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2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013

作者： Yuan, Hai-Dong Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781479910434

Previous studies have shown how to 'fingerprint' certain image processing operation. In this paper, we model the gray-level cumulative distribution of histogram-equalized image as discrete identity function, which is an intrinsic fingerprint produced by global histogram equalization processing. This model is shown to match well with the observed gray-level cumulative distribution. Based on the new model, a classification method is proposed for identifying the use of global histogram equalization processing. In comparison to previous arts, the proposed method can accurately distinguish global histogram equalization from other kinds of contrast enhancement techniques. The effectiveness of the proposed method is exhaustively evaluated in the context of histogram-equalized image identification and resistance against attacks. © 2013 IEEE.

关键词： Image processing

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A parallel target-directed analysis method for malware behaviors

A parallel target-directed analysis method for malware behav...

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International Conference on Cyberspace Technology, CCT 2014

作者： Qin, Yanfeng Wang, Qingxian Zeng, Yongjun Xi, Qi State Key Laboratory of Mathematical Engineering and Advanced Computing China Luoyang University of Foreign Languages China

ISBN: (纸本)9781849199285

To improve the efficiency of analyzing malware behaviors and increase the validity of the test data, this paper proposes a parallel target-directed analysis method for malware behaviors, which combines static analysis with concolic testing techniques. It first uses static analysis techniques to identify and locate those interactive or input points and sensitive behavior functions. Then based on the distributed platform, by combining symbolic execution and concrete dynamic execution together and taking malware sensitive behaviors as the leading target, the parallel target-directed algorithm of searching sensitive paths and the method of leading and approaching sensitive behaviors are designed. It leads to traverse the sensitive functions, obtain the sensitive paths which can reach the sensitive behavior areas by path backtracking, and generate the corresponding test data. Finally, it finishes the analysis and test of malware behaviors. Experiments show that, compared with fuzz and full paths covering and traversing technique, this method can generate test data more efficiently, reduce the number of paths to be analyzed, and improve the analysis speed and efficiency of malware behaviors.

关键词： Malware

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A Selection Strategy for Network Security Defense Based on a Time Game Model

A Selection Strategy for Network Security Defense Based on a...

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2021 International Conference on Digital Society and Intelligent Systems, DSInS 2021

作者： Sun, Pengyu Zhang, Hengwei Ma, Junqiang Li, Chenwei Mi, Yan Wang, Jindong Key Laboratory of Information Security of Henan Provincial State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665406307

Current network assessment models often ignore the impact of attack-defense timing on network security, making it difficult to characterize the dynamic game of attack-defense effectively. To effectively manage the network security risks and reduce potential losses, in this article, we propose a selection strategy for network defense based on a time game model. By analyzing the attack-defense status by analogy with the SIR infectious disease model, construction of an optimal defense strategy model based on time game, and calculation of the Nash equilibrium of the the attacker and the defender under different strategies, we can determine an optimal defense strategy. With the Matlab simulation, this strategy is verified to be effective. © 2021 IEEE.

关键词： Network security

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Timing Strategy for Active Detection of APT Attack Based on FlipIt Model and Q-learning Method

Timing Strategy for Active Detection of APT Attack Based on ...

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2021 International Conference on Digital Society and Intelligent Systems, DSInS 2021

作者： Liu, Zhilin Zhang, Hengwei Sun, Pengyu Mi, Yan Zhang, Xiaoning Wang, Jindong Key Laboratory of Information Security of Henan Provincial State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665406307

At present, APT attack detection mainly focuses on the specific realization of detection technology, and there is little research on the timing strategy for active detection of APT attack. This paper focuses on the problem of APT dynamic detection with timing decision intelligence. We use the FlipIt game model and reinforcement learning method of Q-learning algorithm, consider the APT attack events as an exponentially distributed random process, and the defender using the attacker's last move time (LM-defender) to learn his optimal timing strategy using Q-Learning algorithm. The defender's reinforcement learning mechanism for the timing of the APT attack action and outputs its timing selection strategy. Simulation experiments show that compared with the existing greedy algorithm, the timing strategy based on the Q-Learning algorithm does not require the attacker's prior information under the premise, it can achieve a higher average benefit than the greedy strategy. This result provides a theoretical reference for the design of timing strategy to defend APT attack intelligently and efficient. © 2021 IEEE.

关键词： Reinforcement learning

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Network Attack Intention Recognition Based on Signaling Game Model and Netlogo Simulation

Network Attack Intention Recognition Based on Signaling Game...

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2021 International Conference on Digital Society and Intelligent Systems, DSInS 2021

作者： Zhang, Xiaoning Zhang, Hengwei Li, Chenwei Sun, Pengyu Liu, Zhilin Wang, Jindong State Key Laboratory of Mathematical Engineering and Advanced Computing Key Laboratory of Information Security of Henan Provincial Zhengzhou China

ISBN: (纸本)9781665406307

With the development of attack technology, identifying the real intention of network attack and avoiding further deterioration of security situation has become a hot research topic in recent years. This paper proposes an attack intention recognition method based on signaling game model. Firstly, we generate attack intention hypotheses, and then calculate the probability of each attack intention by solving game equilibrium. Experiments show that the method can effectively improve the accuracy of attack intention recognition from the perspective of the revenue. © 2021 IEEE.

关键词： Deterioration

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New strategy for searching disturbance vector of SHA-1 collision attack

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Science China(Information Sciences) 2017年第12期60卷 280-282页

作者： Hao FENG Guang ZENG Wenbao HAN Yang YANG State Key Laboratory of Mathematical Engineering and Advanced Computing Centrum Wiskunde & Informatica Amsterdam 1098 XG Zhengzhou Information Science and Technology Institute Trusted Computing and Information Assurance Laboratory Institute of SoftwareChinese Academy of Sciences

Dear editor,We present a new algorithm to search for effective disturbance vectors with a complexity of 2;based on the following two properties of disturbance *** property is the weight correlation between the first 16-step disturbance vectors and the60-step disturbance *** other property requires all the differences of the active bit positions of the first 16-step disturbance vectors to be

关键词： New strategy for searching disturbance vector of SHA-1 collision attack

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A new socio-rational secret sharing scheme

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International Journal of Innovative computing and Applications 2017年第1期8卷 21-30页

作者： Jin, Jianghao Zhou, Xie Ma, Chuangui Wang, Xu'an State Key laboratory of Mathematical Engineering and Advanced Computing ZhengzhouHenan China Department of Basic Courses Army Aviation Institute Beijing China Engineering University of CAPF Xi'anShanxi China

We introduce the concept of a socio-rational secret sharing scheme, in which shares are delivered based on players' reputation and the way they contact with other participants. At the secret sharing stage, weights of players are defined such that participants who cooperate will get more shares than those who defect. Alternatively, a newcomer can be enrolled in the scheme when a corrupted player is disengaged immediately. In other words, this scheme successfully renews shares at each cycle without changing the secret, and it allows trusted participants to have a chance to obtain more authority. Our intention is that, in real world applications, participants of a secure scheme may have different levels of importance (i.e., the weight of shares a player owns) as well as reputation (i.e., cooperation with other players for the share renewal or secret recovery). Therefore, a good scheme should balance these two factors alone. In the proposed schemes, both the traditional and rational players are considered in an unconditionally secure setting. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Game theory

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Delay-Distance Correlation Study for IP Geolocation

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Wuhan University Journal of Natural Sciences 2017年第2期22卷 157-164页

作者： DING Shichang LUO Xiangyang YE Dengpan LIU Fenlin The State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 Henan China School of Computer Wuhan University Wuhan 430072Hubei China

Although many classical IP geolocation algorithms are suitable to rich-connected networks, their performances are seriously affected in poor-connected networks with weak delay-distance correlation. This paper tries to improve the performances of classical IP geolocation algorithms by finding rich-connected sub-networks inside poor-connected networks. First, a new delay-distance correlation model （RTD-Corr model） is proposed. It builds the relationship between delay-distance correlation and actual network factors such as the tortuosity of the network path and the ratio of propagation delay. Second, based on the RTD-Corr model and actual network characteristics, this paper discusses about how to find rich-connected networks inside China Intemet which is a typical actual poor-connected network. Then we find rich-connected sub-networks of China Intemet through a large-scale network measurement which covers three major ISPs and thirty provinces. At last, based on the founded rich-connected sub-networks, we modify two classical IP geolocation algorithms and the experiments in China Intemet show that their accuracy is significantly increased.

关键词： IP geolocation delay-distance correlation network security network measurement rich-connected sub-networks

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NEXT:a neural network framework for next POI recommendation

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Frontiers of Computer Science 2020年第2期14卷 314-333页

作者： Zhiqian ZHANG Chenliang LI Zhiyong WU Aixin SUN Dengpan YE Xiangyang LUO Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of EducationSchool of Cyber Science and EngineeringWuhan UniversityWuhan 430072China Department of Computer Science The University of Hong KongPokfulam RoadHong Kong 999077China School of Computer Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore State Key Lab of Mathematical Engineering and Advanced Computing Zhengzhou 450001China

The task of next POI recommendations has been studied extensively in recent ***,developing a unified recommendation framework to incorporate multiple factors associated with both POIs and users remains challenging,because of the heterogeneity nature of these ***,effective mechanisms to smoothly handle cold-start cases are also a difficult *** by the recent success of neural networks in many areas,in this paper,we propose a simple yet effective neural network framework,named NEXT,for next POI *** is a unified framework to learn the hidden intent regarding user's next move,by incorporating different factors in a unified ***,in NEXT,we incorporate meta-data information,e.g.,user friendship and textual descriptions of POIs,and two kinds of temporal contexts(i.e.,time interval and visit time).To leverage sequential relations and geographical influence,we propose to adopt DeepWalk,a network representation learning technique,to encode such *** evaluate the effectiveness of NEXT against other state-of-the-art alternatives and neural networks based *** results on three publicly available datasets demonstrate that NEXT significantly outperforms baselines in real-time next POI *** experiments show inherent ability of NEXT in handling cold-start.

关键词： POI neural networks POI recommendation

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Axiomatic approaches based on the software trustworthiness measure

Axiomatic approaches based on the software trustworthiness m...

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International Conference on Applied System Innovation, ICASI 2015

作者： Tao, H.W. Chen, Y.X. Pang, J.M. State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China MoE Engineering Center for Software/Hardware Co-Design Technology and Application East China Normal University Shanghai China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781138028937

Due to the outstanding problems of software trustworthiness, the measurement of software trustworthiness has aroused more and more concern. However, few researches pay attention to using more rigorous approaches in the measurement of software trustworthiness and carrying out the theoretical validation of measures. Axiomatic approaches by formally defining the desirable properties of the measures for software attributes can provide precise, formal, and unambiguous terms for the quantification of software attributes. We once applied axiomatic approaches to the measured software trustworthiness, presented four properties for software trustworthiness measures and gave three measures for software trustworthiness. In this paper, we propose a new property-related user expectation to establish an improved software trustworthiness measure and validate this measure from the theory point of view by proving that it complies with the five properties presented by us. A comparative study shows that this measure is better than the popular software trustworthiness measures in terms of our properties. © 2016 Taylor & Francis Group.

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