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Stego key searching for LSB steganography on JPEG decompressed image

Science China(Information Sciences) 2016年第3期59卷 60-74页

作者： Jiufen LIU Yuguo TIAN Tao HAN Junchao WANG Xiangyang LUO Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing

At present, steganalysis research focuses on detecting the existence of a hidden message. However,extracting the hidden information, i.e., an extracting attack, is crucial in obtaining effective evidence in computer forensics. Due to the difficulty of an extracting attack, research in this field is limited. In steganography with a stego key, an extracting attack is equivalent to recovering the stego key. In this paper we study a method for recovering the stego key in least significant bit(LSB) steganography with a decompressed JPEG image as the cover image. Firstly, the recovery of the stego key is translated into a cryptanalysis problem for a sequential cipher. The method for recovering the stego key is based on estimating the modification positions. The minimum size of the data used to recover the stego key successfully is discussed. Secondly, when a decompressed JPEG image is used as the cover image, the probability of recovering the cover pixels using recompression is *** is used to compute the error of the estimated sequence. Finally, an algorithm to recover the stego key in LSB steganography with a decompressed JPEG image as the cover image is proposed. The experimental results for the steganographic software, Hide and Seek 4.1 and its variant, which is a typical representative of LSB steganography, show that the proposed method can successfully recover the stego key in LSB replacement and LSB matching, i.e., the extracting attack is successful, and it outperforms three previous methods in terms of computational complexity.

关键词： steganalysis extracting attack LSB steganography decompressed JPEG image recompression stego key

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Classification of Arrhythmia Based on Extreme Learning Machine

Classification of Arrhythmia Based on Extreme Learning Machi...

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International Conference on Intelligent Human-Machine Systems and Cybernetics

作者： Xingjin Zhang Runchuan Li Yongpeng Liu Shan Gao Hongpo Zhang Shengya Shen Zongmin Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou China Cooperative Innovation Center of Internet Healthcare Zhengzhou University Zhengzhou Henan China School of Foreign Languages Zhengzhou University Zhengzhou Henan China

This paper proposes an arrhythmia classification method based on Extreme Learning Machine (ELM). Firstly, we extract a feature vector from the electrocardiogram (ECG) dataset as the input of the ELM model for each heartbeat and use the 10-fold cross validation method to test the model. Secondly, we complete the experiment on the MIT-BIH database according to the AAMI-reported arrhythmia classification criteria. Finally, compared with other methods the average accuracy of classification method proposed in this paper has a 1.7% increase, and the sensitivity of the N, S, V, and Q categories are 99.12%, 75.2%, 93.72%, and 98.64%, respectively. We found that the performance about class F is lower than the best performance in the literature, because the optimal outcome of neural network requires a relatively high number of training samples.

关键词： Arrhythmia Extreme learning machine Heartbeat classification

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A survey of industrial control system testbeds

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IOP Conference Series: Materials Science and engineering 2019年第4期569卷

作者： Yangyang Geng Yi Wang Wenwen Liu Qiang Wei Ke Liu Haolan Wu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 China. Department of Research and Development Center Beijing sifang automation co.ltd Beijing 100085 China

Industrial Control System(ICS) testbed is the basis of ICS safety research. In order to build an ICS testbed, it is necessary to have a deep understanding of the current research status. This paper introduced the structure and composition of the typical ICS system. Then it simply analyzed the technical characteristics, system framework and advantages and disadvantages of four types of typical ICS testbeds. Finally, it summarized application scenarios of ICS testbed and pointed out some problems in testbed construction and the development direction of ICS testbed with the fusion of cyber and physical.

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Accountable multi-authority ciphertext-policy attribute-based encryption without key escrow and key abuse 9th

Accountable multi-authority ciphertext-policy attribute-base...

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9th International Symposium on Cyberspace Safety and Security, CSS 2017

作者： Yu, Gang Ma, Xiaoxiao Cao, Zhenfu Zhu, Weihua Zeng, Junjie State Key Laboratory of Mathematical Engineering and Advanced Computing Information Science and Technology Institute Zhengzhou450001 China Shanghai Key Lab for Trustworthy Computing East China Normal University Shanghai200062 China Zheng Zhou Vocational University of Information and Technology Zhengzhou450046 China

ISBN: (纸本)9783319694702

Ciphertext-policy attribute-based encryption (CP-ABE) is a promising public key encryption primitive enabling fine-grained access control on shared data in public cloud. However, two quite challenging issues, the prevention of key escrow and key abuse, still exist in CP-ABE system. In this paper, we propose a multi-authority CP-ABE scheme without key escrow and key abuse. To prevent key escrow, multiple authorities are employed to perform the same procedure of key generation for an attribute. Thus, no individual authority or colluded authorities that manage no common attribute can decrypt any ciphertext, and it can also resist collusion attack from curious authority with the help of dishonest users. To prevent key abuse of dishonest users, user’s global identifier along with a signature is embedded into the secret key. Thus, any third party can learn the identity from a shared secret key and publicly verify its validity. An advantage of simultaneously preventing key escrow and key abuse is that the proposed scheme can achieve accountability, i.e. an auditor can publicly audit a user or authorities abuse the secret key. At last, the proposed scheme is fully secure in the random oracle model, and due to a key aggregate algorithm its efficiency is comparable to the decentralizing CP-ABE scheme [18] on which it is based. © 2017, Springer International Publishing AG.

关键词： Access control

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Fair Efficiency Comparisons of Decoy-state Quantum key Distribution Protocols

arXiv

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arXiv 2018年

作者： Hong-Xin, Li Ming, Gao Xue-Ping, Yan Bao, Yan Yu, Han Ling, Shan Zhi, Ma Department of Language Engineering LuoyangUniversity of Foreign Languages Luoyang Henan471003 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China College of Animal Science and Technology Henan University of Science and Technology Luoyang Henan471003 China

Secure key rate of decoy-state quantum key distribution protocols hasbeen improved with biased basis choice, however, the securitystandardsand parameters of current protocols are *** a result, we cannotgive an accurate key rate comparison between different kinds of protocols. Taking the schemes based on different formula of secure key rate as examples, we give a fair comparison between typical protocols under universalcomposable securitystandard. Through analyzing the relationship of security parameters in post-processing stage and final secure key, we achieve the unified quantification between protocols based on Gottesman-Lo-Lütkenhaus-Preskill formula and the ones under universal composable security. Based on the above research, the impact of different sending length and secure parameters on secure key rate is investigated, meanwhile, we give the dependent relationship between secure key rate and sending length under different secure parameters. Besides, we analyze the importance and conditions of fair comparison. For the first time we give a fair comparison betweenthe protocols based on GLLP formula and smooth entropy, and taking Raymond protocol and Toshiba protocol as examples, we analyze the way for improving secure key rate in the light intensity choice and the singlebit error rate estimation method. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum cryptography

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Strong light illumination on gain-switched semiconductor lasers helps the eavesdropper in practical quantum key distribution systems

arXiv

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arXiv 2018年

作者： Fei, Yang-yang Meng, Xiang-dong Gao, Ming Yang, Yi Wang, Hong Ma, Zhi State Key Laboratory of Mathematical Engineering and Advanced Computing ZhengzhouHenan450001 China CAS Center for Excellence Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China HefeiAnhui230026 China

The temperature of the semiconductor diode increases under strong light illumination whether thermoelectric cooler is installed or not, which changes the output wavelength of the laser (Lee M. S. et al., 2017). However, other characteristics also vary as temperature increases. These variations may help the eavesdropper in practical quantum key distribution systems. We study the effects of temperature increase on gain-switched semiconductor lasers by simulating temperature dependent rate equations. The results show that temperature increase may cause large intensity fluctuation, decrease the output intensity and lead the signal state and decoy state distinguishable. We also propose a modified photon number splitting attack by exploiting the effects of temperature increase. Countermeasures are also proposed. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum cryptography

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A new aggregate signature scheme in cryptographic currency

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International Journal of Performability engineering 2017年第5期13卷 754-762页

作者： Yuan, Chao Xu, Mixue Si, Xueming State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China

With the rise of Bitcoin, cryptographic currencies have attracted more and more attention. Subsequently, other cryptographic currencies were gradually created, such as Zcash, Moreno, Dash and so on. In cryptographic currency, privacy preserving and expansion are two key technical points. In terms of privacy preserving, more effective solutions were proposed in Zcach, Moreno, Dash and other cryptographic currencies systems, in which ring signature, zero knowledge proof and other cryptographic techniques played important roles. But these schemes mainly considered protecting the addresses of both sides of the transaction. In terms of expansion, lightning network and other projects also give solutions. But most of these projects will bring other problems. In this paper, a signature scheme based on the aggregate signature and the elliptic curve algorithm is proposed to hide the transaction value of a single sender and receiver in the transactions which contain multiple inputs and outputs. This signature scheme achieves the purpose of privacy preserving from the transaction value. Further, the correctness proof and security analysis are given in this paper. In addition to that, another signature scheme that combines aggregation signature with bilinear ring signature is proposed. This aggregate ring signature scheme gives another attempt to solve the problem of expansion in the cryptographic currency system only using cryptographic technologies. At the same time, the sender's addresses can be hidden. Similarly, we also confirmed the correctness of this signature scheme.

关键词： Expansion

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A malware detection system based on intermediate language

A malware detection system based on intermediate language

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International Conference on Systems and Informatics (ICSAI)

作者： Binglin Zhao Jin Han Xi Meng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Malware remains a serious problem for economic corporations, government agencies, and individuals. With the evolution of malware, the malware detection method based on signature, reputation or anomaly show the lack of detection ability. In this paper, we proposed a novel malware detection system, which use the feature extract from intermediate representation and utilizes multiple evaluation methods to detect the malware. We extract the feature from intermediate representation with fine-grained that retain the functional sequence of malware. Then, we use LSTM (Long Sort Term Memory) to learn the pattern from the training set and build a detection system that contain many antivirus software's results to detect malware and classify it. Our approach is evaluated on more than 300,000 samples. Experimental results show that our system can effectively detect unknown malware and classify it.

关键词： Malware Feature extraction Training Classification algorithms Flow graphs Androids

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Quantum man-in-the-middle attack on the calibration process of quantum key distribution

arXiv

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arXiv 2018年

作者： Fei, Yang-Yang Meng, Xiang-Dong Gao, Ming Wang, Hong Ma, Zhi Gao, Ming State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan450001 China Cas Ctr. for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui230026 China

Quantum key distribution (QKD) protocol has been proved to provide unconditionally secure key between two remote legiti-mate users in theory. key distribution signals are transmitted in a quantum channel which is established by the calibration process to meet the requirement of high count rate and low error rate. All QKD security proofs implicitly assume that the quantum channel has been established securely. However, the eavesdropper may attack the calibration process to break the security assumption of QKD and provide precondition to steal information about the final key successfully. Inspired by N. Jain et al., Phys. Rev. Lett.107,110501(2011), we reveal the security risk of the calibration process of a passive-basis-choice BB84 QKD system by launching a quantumman-in-the-middle attack which intercepts all calibration signals and resends faked ones. Large temporal bit-dependent or basis-dependent detector efficiency mismatch can be induced. Then we propose a basis-dependent detector efficiency mismatch (BEM) based faked states attack on a single photon BB84 QKD to stress the threat of BEM. Moreover, the security of single photon QKD systems with BEM is studied simply and intuitively. Two effective countermeasures are suggested to remove the general security risk of the calibration process. Copyright © 2018, The Authors. All rights reserved.

关键词： Efficiency

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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