs) to occupy licensed bands in a non-interference way. SUs perform spectrum sensing to determine the presence of primary user (PU). Spectrum sensing period and transmission time are the critical parameters for the sensing performance and the secondary throughput, respectively. In this paper, a joint optimization of sensing period and transmission time is proposed for cognitive radio sensor network (CRSNs). The joint optimization model is established by taking the network energy efficiency and interference caused by SU's traffic into consideration. By using the optimization model, we try to figure out the optimal sensing period and transmission time which can guarantee the network energy efficiency and maximize the network throughput jointly. The performance of the proposed optimization model is evaluated through a set of simulations, and the existence of the optimal sensing period and transmission time is verified. © 2017 ACM.

关键词： Sensor networks

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Deep Feature Aggregation and Image Re-ranking with Heat Diffusion for Image Retrieval

arXiv

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arXiv 2018年

作者： Pang, Shanmin Ma, Jin Xue, Jianru Zhu, Jihua Ordonez, Vicente School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Xi’an Jiaotong University Xi’an710049 China Dept. of Computer Science University of Virginia VA22904 United States

Image retrieval based on deep convolutional features has demonstrated state-of-the-art performance in popular benchmarks. In this paper, we present a unified solution to address deep convolutional feature aggregation and image re-ranking by simulating the dynamics of heat diffusion. A distinctive problem in image retrieval is that repetitive or bursty features tend to dominate final image representations, resulting in representations less distinguishable. We show that by considering each deep feature as a heat source, our unsupervised aggregation method is able to avoid over-representation of bursty features. We additionally provide a practical solution for the proposed aggregation method and further show the efficiency of our method in experimental evaluation. Inspired by the aforementioned deep feature aggregation method, we also propose a method to re-rank a number of top ranked images for a given query image by considering the query as the heat source. Finally, we extensively evaluate the proposed approach with pre-trained and fine-tuned deep networks on common public benchmarks and show superior performance compared to previous work. Copyright © 2018, The Authors. All rights reserved.

关键词： Convolution

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Sequential image-based attention network for inferring force estimation without haptic sensor

arXiv

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arXiv 2018年

作者： Shin, Hochul Hyeon, C.H.O. Dongyi, K.I.M. Ko, Dae-Kwan Lim, Soo-Chul Hwang, Wonjun Dept. of Software and Computer Engineering Ajou University San 5-1 Woncheon-dong Yeongtong-gu Suwon-si Gyeonggi-do16499 Korea Republic of Dongguk University Korea Republic of

Humans can approximately infer the force of interaction between objects using only visual information because we have learned it through experiences. Based on this idea, in this paper, we propose a method based on a recurrent convolutional neural network that uses sequential images to infer the interaction force without using a haptic sensor. To train and validate deep learning methods, we collected a large number of images and corresponding data concerning the interaction forces between objects shown therein through an electronic motor-based device. To focus on the changing appearances of a target object owing to external force in the images, we develop a sequential image-based attention module that learns a salient model from temporal dynamics for predicting unknown interaction forces. We propose a sequential image-based spatial attention module and a sequential image-based channel attention module, which are extended to exploit multiple images based on corresponding weighted average pooling layers. Extensive experimental results verified that the proposed method can successfully infer interaction forces in various conditions featuring different target materials, changes in illumination, and directions of external forces. Copyright © 2018, The Authors. All rights reserved.

关键词： Long short-term memory

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