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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

引用

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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A Visualization Method Based on Graph Database in security Logs Analysis

A Visualization Method Based on Graph Database in Security L...

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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

引用

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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