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A secure and high-performance multi-controller architecture for software-defined networking

Frontiers of Information technology & Electronic Engineering 2016年第7期17卷 634-646页

作者： Huan-zhao WANG Peng ZHANG Lei XIONG Xin LIU Cheng-chen HU Department of Computer Science and Technology Xi'an Jiaotong UniversityXi'an 710059China Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory Shijiazhuang 050081China MOE Key Laboratory for Intelligent Networks and Network Security Xi'an Jiaotong UniversityXi'an 710049China

Controllers play a critical role in software-defined networking(SDN).However,existing singlecontroller SDN architectures are vulnerable to single-point failures,where a controller's capacity can be saturated by flooded flow *** addition,due to the complicated interactions between applications and controllers,the flow setup latency is relatively *** address the above security and performance issues of current SDN controllers,we propose distributed rule store(DRS),a new multi-controller architecture for *** DRS,the controller caches the flow rules calculated by applications,and distributes these rules to multiple controller *** controller instance holds only a subset of all rules,and periodically checks the consistency of flow rules with each *** from switches are distributed among multiple controllers,in order to mitigate controller capacity saturation *** the same time,when rules at one controller are maliciously modified,they can be detected and recovered in *** implement DRS based on Floodlight and evaluate it with extensive *** results show that DRS can effectively maintain a consistently distributed rule store,and at the same time can achieve a shorter flow setup time and a higher processing throughput,compared with ONOS and Floodlight.

关键词： Software-defined networking(SDN) security Multi-controller Distributed rule store

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Cross-site scripting attacks on android hybrid applications 17

Cross-site scripting attacks on android hybrid applications

引用

2017 International Conference on Cryptography, security and Privacy, ICCSP 2017

作者： Bao, Wenying Yao, Wenbin Zong, Ming Wang, Dongbin Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications No. 10 Xitucheng Road Beijing100876 China YingCai Honors College University of Electronic Science and Technology of China Chengdu610054 China National Engineering Laboratory for Mobile Network Security Beijing University of Posts and Telecommunications No. 10 Xitucheng Road Beijing100876 China

ISBN: (纸本)9781450348676

Hybrid mobile applications are coded in both standard web languages and native language. The including of web technologies results in that Hybrid applications introduce more security risks than the traditional web applications, which have more possible channels to inject malicious codes to gain much more powerful privileges. In this paper, Cross-site Scripting attacks specific to Android Hybrid apps developed with PhoneGap framework are investigated. We find out that the XSS vulnerability on Hybrid apps makes it possible for attackers to bypass the access control policies of WebView and WebKit to run malicious codes into victim's WebView. With the PhoneGap plugins, the malicious codes can steal user's private information and destroy user's file system, which are more damaging than cookie stealing. © 2017 ACM.

关键词： Android (operating system)

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Flame detection via quaternion discrete cosine transform based spectral saliency

International Journal of Control and Automation

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International Journal of Control and Automation 2016年第9期9卷 343-352页

作者： Zhang, Haiyan Gao, Shangbing Xue, Jianxun Zheng, Hao Faculty of computer and software Jiangsu Provincial Key Laboratory for advanced manufacturing technology Huaiyin Institute of Technology Huai'an China The Key Laboratory for traffic and transportation security of Jiangsu Province Huai'an China Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing Xiaozhuang University Nanjing China

To address the problem of detecting the specific object of flame, this paper proposes quaternion discrete cosine transform based video flame detection algorithm in conjunction with the bottom-up visual attention mechanisms and the flame features. According to the characteristics of the flame to be detected, the brightness, color, texture and motion information of the image are respectively defined and extracted to form a quaternion image, and then the flame saliency map is produced by Quaternion discrete cosine Transform with this quaternion image. Extensive experimental results verify the accuracy and robustness of the proposed method on flame detection. © 2016 SERSC.

关键词： Discrete cosine transforms

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Detecting Malicious PDF Files Using Semi-Supervised Learning Method

Detecting Malicious PDF Files Using Semi-Supervised Learning...

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2017 5th International Conference on Advanced Computer Science Applications and Technologies(ACSAT 2017)

作者： Di Feng Min Yu Yongjian Wang Chao Liu Chunguang Ma Institution of Information Engineering Chinese Academy of Sciences College of Computer Science and Technology Harbin Engineering University School of Cyber Security University of Chinese Academy of Sciences Key Laboratory of Information Network Security of Ministry of Public Security the Third Research Institute of Ministry of Public Security

With the increase in popularity of Portable Document Format(PDF) documents and increasing vulnerability of PDF users, effective detection of malicious PDF documents has become as a more and more significant issue. In this paper, we proposed a way to detect malicious PDF files by using semi-supervise learning method. Compare with previous studies, this method not only improve detection accuracy and generalization ability by combining with three different classifiers, but also effectively utilize the abundant unlabeled PDF files to retrain classifiers and update module by selecting the "useful" files from unlabeled test set.

关键词： malicious PDF files malicious Java Script semi-supervised learning

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Source code fragment summarization with small-scale crowdsourcing based features

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Frontiers of Computer Science 2016年第3期10卷 504-517页

作者： Najam NAZAR He JIANG Guojun GAO Tao ZHANG Xiaochen LI Zhilei REN Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian 116621 China State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China Department of Computing The Hong Kong Polytechnic University Hong Kong China

Recent studies have applied different approaches for summarizing software artifacts, and yet very few efforts have been made in summarizing the source code fragments available on web. This paper investigates the feasibility of generating code fragment summaries by using supervised learning algorithms. We hire a crowd of ten individuals from the same work place to extract source code features on a cor- pus of 127 code fragments retrieved from Eclipse and Net- Beans Official frequently asked questions （FAQs）. Human an- notators suggest summary lines. Our machine learning algo- rithms produce better results with the precision of 82% and perform statistically better than existing code fragment classi- fiers. Evaluation of algorithms on several statistical measures endorses our result. This result is promising when employing mechanisms such as data-driven crowd enlistment improve the efficacy of existing code fragment classifiers.

关键词： summarizing code fragments supervised learning crowdsourcing

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Rectangle transformation problem

arXiv

引用

arXiv 2017年

作者： Wang, Shaojiang He, Kun Pan, Yicheng Xia, Mingji State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences

In this paper, we propose the rectangle transformation problem (RTP) and its variants. RTP asks for a transformation by a rectangle partition between two rectangles of the same area. We are interested in the minimum RTP which requires to minimize the partition size. We mainly focus on the strict rectangle transformation problem (SRTP) in which rotation is not allowed in transforming. We show that SRTP has no finite solution if the ratio of the two parallel side lengths of input rectangles is irrational. So we turn to its complement denoted by SIRTP, in which case all side lengths can be assumed integral. We give a polynomial time algorithm ALGSIRTP which gives a solution at most q/p + O(√p) to SIRTP(p,q)(q ≥ p), where p and q are two integer side lengths of input rectangles p×q and q×p, and so ALGSIRTP is a O(√p)-approximation algorithm for minimum SIRTP(p,q). On the other hand, we show that there is not constant solution to SIRTP(p,q) for all integers p and q (q > p) even though the ratio q/p is within any constant range. We also raise a series of open questions for the research along this line. Copyright © 2017, The Authors. All rights reserved.

关键词： Polynomial approximation

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Utilizing Dynamic Properties of Sharing Bits and Registers to Estimate User Cardinalities over Time

arXiv

引用

arXiv 2018年

作者： Wang, Pinghui Jia, Peng Zhang, Xiangliang Tao, Jing Guan, Xiaohong Towsley, Don MOE Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University China Shenzhen Research Institute of Xi’an Jiaotong University Shenzhen China King Abdullah University of Science and Technology Thuwal Saudi Arabia Zhejiang Research Institute of Xi’an Jiaotong University Hangzhou China Department of Automation and NLIST Lab Tsinghua University Beijing China School of Computer Science University of Massachusetts Amherst MA United States

—Online monitoring user cardinalities (or degrees) in graph streams is fundamental for many applications. For example in a bipartite graph representing user-website visiting activities, user cardinalities (the number of distinct visited websites) are monitored to report network anomalies. These real-world graph streams may contain user-item duplicates and have a huge number of distinct user-item pairs, therefore, it is infeasible to exactly compute user cardinalities when memory and computation resources are limited. Existing methods are designed to approximately estimate user cardinalities, whose accuracy highly depends on parameters that are not easy to set. Moreover, these methods cannot provide anytime-available estimation, as the user cardinalities are computed at the end of the data stream. Real-time applications such as anomaly detection require that user cardinalities are estimated on the fly. To address these problems, we develop novel bit and register sharing algorithms, which use a bit array and a register array to build a compact sketch of all users’ connected items respectively. Compared with previous bit and register sharing methods, our algorithms exploit the dynamic properties of the bit and register arrays (e.g., the fraction of zero bits in the bit array at each time) to significantly improve the estimation accuracy, and have low time complexity (O(1)) to update the estimations each time they observe a new user-item pair. In addition, our algorithms are simple and easy to use, without requirements to tune any parameter. We evaluate the performance of our methods on real-world datasets. The experimental results demonstrate that our methods are several times more accurate and faster than state-of-the-art methods using the same amount of memory. Copyright © 2018, The Authors. All rights reserved.

关键词： Websites

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Coherence-based Automated Essay Scoring using Self-Attention

Coherence-based Automated Essay Scoring using Self-Attention

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第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)

作者： Xia Li Minping Chen Jianyun Nie Zhenxing Liu Ziheng Feng Yingdan Cai Key Laboratory of Language Engineering and Computing Guangdong university of foreign studies Guangzh School of Information Science and Technology/School of Cyber Security Guangdong university of foreig Department of Computer Science and Operations Research University of montreal MontrealCanada

Automated essay scoring aims to score an essay automatically without any human *** methods heavily rely on manual feature engi-neering,making it expensive to extract the *** recent studies used neural-network-based scoring models to avoid feature *** of them used CNN or RNN to learn the representation of the *** these mod-els can cope with relationships between words within a short distance,they are limited in capturing long-distance relationships across *** particular,it is difficult to assess the coherence of the essay,which is an essential criterion in essay *** this paper,we use self-attention to capture useful long-distance relationships between words so as to estimate a coherence *** tested our model on two datasets(ASAP and a new non-native speaker dataset).In both cases,our model outperforms the existing state-of-the-art models.

关键词： Self-Attention Automated Essay Scoring Neural networks

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A geometric image segmentation method based on a bi-convex, fuzzy, variational principle with teaching-learning optimization

A geometric image segmentation method based on a bi-convex, ...

引用

作者： Jin, Haiyan Li, Yaning Xing, Bei Wang, Lei Department of Computer Science and Engineering Xi'An University of Technology No. 5 South Jinhua Road Xi'an Shaanxi710048 China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China

This paper proposes an efficient, bi-convex, fuzzy, variational (BFV) method with teaching and learning based optimization (TLBO) for geometric image segmentation. Firstly, we adopt a bi-convex, object function to process a geometric image. Then, we introduce TLBO to maximally optimize the length-penalty item, which will be changed under the teaching phase and the learner phase of the TLBO. This makes the length penalty item closer to the target boundary. Therefore, the length-penalty item can be automatically adjusted according to the fitness function, namely the evaluation standards of the image quality. At last, we combine the length-penalty item with the numerical remedy mechanism to achieve better results. Compared with existing methods, simulations show that our method is more effective. © 2016 - IOS Press and the authors. All rights reserved.

关键词： Image segmentation

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A Two-grid Method for Linearizing and Symmetrizing the Steady-state Poisson-Nernst-Planck Equations

arXiv

引用

arXiv 2017年

作者： Li, Xuefang Yang, Ying Cheng, Hang School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin Guangxi541004 China School of Mathematics and Computing Science Guangxi Colleges Universities Key Laboratory of Data Analysis and Computation Guangxi Key Laboratory of Cryptography and information Security Guilin University of Electronic Technology Guilin Guangxi541004 China School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin Guangxi541004 China

In this paper, a two-grid method is proposed to linearize and symmetrize the steady-state Poisson-Nernst-Planck equations. The computational system is decoupled to linearize and symmetrize equations by using this method, which can improve the computational efficiency compared with the finite element method. Error estimates are derived for the proposed method. The numerical results show that the two-grid method is effective.65N30, 92C40. Copyright © 2017, The Authors. All rights reserved.

关键词： Finite element method

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