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Discovering optimal features using static analysis and a genetic search based method for Android malware detection

Frontiers of information technology & Electronic Engineering 2018年第6期19卷 712-736页

作者： Ahmad FIRDAUS Nor Badrul ANUAR Ahmad KARIM Mohd Faizal Ab RAZAK Department of Computer System and Technology University of Malaya Faculty of Computer System & Software Engineering University Malaysia Pahang Department of Information Technology Bahauddin Zakariya University

Mobile device manufacturers are rapidly producing miscellaneous Android versions worldwide. Simultaneously, cyber criminals are executing malicious actions, such as tracking user activities, stealing personal data, and committing bank fraud. These criminals gain numerous benefits as too many people use Android for their daily routines, including important communications. With this in mind, security practitioners have conducted static and dynamic analyses to identify malware. This study used static analysis because of its overall code coverage, low resource consumption, and rapid processing. However, static analysis requires a minimum number of features to efficiently classify malware. Therefore, we used genetic search（GS）, which is a search based on a genetic algorithm（GA）, to select the features among 106 strings. To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Na？ve Bayes（NB）, functional trees（FT）, J48, random forest（RF）, and multilayer perceptron（MLP）. Among these classifiers, FT gave the highest accuracy（95%） and true positive rate（TPR）（96.7%） with the use of only six features.

关键词： Genetic algorithm Static analysis Android Malware Machine learning

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Hierarchical Clustering of Complex Symbolic Data and Application for Emitter Identification

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Journal of Computer Science & technology 2018年第4期33卷 807-822页

作者： Xin Xu Jiaheng Lu Wei Wang Laboratory of Science and Technology on Information System Engineering Nanjing Research Institute of Electronics Engineering Nanjing 21000~ China Department of Computer Science University of Helsinki Helsinki 00014 Finland State Key Laboratory for Novel Software and Technology Nanjing University Nanjing 210046 China

It is well-known that the values of symbolic variables may take various forms such as an interval, a set of stochastic measurements of some underlying patterns or qualitative multi-values and so on. However, the majority of existing work in symbolic data analysis still focuses on interval values. Although some pioneering work in stochastic pattern based symbolic data and mixture of symbolic variables has been explored, it still lacks flexibility and computation efficiency to make full use of the distinctive individual symbolic variables. Therefore, we bring forward a novel hierarchical clustering method with weighted general Jaccard distance and effective global pruning strategy for complex symbolic data and apply it to emitter identification. Extensive experiments indicate that our method has outperformed its peers in both computational efficiency and emitter identification accuracy.

关键词： symbolic data analysis stochastic pattern fuzzy interval hierarchical clustering emitter identification

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Interaction between internal waves and surface waves over a slope-shelf 29th

Interaction between internal waves and surface waves over a ...

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29th International Ocean and Polar Engineering Conference, ISOPE 2019

作者： Hsieh, Chih-Min Cheng, Ming-Hung Sau, Amalendu Hwang, Robert R. Peng, Yih-Ferng Yang, Wen-Chang Department of Maritime Information and Technology National Kaohsiung University of Science and Technology Taiwan Department of System Engineering and Naval Architecture National Taiwan Ocean University Keelung Taiwan Department of Aerospace and Software Engineering Gyeongsang National University Jinju Korea Republic of Institute of Physics Academia Sinica Nankang Taipei Taiwan Department of Civil Engineering National Chi Nan University Nantou Hsien Taiwan Kaohsiung Taiwan

ISBN: (纸本)9781880653852

In order to study the interaction between the internal waves (IWs) and the surface waves (SWs) with different periods over a slope-shelf, laboratory experiments and numerical simulations by using plunger wave maker are conducted in the paper. Laboratory results reveal that the wave period of IWs shows significant decrease during this process at long incident;at short incident, the wave period of IWs and SWs keep the same value. The results of the numerical simulation show that the short interaction time causes the weak internal hydraulic jump on front slope when IWs propagates over a slope-shelf. © 2019 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Surface waves

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Environmentally safe layered crystal produced from hazardous chemical elements: TlPb2BrI4, a new promising detector material

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Journal of Alloys and Compounds 2022年 924卷 1页

作者： Khyzhun, O.Y. Vu, Tuan V. Parasyuk, O.V. Fedorchuk, A.O. Fochuk, P.M. Lavrentyev, A.A. Gabrelian, B.V. Levchuk, Ievgen Matt, Gebhard J. Tedde, Sandro F. Schmidt, Oliver Shrestha, Shreetu Brabec, Christoph J. Kityk, I.V. Piasecki, M. Frantsevych Institute for Problems of Materials Science National Academy of Sciences of Ukraine 3 Krzhyzhanovsky Street KyivUA-03142 Ukraine Faculty of Mechanical - Electrical and Computer Engineering School of Engineering and Technology Van Lang University Ho Chi Minh City Viet Nam Department of Inorganic and Physical Chemistry Lesya Ukrainka Volyn National University 13 Voli Avenue LutskUA-43025 Ukraine Department of Inorganic and Organic Chemistry Lviv National University of Veterinary Medicine and Biotechnologies 50 Pekarska Street Lviv79010 Ukraine Yuriy Fed'kovych Chernivtsi National University 2 Kotziubynskoho Street Chernivtsi58012 Ukraine Department of Electrical Engineering and Electronics Don State Technical University 1 Gagarin Square Rostov-on-Don344010 Russia Department of Computational Technique and Automated System Software Don State Technical University 1 Gagarin Square Rostov-on-Don344010 Russia Martensstrasse 7 Erlangen91058 Germany Siemens Healthineers Technology Center Guenther-Scharowsky-Str. 1 Erlangen91058 Germany Electrical Engineering Department Czestochowa University Technology Armii Krajowej 17 Częstochowa42217 Poland Departmentof Experimental Physics and Information-measuring Technology Lesya Ukrainka Volyn National University Voli Avenue 13 Lutsk43025 Ukraine J.Dlugosz University Częstochowa Armii Krajowej 13/15 Częstochowa42200 Poland

Exploring better Gamma, X-Ray and IR-Mid-R detectors, adequately sensitive to ambient temperatures and environmental conditions, is highly desirable. Therefore, following this path, we present detecting opportunities, based on data of experimental and theoretical investigation of the electronic and optical properties, photocurrent behavior at different bias voltages as well as the reflection for the He-Cd cw laser after irradiation by three different IR laser wavelengths, for recently grown TlPb2BrI4 single crystal with strong anisotropic, two-dimensional (2D) layered structure. The X-ray photoelectron spectroscopy brings data on binding energy values of core levels of TlPb2BrI4 for both as-grown and Ar+-ion-treated crystal surfaces as well as for elucidation of the energy distribution of the valence electronic states. In opposite to well-known IR-detector materials, TlPb2BrI4 crystal surface shows high chemical stability concerning Ar+-ion bombardment. Further, we carry out ab initio band-structure calculations to gain curves of total and partial densities of states and to elucidate the principal optical constants of TlPb2BrI4. The present studies indicate that, in spite of the fact that the TlPb2BrI4 crystal contains two very hazardous/toxic chemical elements, thallium and lead;however, it is chemically stable and reveals very low hygroscopic behavior when being exposed to environmental conditions. © 2022 Elsevier B.V.

关键词： X ray photoelectron spectroscopy

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A Density-based Clustering Algorithm Using Adaptive Parameter K-Reverse Nearest Neighbor

A Density-based Clustering Algorithm Using Adaptive Paramete...

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IEEE International Conference on Power, Intelligent Computing and systems

作者： Pengyu Pei Dong Zhang Feng Guo Industrial Technology Research Institute Zhengzhou University System Software R&D Department Inspur Electronic Information Industry Co. Ltd

ISBN: (纸本)9781728137216

Density-based clustering method DBSCAN is one of the most widely used clustering methods, this algorithm does not need to input the number of clustering, and can find clusters of any shape. However, DBSCAN algorithm requires two parameters, with different parameters, the clustering results are quite different. This paper proposes a density-based clustering algorithm using adaptive parameter k-reverse nearest neighbor: ARKNN-DBSCAN, which can effectively identify and separate clusters with different densities by analyzing the correlation through the reverse k-nearest neighbor of the observation in the dataset without input parameters. Our results show that this algorithm is more accurate than other density-based clustering algorithms using adaptive parameter.

关键词： Clustering algorithms K-reverse nearest neighbor DBSCAN Adaptive parameter Clustering algorithms Nearest neighbor algorithms Clustering methods Self tuning two parameter input parameter Dataset

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Harmonized software Quality Improvement Models for Sudanese SME Based on CMMI

Harmonized Software Quality Improvement Models for Sudanese ...

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International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)

作者： Zeinab Mahmoud Aiman Solyman Arafat Abdulgader Mohammed Elhag Department of Computer Science Faculty of Science and Technology Nile Valley University Sudan School of software engineering South china University of Technology SCUT China Department of Information System University of Bisha Saudi Arabia

ISBN: (数字)9781728110066

ISBN: (纸本)9781728110073

software institutions recently implement more than one software process model in order to achieve a high value in their products and services. The challenges of implementing several quality models are increasing the risk of Multi-Model Environment (MME) failure and more resources are needed to support the MME. This kind of resources is not available in the Small and Medium Enterprises (SME), especially in Sudanese institutions. This study aims to provide a solution by encouraging the Sudanese SMEs to apply software models in their software development processes. We are seeking to make these institutions understand how to integrate product quality models with software process improvement models. To achieve this goal, we used a systematic harmonization technique to harmonize and map ISO/IEC 25010 standard onto Capability Maturity Model Integrity (CMMI) Dev 1.3 level 2 and 3. Also, we reviewed the related works of the previous studies on MMEs to achieve better results. The results show some of the processes and activities of CMMI Dev 1.3 considering software quality attributes on the early stage of the software Development Lifecycle (SDLC). On the other hand, we presented how to apply the mapped models and suggest a tool for implementation. This kind of approach gives small organizations the ability to apply multi SPI models.

关键词： software quality ISO Standards Capability maturity model Organizations Analytical models

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The simulation of open one-side uncertain probability for fusion model of data uncertainty and data relation uncertainty 3

The simulation of open one-side uncertain probability for fu...

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3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Ye, Ruiqi Liao, Mingxue Cui, Tianyu Lv, Pin Science and Technology on Integrated Information System Laboratory Institute of Software CAS South No.4 street Zhongguancun Beijing China Department of Software Engineering School of Software Shandong University Jinan Shandong China

ISBN: (纸本)9781538647936

Uncertain big data has become increasingly important in our life, since uncertainties exist in data generation/acquisition, physical measurements and data staling. Thus, in this paper, we aim to create a unified mathematical model between data uncertainties and data relation uncertainties, which are both important aspects of uncertain big data. We first proposed the fusion model of data uncertainty and data relation uncertainty, which consists of data uncertainty model and data relation uncertainty model. Then we defined two fundamental forms for data uncertainty model and two fundamental forms for fusion model, which are open uncertainty, closed uncertainty and one-side uncertainty, coupling uncertainty respectively. After that we picked a part of the fusion model called open one-side uncertainty to discuss. We studied the open one-side uncertainty under both continuous distribution assumption and discrete distribution assumption, and obtained the expressions for reverse probability respectively. Last but not least, we simulated our model and acquired the averaged values of relative error and absolute error under two kinds of distribution assumption, which are around 0.5% and 0.1% respectively. Finally, we concluded that our model is correct and feasible while the simulation program is efficient as well. © 2018 IEEE.

关键词： Big data

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Order-Preserving Wasserstein Discriminant Analysis

Order-Preserving Wasserstein Discriminant Analysis

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International Conference on Computer Vision (ICCV)

作者： Bing Su Jiahuan Zhou Ying Wu Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Northwestern University Evanston IL

ISBN: (数字)9781728148038

ISBN: (纸本)9781728148045

Supervised dimensionality reduction for sequence data projects the observations in sequences onto a low-dimensional subspace to better separate different sequence classes. It is typically more challenging than conventional dimensionality reduction for static data, because measuring the separability of sequences involves non-linear procedures to manipulate the temporal structures. This paper presents a linear method, namely Order-preserving Wasserstein Discriminant Analysis (OWDA), which learns the projection by maximizing the inter-class distance and minimizing the intra-class scatter. For each class, OWDA extracts the order-preserving Wasserstein barycenter and constructs the intra-class scatter as the dispersion of the training sequences around the barycenter. The inter-class distance is measured as the order-preserving Wasserstein distance between the corresponding barycenters. OWDA is able to concentrate on the distinctive differences among classes by lifting the geometric relations with temporal constraints. Experiments show that OWDA achieves competitive results on three 3D action recognition datasets.

关键词： Training Dimensionality reduction Dispersion Complexity theory Distortion Legged locomotion Prototypes

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SHREC 2019 - Monocular image based 3D model retrieval 12

SHREC 2019 - Monocular image based 3D model retrieval

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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for Computer Graphics, EG 2019

作者： Li, Wenhui Liu, Anan Nie, Weizhi Song, Dan Li, Yuqian Wang, Weijie Xiang, Shu Zhou, Heyu Bui, Ngoc-Minh Cen, Yunchi Chen, Zenian Chung-Nguyen, Huy-Hoang Diep, Gia-Han Do, Trong-Le Doubrovski, Eugeni L. Duong, Anh-Duc Geraedts, Jo M.P. Guo, Haobin Hoang, Trung-Hieu Li, Yichen Liu, Xing Liu, Zishun Luu, Duc-Tuan Ma, Yunsheng Nguyen, Vinh-Tiep Nie, Jie Ren, Tongwei Tran, Mai-Khiem Tran-Nguyen, Son-Thanh Tran, Minh-Triet Vu-Le, The-Anh Wang, Charlie C.L. Wang, Shijie Wu, Gangshan Yang, Caifei Yuan, Meng Zhai, Hao Zhang, Ao Zhang, Fan Zhao, Sicheng Shool of Electrical and Information Engineering Tianjin University China University of Science VNU-HCM Viet Nam State Key Laboratory of Virtual Reality Technology and System Beihang University China Delft University of Technology Netherlands University of Information Technology VNU-HCM Viet Nam Nanjing University China SuoAo Technology Center SAEE University of Science and Technology Beijing China Chinese University of Hong Kong Hong Kong School of Software Dalian University of Technology China Department of Electrical Engineering and Computer Sciences University of California Berkeley United States Ocean University of China China

ISBN: (纸本)9783038680772

Monocular image based 3D object retrieval is a novel and challenging research topic in the field of 3D object retrieval. Given a RGB image captured in real world, it aims to search for relevant 3D objects from a dataset. To advance this promising research, we organize this SHREC track and build the first monocular image based 3D object retrieval benchmark by collecting 2D images from ImageNet and 3D objects from popular 3D datasets such as NTU, PSB, ModelNet40 and ShapeNet. The benchmark contains classified 21,000 2D images and 7,690 3D objects of 21 categories. This track attracted 9 groups from 4 countries and the submission of 20 runs. To have a comprehensive comparison, 7 commonly-used retrieval performance metrics have been used to evaluate their retrieval performance. The evaluation results show that the supervised cross domain learning get the superior retrieval performance (Best NN is 97.4 %) by bridging the domain gap with label information. However, there is still a big challenge for unsupervised cross domain learning (Best NN is 61.2%), which is more practical for the real application. Although we provided both view images and OBJ file for each 3D model, all the participants use the view images to represent the 3D model. One of the interesting work in the future is directly using the 3D information and 2D RGB information to solve the task of monocular Image based 3D model retrieval. © 2019 The Author(s)

关键词： 3D modeling

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Color filter array interpolation using cellular neural networks considering self-congruence 16

Color filter array interpolation using cellular neural netwo...

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16th International Workshop on Cellular Nanoscale Networks and Their Applications, CNNA 2018

作者： Iriyama, Taishi Sato, Masatoshi Otake, Tsuyoshi Aomori, Hisashi Tanaka, Mamoru Graduate School of Engineering Tamagawa University Tokyo Japan Department of Software Science Tamagawa University Tokyo Japan Department of Information System Technology Chukyo University Aichi Japan Department of Information and Communication Sciences Sophia University Tokyo Japan

ISBN: (纸本)9783800747665

In this paper, we propose a novel color filter array (CFA) interpolation technique based on color difference correlation model. The difference model exploits the inter-channel correlation, where the interpolation is achieved by using the color differences R-G and B-G. At first the green channel is handled, and the other color channels are estimated based on the result of green channel. Missing color difference values are estimated by using discrete-time cellular neural network (DT-CNN) predictor. First, the DT-CNN transforms color difference values into the optimal coefficients which make possible to establish the optimal prediction using the quincunx A-template. Then, the optimal missing color differences are obtained by using the convolution of the B-template which is derived by rotating the A-template. Moreover, we utilize self-congruence property in order to improve the prediction performance around edges. Experimental evaluation shows that the proposed method has a better performance compared with the conventional method. © VDE VERLAG GMBH.

关键词： Interpolation

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