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Measuring web page complexity by analyzing TCP flows and HTTP headers

The Journal of China Universities of Posts and Telecommunications 2017年第6期24卷 1-13页

作者： Cheng Weiqing Hu Yangyang Yin Qiaofeng Chen Jiajia School of Computer Science Nanjing University of Posts and Telecommunications Key Laboratory of Computer Network and Information Integration Southeast University Jiangsu Education Information Center Jiangsu Provincial Department of Education

To understand website complexity deeply, a web page complexity measurement system is developed. The system measures the complexity of a web page at two levels： transport-level and content-level, using a packet trace-based approach rather than server or client logs. Packet traces surpass others in the amount of information contained. Quantitative analyses show that different categories of web pages have different complexity characteristics. Experimental results show that a news web page usually loads much more elements at more accessing levels from much more web servers within diverse administrative domains over much more concurrent transmission control protocol （TCP） flows. About more than half of education pages each only involve a few logical servers, where most of elements of a web page are fetched only from one or two logical servers. The number of content types for web game traffic after login is usually least. The system can help web page designers to design more efficient web pages, and help researchers or Internet users to know communication details.

关键词： hyper text transfer protocol concurrent TCP flows world wide web web page complexity

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Evaluation of Age of information for LDPC Coded Transmission over AWGN Channels

Evaluation of Age of Information for LDPC Coded Transmission...

引用

IEEE Vehicular Technology Conference

作者： Mangang Xie Qianfan Wang Jie Gong Xiao Ma School of Data and Computer Science Sun Yat-sen University Guangzhou China School of Electronics and Communication Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou China

Age of information (AoI) is an important metric in real-time status update communication system to assess the freshness of information. Different from previous works, this paper focuses on the average AoI over additive white Gaussian noise (AWGN) channels. A fixed redundancy (FR) coding scheme is considered, which encodes each k-bits update as an n-bits packet by a low-density parity-check (LDPC) code. By using the renewal-reward theory, a closed-form expression of the average AoI under the FR scheme is derived. Simulation results show that the average AoI relies on E_b/N_0, especially in the low E_b/N_0 region. For different E_b/N_0, an optimal code length always exists to minimize the average AoI. In addition, the same average AoI can be achieved with different code lengths in the high E_b/N_0 region. Hence, in the high E_b/N_0 region, short codes are preferred especially when the transmission delay is taken into account.

关键词： Encoding Parity check codes AWGN channels Monitoring Real-time systems Binary phase shift keying Measurement

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引用

IEEE Global Communications Conference

作者： Haojie Feng Yanxiang Jiang Dusit Niyato Fu-Chun Zheng Xiaohu You National Mobile Communications Research Laboratory Southeast University Nanjing China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China School of Computer Engineering Nanyang Technological University (NTU) Singapore School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

In this paper, the content popularity prediction problem in cache-enabled fog radio access networks (F-RANs) is investigated. In order to make the popularity prediction accurate and adaptive, we propose to learn the corresponding popularity prediction model for every content class from the preprocessed popularity series by training a simplified bidirectional long short-term memory (Bi-LSTM) network, and further use it to help build a content classifier in terms of content popularity trend in the training phase. Then, content popularity can be predicted by the right prediction model with respect to the corresponding content class in the predicting phase. Considering that it is hard to collect enough data about numerous content features through F-APs, we propose to only use the number of requests. Our proposed content popularity prediction policy offers a high prediction accuracy with low computational complexity by transferring the high complexity tasks from the predicting phase to the training phase. Simulation results show that the cache hit rate of our proposed policy approaches the optimal performance.

关键词： Predictive models Training Market research Computational modeling Machine learning Radio access networks Adaptation models

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security and privacy on blockchain

arXiv

引用

arXiv 2019年

作者： Zhang, Rui Xue, Rui Liu, Ling State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences 89 Minzhuang Rd Haidian Dist Beijing Beijing100093 China School of Cyber Security University of Chinese Academy of Sciences 19 Yuquan Rd Shijingshan Dist Beijing Beijing100049 China School of Computer Science Georgia Institute of Technology USA AtlantaGA30332-0765 United States

Blockchain offers an innovative approach to storing information, executing transactions, performing functions, and establishing trust in an open environment. Many consider blockchain as a technology breakthrough for cryptography and cybersecurity, with use cases ranging from globally deployed cryptocurrency systems like Bitcoin, to smart contracts, smart grids over the Internet of Things, and so forth. Although blockchain has received growing interests in both academia and industry in the recent years, the security and privacy of blockchains continue to be at the center of the debate when deploying blockchain in different applications. This paper presents a comprehensive overview of the security and privacy of blockchain. To facilitate the discussion, we first introduce the notion of blockchains and its utility in the context of Bitcoin like online transactions. Then we describe the basic security properties that are supported as the essential requirements and building blocks for Bitcoin like cryptocurrency systems, followed by presenting the additional security and privacy properties that are desired in many blockchain applications. Finally, we review the security and privacy techniques for achieving these security properties in blockchain-based systems, including representative consensus algorithms, hash chained storage, mixing protocols, anonymous signatures, non-interactive zero-knowledge proof, and so forth. We conjecture that this survey can help readers to gain an in-depth understanding of the security and privacy of blockchain with respect to concept, attributes, techniques and systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Blockchain

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Andro-MD: Android malware detection based on convolutional neural networks

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International Journal of Performability Engineering 2018年第3期14卷 547-558页

作者： Xie, Nannan Di, Xiaoqiang Wang, Xing Zhao, Jianping School of Computer Science and Technology Changchun University of Science and Technology Changchun130022 China Jilin Provincial Key Laboratory of Network and Information Security Changchun130022 China School of Computer Science and Information Technology Beijing Jiaotong University Beijing100044 China

Android OS maintains its dominance in smart terminal markets, which brings growing threats of malicious applications (apps). The research on Android malware detection has attracted attention from both academia and industry. How to improve the malware detection performance, what classifiers should be selected, and what features should be employed are all critical issues that need to be solved. Convolutional Neural networks (CNN) is a typical deep learning technique that has achieved great performance in image and speech recognitions. In this work, we present an Android malware detection framework Andro-MD that can train and classify samples with a deep learning technique. The framework includes dataset construction and feature preprocessing, training and classification by CNN, and evaluation by experiments. First, an Android app dataset is constructed with 21,000 samples collected from third-party markets and 34,570 features of 7 categories. Second, we employ sequential and parallel models to train the extracted features and classify the malware apps. Finally, extensive experimental results show the effectiveness and feasibility of the proposed method. Comparisons with similar work and traditional classifiers show that Andro-MD has a better performance on malware detection, and its accuracy can achieve 99.25% with a FPR of 0.53%. The request permissions and used permissions feature categories have better performances with limited dimensions. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Convolution

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Exploiting Gabor Feature Extraction Method for Chinese Character Writing Quality Evaluation

引用

Journal of Physics: Conference Series 2020年第1期1575卷

作者： Zhixiao Wang Wenyao Yan Mingtao Guo Jiulong Zhang School of Computer Science and Engineering Xi'an University of Technology Xi'an 710048 China Shaanxi Key Laboratory Xi'an of Network Computing and Security Technology China School of Data Science and Computer Xi'an innovation college of Yan'an University Xi'an 710100 China

The automatic evaluation of Chinese character writing quality has a wide application prospect. Most of the existing evaluation methods of Chinese character writing quality are based on radical segmentation and feature judgment, which require the high accuracy of Chinese character segmentation. However, there are many problems in the real handwriting, such as continuous writing, uneven strength of writing, personalized writing style and so on, which lead to the difficulty of segmentation in the ordinary handwriting. To solve the above problems, we propose an effective method based on image texture where the uniformity of writing lines and writing style is taken as an effective criterion. In our method, Gabor transform is used to extract the image features of writing samples, and finally the statistical learning method of support vector machine is used to effectively evaluate the writing quality. Experiments on multiple real datasets including CHAED show that our method is effective and accurate. The advantage of this method is that it does not need to segment fonts, and the cost of global feature extraction is small.

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Improved meet-in-the-middle attacks on reduced-round Piccolo

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Science China(information Sciences) 2018年第3期61卷 95-107页

作者： Ya LIU Liang CHENG Zhiqiang LIU Wei LI Qingju WANG Dawu GU Department of Computer Science and Engineering University of Shanghai for Science and Technology State Key Laboratory of Cryptology Department of Computer Science and Engineering Shanghai Jiao Tong University School of Computer Science and Technology Donghua University Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Department of Applied Mathematics and Computer Science Technical University of Denmark

Piccolo is a lightweight block cipher that adopts a generalized Feistel network structure with4 branches, each of which is 16 bit long. The key length is 80 or 128 bit, denoted by Piccolo-80 and Piccolo-128, respectively. In this paper, we mounted meet-in-the-middle attacks on 14-round Piccolo-80 without preand post-whitening keys and 18-round Piccolo-128 with post-whitening keys by exploiting the properties of the key schedule and Maximum Distance Separable（MDS） matrix. For Piccolo-80, we first constructed a 5-round distinguisher. Then 4 rounds and 5 rounds were appended at the beginning and at the end,respectively. Based on this structure, we mounted an attack on 14-round Piccolo-80 from the 5 th round to the 18 th round. The data, time, and memory complexities were 252chosen plaintexts, 267.44encryptions, and 264.91blocks, respectively. For Piccolo-128, we built a 7-round distinguisher to attack 18-round Piccolo-128 from the 4 th round to the 21st round. The data, time, and memory complexities were 252chosen plaintexts,2126.63encryptions, and 2125.29blocks, respectively. If not considering results on biclique cryptanalysis,these are currently the best public results on this reduced version of the Piccolo block cipher.

关键词： block cipher lightweight Piccolo meet-in-the-middle attack distinguisher

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Research on Electric Micro-Meteorological Monitoring and Early Warning System

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Journal of Physics: Conference Series 2020年第1期1449卷

作者： Zehao Zhang Zhen Yu Xiyuan Xu Cheng Guan Song Zhang Global Energy Interconnection Research Institute co. Ltd Research Institute of Information Technology & Communication Beijing 102206 China. State Grid Key Laboratory of Information & Network Security State Grid FuJian Electric Power co. LTD

This paper studies and analyzes the influence of micro-meteorological disasters on power system, points out the main problems in the establishment of power micro-meteorological monitoring and early warning system, puts forward the system architecture of power micro-meteorological monitoring and early warning system, which provides a reference for the establishment of power micro-meteorological monitoring and early warning system.

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Bug or not bug? Labeling issue reports via user reviews for mobile apps 30

Bug or not bug? Labeling issue reports via user reviews for ...

引用

30th International Conference on Software Engineering and Knowledge Engineering, SEKE 2018

作者： Li, Haoming Zhang, Tao Wang, Ziyuan College of Computer Science and Technology Harbin Engineering University Harbin150001 China Key Laboratory of Network Assessment Technology Institute of Information Engineering CAS Bejing100093 China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)1891706446

A great number of mobile applications (apps) have been released to the market. Therefore, software maintenance for these apps become an important and challenging task. For each app, developers usually submit issue reports to report the bugs, the features, the questions, and other changes appearing in it. In the process of software maintenance, developers refer to the corresponding labels to decide which one should be fixed first. If the label of an issue report is "bug" which means the report describes a serious error, developers should fix the bug first. Otherwise, if the label is not "bug" (e.g., feature or question), developers can resolve it later. However, according to our investigation, 36.7% of issue reports in top-10 popular mobile apps are not labeled. In other words, there are not any labels in them. It is difficult for developers to decide which issue should be resolved preferentially. To resolve this problem, we propose a method to verify whether an issue report describes a bug or not by using user reviews. Developers usually extract useful information from user reviews to maintain mobile apps. In this work, we utilize tfidf, Word2Vec, and Microsoft Concept Graph (MCG) to compute the textual similarity between issue reports and user reviews related to real bug in order to find the issue reports which describe the real bugs. As a result, our approach with Word2Vec performs the best among three similarity metrics. © 2018 Universitat zu Koln. All rights reserved.

关键词： computer software maintenance

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A note on two constructions of zero-difference balanced functions

arXiv

引用

arXiv 2018年

作者： Yi, Zongxiang Yu, Yuyin Tang, Chunming Zheng, Yanbin School of Mathematics and Information Science Guangzhou University Guangzhou510006 China Key Laboratory of Information Security School of Mathematics and Information Science Guangzhou University Guangzhou510006 China School of Computer Science and Network Security Dongguan University of Technology Dongguan523808 China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin541004 China

Notes on two constructions of zero-difference balanced (ZDB) functions are made in this letter. Then ZDB functions over Ze × Îik=0 Fqi are obtained. And it shows that all the known ZDB functions using cyclotomic cosets over Zn are special cases of a generic construction. Moreover, applications of these ZDB functions are presented. Copyright © 2018, The Authors. All rights reserved.

关键词： Frequency hopping

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