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arXiv 2018年

作者： Wang, Xiangrong Kooij, Robert E. Moreno, Yamir van Mieghem, Piet Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands iTrust Centre for Research in Cyber Security Singapore University of Technology and Design Singapore Singapore University of Zaragoza Zaragoza50009 Spain Department of Theoretical Physics University of Zaragoza Zaragoza50009 Spain ISI Foundation Turin Italy

Networks are often made up of several layers that exhibit diverse degrees of interdependencies. A multilayer interdependent network consists of a set of graphs G that are interconnected through a weighted interconnection matrix B, where the weight of each inter-graph link is a non-negative real number p. Various dynamical processes, such as synchronization, cascading failures in power grids, and diffusion processes, are described by the Laplacian matrix Q characterizing the whole system. For the case in which the multilayer graph is a multiplex, where the number of nodes in each layer is the same and the interconnection matrix B = pI, being I the identity matrix, it has been shown that there exists a structural transition at some critical coupling, p∗. This transition is such that dynamical processes are separated into two regimes: if p > p∗, the network acts as a whole;whereas when p ∗, the network operates as if the graphs encoding the layers were isolated. In this paper, we extend and generalize the structural transition threshold p∗ to a regular interconnection matrix B (constant row and column sum). Specifically, we provide upper and lower bounds for the transition threshold p∗ in interdependent networks with a regular interconnection matrix B and derive the exact transition threshold for special scenarios using the formalism of quotient graphs. Additionally, we discuss the physical meaning of the transition threshold p∗ in terms of the minimum cut and show, through a counter-example, that the structural transition does not always exist. Our results are one step forward on the characterization of more realistic multilayer networks and might be relevant for systems that deviate from the topological constrains imposed by multiplex networks. Copyright © 2018, The Authors. All rights reserved.

关键词： Multilayers

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Matrix Factorization Recommendation Algorithm Based on User Characteristics

Matrix Factorization Recommendation Algorithm Based on User ...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Hongtao Liu Ouyang Mao Chen Long Xueyan Liu Zhenjia Zhu School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of cyber Security and Information Law Chongqing University of Posts and Telecommunications Chongqing China School of Economics and Management Chongqing University of Posts and Telecommunications Chongqing China School of Software Engineering Shenzhen Institute of Information Technology Shenzhen China

ISBN: (纸本)9781728104423;9781728104416

Matrix Factorization is a popular and successful method. It is already a common model method for collaborative filtering in recommendation systems. As most of the scoring matrix is sparse and the dimensions are increasing rapidly, the prediction accuracy and calculation time of the current matrix decomposition are limited. In this paper, a matrix decomposition model based on user characteristics is proposed, which can effectively improve the accuracy of predictive scoring and reduce the number of iterations. By testing the actual data and comparing it with the existing recommendation algorithm, the experimental results show that the method proposed in this paper can predict user's score well.

关键词： Matrix decomposition Prediction algorithms Collaboration Filtering Optimization Mathematical model Telecommunications

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引用

International Conference on Semantics, Knowledge and Grid (SKG)

作者： Hongtao Liu Lulu Guo Long Chen Xueyan Liu Zhenjia Zhu School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of cyber Security and Information Law Chongqing University of Posts and Telecommunications Chongqing China School of Economics and Management Chongqing University of Posts and Telecommunications Chongqing China School of Software Engineering Shenzhen Institute of Information Technology Shenzhen China

ISBN: (纸本)9781728104423;9781728104416

The core of the recommendation system is the recommendation algorithm, especially the application of collaborative filtering recommendation algorithm is the most widely used. With the rapid increase of data sparsity. This paper aims at the problem of data sparsity in collaborative filtering algorithms. By mining the hidden information behind the user and the project, that is, considering different factors in the user's personal rating habits, and using Cosine and Jaccard to calculate the full degree of similarity to effectively use the rate data, improves the similarity calculation method, and solves the problem of low accuracy of the recommendation due to inaccuracy of similarity calculation. This is more in line with the logic of real life and can produce reasonable recommendations.

关键词： Collaboration Filtering algorithms Telecommunications Data mining Internet Recommender systems

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Low-resolution face recognition in the wild via selective knowledge distillation

arXiv

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arXiv 2018年

作者： Ge, Shiming Zhao, Shengwei Li, Chenyu Li, Jia Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security at University of Chinese Academy of Sciences China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible solution is compressing a complex face model to achieve higher speed and lower memory at the cost of minimal performance drop. Inspired by that, this paper proposes a learning approach to recognize low-resolution faces via selective knowledge distillation. In this approach, a two-stream convolutional neural network (CNN) is first initialized to recognize high-resolution faces and resolution-degraded faces with a teacher stream and a student stream, respectively. The teacher stream is represented by a complex CNN for high-accuracy recognition, and the student stream is represented by a much simpler CNN for low-complexity recognition. To avoid significant performance drop at the student stream, we then selectively distil the most informative facial features from the teacher stream by solving a sparse graph optimization problem, which are then used to regularize the fine-tuning process of the student stream. In this way, the student stream is actually trained by simultaneously handling two tasks with limited computational resources: approximating the most informative facial cues via feature regression, and recovering the missing facial cues via low-resolution face classification. Experimental results show that the student stream performs impressively in recognizing low-resolution faces and costs only 0.15MB memory and runs at 418 faces per second on CPU and 9, 433 faces per second on GPU. Copyright © 2018, The Authors. All rights reserved.

关键词： Students

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Greening cloud-enabled big data Storage forensics: Syncany as a case study

arXiv

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arXiv 2018年

作者： Teing, Yee-Yang Dehghantanha, Ali Choo, Kim-Kwang Raymond Abdullah, Mohd Taufik Muda, Zaiton Department of Computer Science Faculty of Computer Science and Technology Universiti Putra Malaysia Serdang Selangor43400 Malaysia School of Computing Science and Engineering University of Salford Salford Greater ManchesterM5 4WT United Kingdom Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249-0631 United States Information Assurance Research Group University of South Australia AdelaideSA5001 Australia

—The pervasive nature of cloud-enabled big data storage solutions introduces new challenges in the identification, collection, analysis, preservation and archiving of digital evidences. Investigation of such complex platforms to locate and recover traces of criminal activities is a time-consuming process. Hence, cyber forensics researchers are moving towards streamlining the investigation process by locating and documenting residual artefacts (evidences) of forensic value of users’ activities on cloud-enabled big data platforms, in order to reduce the investigation time and resources involved in a real-world investigation. In this paper, we seek to determine the data remnants of forensic value for Syncany private cloud storage service, a popular storage engine for big data platforms. We demonstrate the types and the locations of the artefacts that can be forensically recovered. Findings from this research contribute to an in-depth understanding of cloud-enabled big data storage forensics, which can result in reduced time and resources spent in real-world investigations involve Syncany-based cloud platforms. Copyright © 2018, The Authors. All rights reserved.

关键词： Big data

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V-Chain: A Blockchain-Based Car Lease Platform

V-Chain: A Blockchain-Based Car Lease Platform

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IEEE/ACM Int'l Conference on & Int'l Conference on cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Kwame O.-B Obour Agyekum Qi Xia Emmanuel Boateng Sifah Sandro Amofa Kingsley Nketia Acheampong Jianbin Gao Ruidong Chen Hu Xia James C. Gee Xiaojiang Du Mohsen Guizani School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Center for Cyber Security University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Resource and Environment University of Electronic Science and Technology of China Chengdu China Mr. Ray Co. Ltd. Chengdu and with Youe Data Co. Ltd. Beijing China School of Computer Science and Engineering Chengdu and Youe Data Co. Ltd. Beijing China Department of Radiology University of Pennsylvania Chengdu Philadelphia PA China Department of Computer and Information Sciences Temple University Philadelphia PA USA Electrical and Computer Engineering Department University of Idaho Moscow USA

Significant improvements have been made in the way several businesses are conducted due to the influx of blockchain technology, which is a paradigm shift in research these days. Because of the several benefits this technology brings, including scalability, immutability, and the ability to secure data exchange among parties, data transfer becomes easier and simpler between entities. Automobile renting is a major business nowadays. Renting an auto summons numerous frameworks over a chain of procedures - including confirming the lessee's financial status, driving qualifications, accessible vehicle stock and car features. Leasing companies and financiers, however, need to recognize what is happening to the vehicles after the rent is agreed upon. There is also the problem of time consumption, as the traditional car lease process passes through a lot of stages before completion. The blockchain innovation can keep things up to speed with smart contracts. In this paper, we develop a car lease platform that is solely based on blockchain technology. The underlying principle utilized in this system is the smart contract, which is a programmable script that enforces decisions on all transactions made on the system, and also applies penalties to perpetrators. We evaluate the efficiency of our system by measuring the latency and throughput, and make comparisons with other related systems. Results indicate our system outperforms the others.

关键词： Blockchain Automobiles Smart contracts Companies Consumer electronics

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MBSA: a lightweight and flexible storage architecture for virtual machines

MBSA: a lightweight and flexible storage architecture for vi...

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作者： Chen, Xian Chen, Wenzhi Lu, Zhongyong Zhang, Yu Chang, Rui Hassan, Mohammad Mehedi Alelaiwi, Abdulhameed Xiang, Yang College of Computer Science and Technology Zhejiang University Hangzhou China State Key Laboratory of Mathematic Engineering and Advanced Computing Zhengzhou China College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Centre for Cyber Security Research Deakin University BurwoodVIC Australia

With the advantages of extremely high access speed, low energy consumption, nonvolatility, and byte addressability, nonvolatile memory (NVM) device has already been setting off a revolution in storage field. Conventional storage architecture needs to be optimized or even redesigned from scratch to fully explore the performance potential of NVM device. However, most previous NVM-related works only explore its low access latency and low energy consumption. Few works have been done to explore the appropriate way to use NVM device for improving virtual machine's storage performance. In this paper, we comprehensively evaluate and analyze conventional virtual machine's storage architecture. We find that, even with cutting-edge optimization technologies, virtual machine can only achieve 30% of NVM device's original performance. Based on this observation, we propose a memory bus–based storage architecture, which we named MBSA. Memory bus–based storage architecture can greatly shorten the length of virtual machine's storage input/output stack and improve NVM device's use flexibility. In addition, an efficient wear-leveling algorithm is proposed to prolong NVM device's lifespan. To evaluate the new architecture, we implement it as well as the wear-leveling algorithm on real hardware and software platform. Experimental results show that MBSA can provide a big performance improvement, about 2.55X, and the wear-leveling algorithm can efficiently balance write operations on NVM device with a negligible performance overhead (no more than 3%). Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Virtual machine

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Closed-form word error rate analysis for successive interference cancellation decoders

arXiv

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arXiv 2018年

作者： Wen, Jinming Wu, Keyu Tellambura, Chintha Fan, Pingzhi College of Information Science and Technology College of Cyber Security Jinan University Guangzhou510632 China School of Electronic Science National University of Defense Technology Changsha410073 China Department of Electrical and Computer Engineering University of Alberta EdmontonT6G 2V4 Canada Institute of Mobile Communications Southwest Jiaotong University Chengdu610031 China

We consider the estimation of an integer vector x^ ∈ Zn from the linear observation y = Ax^ + v, where A ∈ Rm×n is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian N (0, 1) entries, and v ∈ Rm is a noise vector with i.i.d. N (0, σ2) entries with given σ. In digital communications, x^ is typically uniformly distributed over an n-dimensional box B. For this estimation problem, successive interference cancellation (SIC) decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) x^ ∈ Zn is fixed and (2) x^ is uniformly distributed over B. We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities. Copyright © 2018, The Authors. All rights reserved.

关键词： Errors

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Concolic Execution on Small-Size Binaries: Challenges and Empirical Study

Concolic Execution on Small-Size Binaries: Challenges and Em...

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International Conference on Dependable Systems and Networks (DSN)

作者： Hui Xu Yangfan Zhou Yu Kang Michael R. Lyu Dept. of Computer Science The Chinese University of Hong Kong School of Computer Science Fudan University Engineering Research Center of Cyber Security Auditing and Monitoring Ministry of Education China

ISBN: (纸本)9781538605431

Concolic execution has achieved great success in many binary analysis tasks. However, it is still not a primary option for industrial usage. A well-known reason is that concolic execution cannot scale up to large-size programs. Many research efforts have focused on improving its scalability. Nonetheless, we find that, even when processing small-size programs, concolic execution suffers a great deal from the accuracy and scalability issues. This paper systematically investigates the challenges that can be introduced even by small-size programs, such as symbolic array and symbolic jump. We further verify that the proposed challenges are non-trivial via real-world experiments with three most popular concolic execution tools: BAP, Triton, and Angr. Among a set of 22 logic bombs we designed, Angr can solve only four cases correctly, while BAP and Triton perform much worse. The results imply that current tools are still primitive for practical industrial usage. We summarize the reasons and release the bombs as open source to facilitate further study.

关键词： Tools Concrete Cognition Scalability Testing Data models Arrays

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Mobile Social Network Forensic Analysis Based on Visualization Method

Mobile Social Network Forensic Analysis Based on Visualizati...

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2017 6th International Conference on Advanced Materials and computer science(ICAMCS 2017)

作者： Jiating Li Chunguang Ma Min Yu Chao Liu College of Computer Science and Technology Harbin Engineering University Institution of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences

Nowadays, so much personal information is stored in the mobile phone, especially in mobile social network. Due to the large amount of data in the mobile phone, it is very difficult to extract and analyze the evidence of the mobile phone. The paper presents a visualization forensic analysis method based on mobile social network, and a forensic analysis of mobile phone messages and call records was conducted, the results shows which makes the evidence more intuitive and improves the efficiency of phone forensics. The method can be used as reference for forensic analysts.

关键词： Forensic Analysis Visualization Mobile Social Network

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