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Cyber Vulnerability Intelligence for Internet of Things binary

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2020年第3期16卷 2154-2163页

作者： Liu, Shigang Dibaei, Mahdi Tai, Yonghang Chen, Chao Zhang, Jun Xiang, Yang Swinburne Univ Technol Sch Software & Elect Engn Hawthorn Vic 3122 Australia Macquarie Univ Dept Comp Sydney NSW 2109 Australia Yunnan Normal Univ Yunnan Key Lab Optoelect Informat Technol Kunming 650101 Yunnan Peoples R China

Internet of Things (IoT) integrates a variety of software (e.g., autonomous vehicles and military systems) in order to enable the advanced and intelligent services. These software increase the potential of cyber-attacks because an adversary can launch an attack using system vulnerabilities. Existing software vulnerability analysis methods used to be relying on human experts crafted features, which usually miss many vulnerabilities. It is important to develop an automatic vulnerability analysis system to improve the countermeasures. However, source code is not always available (e.g., most IoT related industry software are closed source). Therefore, vulnerability detection on binary code is a demanding task. This article addresses the automatic binary-level software vulnerability detection problem by proposing a deep learning-based approach. The proposed approach consists of two phases: binary function extraction, and model building. First, we extract binary functions from the cleaned binary instructions obtained by using IDA Pro. Then, we employ the attention mechanism on top of a bidirectional long short-term memory for building the predictive model. To show the effectiveness of the proposed approach, we have collected datasets from several different sources. We have compared our proposed approach with a series of baselines including source code-based techniques and binary code-based techniques. We have also applied the proposed approach to real-world IoT related software such as VLC media player and LibTIFF project that used on Autonomous Vehicles. Experimental results show that our proposed approach betters the baselines and is able to detect more vulnerabilities.

关键词： Software binary codes Predictive models Machine learning Buildings Feature extraction Autonomous vehicles binary code deep learning machine learning software vulnerability

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Simple capacity-achieving coded modulation strategy

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ELECTRONICS LETTERS 2016年第1期52卷 81-82页

作者： Cazarotto, M. Lopes, R. R. Univ Estadual Campinas DECOM FEEC Sao Paulo Brazil

A simple system that approaches the capacity of the additive white Gaussian noise channel (AWGN) is proposed. It is well known that this capacity is achieved by a Gaussian input, which is hard to obtain in practice. However, if the capacity is <1/2, then the use of a binary input incurs little capacity loss. A parallel between the AWGN and the multiple access channel (MAC) is exploited, which allows for the transformation, without loss of capacity, of the AWGN channel into several parallel channels with capacity <1/2. In this proposal, each channel uses a binary input and a capacity-achieving code, resulting in a system with simple encoding that operates close to capacity. A decoding scheme based on successive interference cancellation is also proposed. As a result, the receiver consists of a series of simple binary receivers. It is shown that the proposed system works at a small gap to the capacity of the AWGN, and that this gap may be attributed to the gap to capacity of the underlying binary code. Similar method has been proposed but the results have shown that this method is better than the iterative method (bit interleaved coded modulation).

关键词： AWGN channels binary codes channel coding decoding interference suppression multi-access systems AWGN channel MAC additive white Gaussian noise channel binary code binary input binary receivers decoding encoding multiple access channel parallel channels simple capacity-achieving coded modulation strategy successive interference cancellation

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Shortened and punctured codes and the MacWilliams identities

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LINEAR ALGEBRA AND ITS APPLICATIONS 1997年第1-3期253卷 1-13页

作者： Goldwasser, JL Department of Mathematics West Virginia University P.O. Box 6310 Morgantown West Virginia 26506-6310 USA

We use shortened and punctured codes to give an elementary proof of a combinatorial identity of Brualdi, Pless, and Beissinger from which the MacWilliams identities follow as special cases. We also give a short, mostl... 详细信息

关键词： Punctured code binary code Proof codes personal identity

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Digital information encrypted in an image using binary encoding

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OPTICS COMMUNICATIONS 2008年第13期281卷 3447-3453页

作者： Lin, Kuang Tsan St Johns Univ Dept Mech & Comp Aided Engn St Johns 25132 NF Taiwan

This paper proposes a new type of encoding methods to encrypt hidden (covert) information in host images. The encrypted information can be plot, fax, word, or network data, and it must be encoded with binary codes. All the pixels in an encoded (overt) image modulated from a host image are classified into three groups. The first group of pixels is called identification codes, used to judge whether the overt image is encoded by a method proposed in this paper or not. The second group of pixels is called type codes, used to judge the encoding type. The third group of pixels is called information codes, used to decode the encoded information. Applying the proposed encoding methods is quite convenient, and host images are not needed for decoding. Decoding covert information from overt images is rather difficult for un-authorized persons, whereas it is very easy for designers or authorized persons. Therefore, the proposed methods are very useful. (C) 2008 Elsevier B.V. All rights reserved.

关键词： encrypt hide covert information overt image binary code

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Design and analysis of codes with distance 4 and 6 minimizing the probability of decoder error

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JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2016年第12期61卷 1440-1455页

作者： Afanassiev, V. B. Davydov, A. A. Zigangirov, D. K. Russian Acad Sci Kharkevich Inst Informat Transmiss Problems Moscow 127051 Russia

The problem of minimization of the decoder error probability is considered for shortened codes of dimension 2 (m) with distance 4 and 6. We prove that shortened Panchenko codes with distance 4 achieve the minimal probability of decoder error under special form of shortening. This shows that Hamming codes are not the best. In the paper, the rules for shortening Panchenko codes are defined and a combinatorial method to minimize the number of words of weight 4 and 5 is developed. There are obtained exact lower bounds on the probability of decoder error and the full solution of the problem of minimization of the decoder error probability for [39,32,4] and [72,64,4] codes. For shortened BCH codes with distance 6, upper and lower bounds on the number of minimal weight codewords are derived. There are constructed [45,32,6] and [79,64,6] BCH codes with the number of weight 6 codewords close to the lower bound and the decoder error probabilities are calculated for these codes. The results are intended for use in memory devices.

关键词： binary code probability of decoder error code weight spectrum

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Deep Hashing for Compact binary codes Learning

Deep Hashing for Compact Binary Codes Learning

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Venice Erin Liong Jiwen Lu Gang Wang Pierre Moulin Jie Zhou Advanced Digital Sciences Center School of Electrical and Electronic Engineering Nanyang Technological University Department of ECE University of Illinois at Urbana-Champaign Department of Automation Tsinghua University

ISBN: (纸本)9781467369657

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search. Unlike most existing binary codes learning methods which seek a single linear projection to map each sample into a binary vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the nonlinear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the deep network: 1) the loss between the original real-valued feature descriptor and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) by including one discriminative term into the objective function of DH which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes. Experimental results show the superiority of the proposed approach over the state-of-the-arts.

关键词： binary code binary vectors top layer hashing Hereditary Xerocytosis Objective function Arts

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Learning Compact binary codes for Visual Tracking

Learning Compact Binary Codes for Visual Tracking

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Xi Li Chunhua Shen Anthony Dick Anton van den Hengel Australian Centre for Visual Technologies The University of Adelaide

ISBN: (纸本)9781467364102

A key problem in visual tracking is to represent the appearance of an object in a way that is robust to visual changes. To attain this robustness, increasingly complex models are used to capture appearance variations. However, such models can be difficult to maintain accurately and efficiently. In this paper, we propose a visual tracker in which objects are represented by compact and discriminative binary codes. This representation can be processed very efficiently, and is capable of effectively fusing information from multiple cues. An incremental discriminative learner is then used to construct an appearance model that optimally separates the object from its surrounds. Furthermore, we design a hypergraph propagation method to capture the contextual information on samples, which further improves the tracking accuracy. Experimental results on challenging videos demonstrate the effectiveness and robustness of the proposed tracker.

关键词： visual tracking binary code Compact Compact Pattern Robustness Visual changes

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Sparse Projections for High-Dimensional binary codes

Sparse Projections for High-Dimensional Binary Codes

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Yan Xia Kaiming He Pushmeet Kohli Jian Sun Univ. of Sci. & Technol. of China Hefei China

ISBN: (纸本)9781467369657

This paper addresses the problem of learning long binary codes from high-dimensional data. We observe that two key challenges arise while learning and using long binary codes: (1) lack of an effective regularizer for the learned high-dimensional mapping and (2) high computational cost for computing long codes. In this paper, we overcome both these problems by introducing a sparsity encouraging regularizer that reduces the effective number of parameters involved in the learned projection operator. This regularizer not only reduces overfitting but, due to the sparse nature of the projection matrix, also leads to a dramatic reduction in the computational cost. To evaluate the effectiveness of our method, we analyze its performance on the problems of nearest neighbour search, image retrieval and image classification. Experiments on a number of challenging datasets show that our method leads to better accuracy than dense projections (ITQ [11] and LSH [16]) with the same code lengths, and meanwhile is over an order of magnitude faster. Furthermore, our method is also more accurate and faster than other recently proposed methods for speeding up high-dimensional binary encoding.

关键词： binary code PROJECTION Speeding valid parameter code length long code Nearest neighbor query

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On partitions of an n-cube into nonequivalent perfect codes

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PROBLEMS OF INFORMATION TRANSMISSION 2007年第4期43卷 310-315页

作者： Avgustinovich, S. V. Solov'eva, F. I. Heden, O. Novosibirsk State Univ RAS Siberian Branch Sobolev Inst Math Novosibirsk 630090 Russia Royal Inst Technol Stockholm Sweden

We prove that for all n = 2(k)-1, k >= 5. there exists a partition of the set of all binary vectors of length n into pairwise nonequivalent perfect binary codes of length n with distance 3.

关键词： binary vectors Perfect N-cube partitions binary code code length codes

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Association schemes related to Kasami codes and Kerdock sets

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DESIGNS codeS AND CRYPTOGRAPHY 1999年第1-3期18卷 89-102页

作者： de Caen, D van Dam, ER Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada

Two new infinite series of imprimitive 5-class association schemes are constructed. The first series of schemes arises from forming, in a special manner, two edge-disjoint copies of the coset graph of a binary Kasami code (double error-correcting BCH code). The second series of schemes is formally dual to the first. The construction applies vector space duality to obtain a fission scheme of a subscheme of the Cameron-Seidel 3-class scheme of linked symmetric designs derived from Kerdock sets and quadratic forms over GF(2).

关键词： association scheme binary code quadratic form

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