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

作者： Xinyu Tang 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

Network security logs can provide evidence for forensic investigators. However, the network logs are facing the problems of high repetition rate, high false alarm rate, uniform format and so on, which make it difficult for forensic researchers to find useful information. In this paper, the association rules mining algorithm is used to analyze the network security logs, so as to eliminate the redundant data and to find the implied association between the logs data. Then the graph database is used to visualize the log information. Forensic analysts can obtain effective evidence by observing the graph database, which can improve the efficiency of the forensic analysts to discover the sensitive event information.

关键词： Network Forensics Log Analysis Association rule mining Graph Database

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Video deblurring via semantic segmentation and pixel-wise non-linear kernel

arXiv

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arXiv 2017年

作者： Ren, Wenqi Pan, Jinshan Cao, Xiaochun Yang, Ming-Hsuan IIE CAS Tencent AI Lab School of Computer Science and Engineering Nanjing University of Science and Technology School of Cyber Security University of Chinese Academy of Sciences Electrical Engineering and Computer Science University of California Merced United States

Video deblurring is a challenging problem as the blur is complex and usually caused by the combination of camera shakes, object motions, and depth variations. Optical flow can be used for kernel estimation since it predicts motion trajectories. However, the estimates are often inaccurate in complex scenes at object boundaries, which are crucial in kernel estimation. In this paper, we exploit semantic segmentation in each blurry frame to understand the scene contents and use different motion models for image regions to guide optical flow estimation. While existing pixel-wise blur models assume that the blur kernel is the same as optical flow during the exposure time, this assumption does not hold when the motion blur trajectory at a pixel is different from the estimated linear optical flow. We analyze the relationship between motion blur trajectory and optical flow, and present a novel pixel-wise non-linear kernel model to account for motion blur. The proposed blur model is based on the non-linear optical flow, which describes complex motion blur more effectively. Extensive experiments on challenging blurry videos demonstrate the proposed algorithm performs favorably against the state-of-the-art methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Optical flows

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Information Leakage in Encrypted Deduplication via Frequency Analysis

Information Leakage in Encrypted Deduplication via Frequency...

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International Conference on Dependable Systems and Networks (DSN)

作者： Jingwei Li Chuan Qin Patrick P. C. Lee Xiaosong Zhang University of Electronic Science and Technology of China Chengdu CN Department of Computer Science and Engineering The Chinese University of Hong Kong Center for Cyber Security University of Electronic Science and Technology of China

ISBN: (纸本)9781538605431

Encrypted deduplication seamlessly combines encryption and deduplication to simultaneously achieve both data security and storage efficiency. State-of-the-art encrypted deduplication systems mostly adopt a deterministic encryption approach that encrypts each plaintext chunk with a key derived from the content of the chunk itself, so that identical plaintext chunks are always encrypted into identical ciphertext chunks for deduplication. However, such deterministic encryption inherently reveals the underlying frequency distribution of the original plaintext chunks. This allows an adversary to launch frequency analysis against the resulting ciphertext chunks, and ultimately infer the content of the original plaintext chunks. In this paper, we study how frequency analysis practically affects information leakage in encrypted deduplication storage, from both attack and defense perspectives. We first propose a new inference attack that exploits chunk locality to increase the coverage of inferred chunks. We conduct trace-driven evaluation on both real-world and synthetic datasets, and show that the new inference attack can infer a significant fraction of plaintext chunks under backup workloads. To protect against frequency analysis, we borrow the idea of existing performance-driven deduplication approaches and consider an encryption scheme called MinHash encryption, which disturbs the frequency rank of ciphertext chunks by encrypting some identical plaintext chunks into multiple distinct ciphertext chunks. Our trace-driven evaluation shows that MinHash encryption effectively mitigates the inference attack, while maintaining high storage efficiency.

关键词： Encryption Maximum likelihood estimation Time-frequency analysis Data models computer security

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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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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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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2019年 842卷 v-vi页

作者： Abawajy, Jemal Choo, Kim-Kwang Raymond Islam, Rafiqul Xu, Zheng Atiquzzaman, Mohammed Faculty of Science Engineering and Built Environment Deakin University Geelong GeelongVIC Australia Department of Information Systems and Cyber Security The University of Texas at San Antonio San AntonioTX United States School of Computing and Mathematics Charles Sturt University AlburyNSW Australia Shanghai University Shanghai Shi China School of Computer Science University of Oklahoma NormanOK United States

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Three Layer Game Theoretic Decision Framework for cyber-Investment and cyber-Insurance 8th

Three Layer Game Theoretic Decision Framework for Cyber-Inve...

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8th International Conference on Decision and Game Theory for security, GameSec 2017

作者： Tosh, Deepak K. Vakilinia, Iman Shetty, Sachin Sengupta, Shamik Kamhoua, Charles A. Njilla, Laurent Kwiat, Kevin Department of Computer Science Norfolk State University NorfolkVA United States Department of Computer Science and Engineering University of Nevada RenoNV United States Virginia Modeling Analysis and Simulation Center Old Dominion University NorfolkVA United States Network Security Branch Army Research Laboratory AdelphiMD United States Cyber Assurance Branch Air Force Research Laboratory RomeNY United States

ISBN: (纸本)9783319687100

cyber-threat landscape has become highly complex, due to which isolated attempts to understand, detect, and resolve cybersecurity issues are not feasible in making a time constrained decisions. Introduction of cyber-threat information (CTI) sharing has potential to handle this issue to some extent, where knowledge about security incidents is gathered, exchanged across organizations for deriving useful information regarding the threat actors and vulnerabilities. Although, sharing security information could allow organizations to make informed decision, it may not completely eliminate the risks. Therefore, organizations are also inclined toward considering cyber-insurance for transferring risks to the insurers. Also, in networked environment, adversaries may exploit the information sharing to successfully breach the participating organizations. In this paper, we consider these players, i.e. organizations, adversary, and insure, to model a three layer game, where players play sequentially to find out their optimal strategies. Organizations determine their optimal self-defense investment to make while participating in CTI sharing and cyber-insurance. The adversary looks for an optimal attack rate while the insurer targets to maximize its profit by offering suitable coverage level to the organizations. Using backward induction approach, we conduct subgame perfect equilibrium analysis to find optimal strategies for the involved players. We observe that when cyber-insurance is not considered, attacker prefers to increase its rate of attack. This motivates the organizations to consider cyber-insurance option for transferring the risks on their critical assets. © 2017, Springer International Publishing AG.

关键词： Game theory

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Hierarchical bloom filter trees for approximate matching

arXiv

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arXiv 2017年

作者： Lillis, David Breitinger, Frank Scanlon, Mark Forensics and Security Research Group School of Computer Science University College Dublin Cyber Forensics Research and Education Group Tagliatela College of Engineering University of New Haven

Bytewise approximate matching algorithms have in recent years shown significant promise in detecting files that are similar at the byte level. This is very useful for digital forensic investigators, who are regularly faced with the problem of searching through a seized device for pertinent data. A common scenario is where an investigator is in possession of a collection of "known-illegal" files (e.g. a collection of child abuse material) and wishes to find whether copies of these are stored on the seized device. Approximate matching addresses shortcomings in traditional hashing, which can only find identical files, by also being able to deal with cases of merged files, embedded files, partial files, or if a file has been changed in any way. Most approximate matching algorithms work by comparing pairs of files, which is not a scalable approach when faced with large corpora. This paper demonstrates the effectiveness of using a "Hierarchical Bloom Filter Tree" (HBFT) data structure to reduce the running time of collection-against-collection matching, with a specific focus on the MRSH-v2 algorithm. Three experiments are discussed, which explore the effects of different configurations of HBFTs. The proposed approach dramatically reduces the number of pairwise comparisons required, and demonstrates substantial speed gains, while maintaining effectiveness. Copyright © 2017, The Authors. All rights reserved.

关键词： Digital forensics

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On the design of a secure user authentication and key agreement scheme for wireless sensor networks

On the design of a secure user authentication and key agreem...

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作者： Kumari, Saru Das, Ashok Kumar Wazid, Mohammad Li, Xiong Wu, Fan Choo, Kim-Kwang Raymond Khan, Muhammad Khurram Department of Mathematics Chaudhary Charan Singh University MeerutUttar Pradesh250 005 India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad500 032 India School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411 201 China Nanjing University of Information Science and Technology Nanjing210044 China Department of Computer Science and Engineering Xiamen Institute of Technology Xiamen361021 China Department of Information Systems and Cyber Security The University of Texas at San Antonio San AntonioTX78249 United States School of Computer Science China University of Geosciences Wuhan China School of Information Technology & Mathematical Sciences University of South Australia AdelaideSA Australia Center of Excellence in Information Assurance King Saud University Riyadh Saudi Arabia

A wireless sensor network (WSN) typically consists of a large number of resource-constrained sensor nodes and several control or gateway nodes. Ensuring the security of the asymmetric nature of WSN is challenging, and designing secure and efficient user authentication and key agreement schemes for WSNs is an active research area. For example, in 2016, Farash et al. proposed a user authentication and key agreement scheme for WSNs. However, we reveal previously unpublished vulnerabilities in their scheme, which allow an attacker to carry out sensor node spoofing, password guessing, user/sensor node anonymity, and user impersonation attacks. We then present a scheme, which does not suffer from the identified vulnerabilities. To demonstrate the practicality of the scheme, we evaluate the scheme using NS-2 simulator. We then prove the scheme secure using Burrows–Abadi–Needham logic. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Authentication

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A robust authentication protocol with privacy protection for wireless sensor networks

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2017年 10155 LNCS卷 30-44页

作者： Li, Xiong Niu, Jianwei Raymond Choo, Kim-Kwang School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249-0631 United States

ISBN: (纸本)9783319620237

As a typical application of Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many fields, such as remote healthcare, to gather data of monitoring area. However, due to open nature of wireless channel and limited computing and storage resource of sensor node, how to guarantee the sensitive sensed data are only be accessed by valid user becomes an important issue. Many user authentication protocols for WSNs have been proposed to address this issue, however, previous work more or less have their own weaknesses. Recently, Gope and Hwang proposed a lightweight anonymity authentication for WSNs, and they claimed that their protocol is secure against most attacks. However, our analysis indicates that their protocol still has some design and security flaws. To address the security issue for WSNs, a user authentication protocol with privacy protection for WSNs has been proposed. The analysis and comparisons results show that the proposed protocol is a robust and security one for WSNs. © Springer International Publishing AG 2017.

关键词： Authentication

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