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Erratum to “High-Efficiency Min-Entropy Estimation Based on Neural Network for Random Number Generators”

security and Communication Networks 2020年第1期2020卷

作者： Na Lv Tianyu Chen Shuangyi Zhu Jing Yang Yuan Ma Jiwu Jing Jingqiang Lin State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 *** Data Assurance and Communications Security Research Center Chinese Academy of Sciences Beijing 100093 *** School of Cyber Security University of Chinese Academy of Sciences Beijing 100093 *** China Information Technology Security Evaluation Center Beijing 100085 *** School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100093 ***

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The method of factorizing multi-digit numbers based on the operation of adding odd numbers 8

The method of factorizing multi-digit numbers based on the o...

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8th International Conference Advanced computer Information Technologies, ACIT 2018

作者： Kasianchuk, Mykhailo Yakymenko, Igor Ivasiev, Stepan Shevchuk, Ruslan Tymoshenko, Lidiya Department of Computer Engineering Ternopil National Economic University 8 Chekhova str. Ternopil Ukraine Department of Cyber Security Ternopil National Economic University 8 Chekhova str. Ternopil Ukraine Department of Computer Science Ternopil National Economic University 8 Chekhova str. Ternopil Ukraine Department of Computer Science and Information Systems Management Odesa National Polytechnic University 1 Shevchenko Str. Odesa Ukraine

ISBN: (纸本)9789666544899

The method for factorizing multi-digit numbers based on the addition of odd numbers is developed in this article. The temporal characteristics of software implementations of the proposed method, the classical Fermat method and its improvement are experimentally investigated. It is revealed that the proposed algorithm, whose time reduction is linear, has an advantage over the other two with a large difference between the multipliers that are factorized. Other dependencies are declining parabolic. Copyright © 2018 for the individual papers by the papers'authors.

关键词： Addition Factorization Fermat method Multi-digit numbers Time complexity

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Fast stochastic ordinal embedding with variance reduction and adaptive step size

arXiv

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arXiv 2019年

作者： Ma, Ke Zeng, Jinshan Xiong, Jiechao Xu, Qianqian Cao, Xiaochun Liu, Wei Yao, Yuan School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China Artificial Intelligence Research Center Peng Cheng Laboratory Shenzhen518055 China School of Computer Information Engineering Jiangxi Normal University NanchangJiangxi330022 China Tencent AI Lab Shenzhen Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen518055 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China Department of Mathematics and by courtesy Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

—Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years. Most of the existing methods are based on semi-definite programming (SDP), which is generally time-consuming and degrades the scalability, especially confronting large-scale data. To overcome this challenge, we propose a stochastic algorithm called SVRG-SBB, which has the following features: i) achieving good scalability via dropping positive semi-definite (PSD) constraints as serving a fast algorithm, i.e., stochastic variance reduced gradient (SVRG) method, and ii) adaptive learning via introducing a new, adaptive step size called the stabilized Barzilai-Borwein (SBB) step size. Theoretically, under some natural assumptions, we show the O(T1 ) rate of convergence to a stationary point of the proposed algorithm, where T is the number of total iterations. Under the further Polyak-Lojasiewicz assumption, we can show the global linear convergence (i.e., exponentially fast converging to a global optimum) of the proposed algorithm. Numerous simulations and real-world data experiments are conducted to show the effectiveness of the proposed algorithm by comparing with the state-of-the-art methods, notably, much lower computational cost with good prediction performance. Copyright © 2019, The Authors. All rights reserved.

关键词： Stochastic systems

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Peapods: OS-Independent Memory Confidentiality for Cryptographic Engines

Peapods: OS-Independent Memory Confidentiality for Cryptogra...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Congwu Li Jingqiang Lin Quanwei Cai Bo Luo School of Cyber Security University of Chinese Academy of Sciences Data Assurance and Communication Security Research Center Chinese Academy of Sciences Department of Electrical Engineering and Computer Science The University of Kansas USA

ISBN: (纸本)9781728111421;9781728111414

Cryptography is widely adopted in computer systems to protect the confidentiality of sensitive information. The security relies on the assumption that cryptography keys are never leaked, which may be broken by the memory disclosure attacks, e.g., the Heartbleed and coldboot attacks. Various schemes are proposed to defend against memory disclosure attacks, e.g., performing the cryptographic computations in registers, or adopting the hardware features (e.g., Intel TSX and Intel SGX) to ensure that the plaintext of the cryptography key never appears in memory. However, these schemes are still not widely deployed due to the following limitations: (a) Most of the schemes are deployed in the OS kernel and require the root (or administrator) privileges of the host; and (b) They require the programmers to integrate these protection schemes in the implementation of different cryptography algorithms on different platforms. In this paper, we propose a tool implemented in Clang/LLVM, named Peapods, which provides the user-mode protection for cryptographic keys in software engines. It introduces one qualifier and three intrinsics for the programmers to specify the sensitive variables and code fragments to be protected, making it easier to be deployed. Peapods adopts transactional memory to protect cryptographic keys, while it is OS-independent and does not require the cryptographic computation performed in the OS kernel. Peapods supports the automatic protection between transactions for better performance. We have implemented the prototype of Peapods. Evaluation results demonstrate that Peapods achieves the design goals with a modest overhead (less than 10%).

关键词： Registers Random access memory Engines Kernel Encryption

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Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency

arXiv

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arXiv 2019年

作者： Li, Jia Fu, Kui Zhao, Shengwei Ge, Shiming State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China School of Cyber Security at University of Chinese Academy of Sciences Beijing100095 China

—The performance of video saliency estimation techniques has achieved significant advances along with the rapid development of Convolutional Neural Networks (CNNs). However, devices like cameras and drones may have limited computational capability and storage space so that the direct deployment of complex deep saliency models becomes infeasible. To address this problem, this paper proposes a dynamic saliency estimation approach for aerial videos via spatiotemporal knowledge distillation. In this approach, five components are involved, including two teachers, two students and the desired spatiotemporal model. The knowledge of spatial and temporal saliency is first separately transferred from the two complex and redundant teachers to their simple and compact students, and the input scenes are also degraded from high-resolution to low-resolution to remove the probable data redundancy so as to greatly speed up the feature extraction process. After that, the desired spatiotemporal model is further trained by distilling and encoding the spatial and temporal saliency knowledge of two students into a unified network. In this manner, the inter-model redundancy can be further removed for the effective estimation of dynamic saliency on aerial videos. Experimental results show that the proposed approach outperforms ten state-of-the-art models in estimating visual saliency on aerial videos, while its speed reaches up to 28,738 FPS on the GPU platform. Copyright © 2019, The Authors. All rights reserved.

关键词： Students

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A Modified Fuzzy Fingerprint Vault Based on Pair-Polar Minutiae Structures 13th

A Modified Fuzzy Fingerprint Vault Based on Pair-Polar Minut...

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13th International Conference on Information securityand Cryptology, Inscrypt 2017

作者： Li, Xiangmin Ding, Ning Lu, Haining Gu, Dawu Wang, Shanshan Xu, Beibei Yuan, Yuan Yan, Siyun Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory of Cryptology P.O. Box 5159 Beijing100878 China School of Cyber Security Shanghai Jiao Tong University Shanghai China Information Technology Co. Ltd. Hangzhou China

ISBN: (纸本)9783319751597

Biometrics-based cryptosystems are helpful tools facilitating our daily life. Examples are that people use their biometrics to identify themselves in clouds or protect passwords as well as other privacy information in mobile phones connected to Internet-of-Things. Among various biometrics, fingerprints are one used most widely. A promising type of secure cryptosystems based on fingerprints is the so called fuzzy fingerprint vaults which can bind a secret key to one fingerprint template and release the same key later with the help of a similar but not necessarily fully identical fingerprint template. However, some aspects such as the security and matching accuracy of existing fingerprint-based fuzzy vaults are still not satisfactory due to troublesome issues such as the alignment of fingerprints and minutiae quantization. In this paper we propose a modified fuzzy fingerprint vault based on pair-polar minutiae structures, aiming at achieving better performance. Recall that Li et al. (2016) presented a fuzzy vault based on pair-polar minutiae structures with two-level secure sketch in recovering the secret key. Unlike their scheme, we compress the two-level structure into one level in which minutia descriptors are exploited to match a vault and thus lower the time complexity of decoding. Our experiment evaluation shows that the proposed fuzzy fingerprint vault achieves high matching accuracy. Importantly, our vault is of strong security against existing attacks such as the brute-force attack, false-accept attack and correlation attack. Also this vault adopts the polynomial representation introduced by Dodis and Reyzin (2006) which is thus able to reduce the storage complexity. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Biometrics

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PixelSteganalysis: Pixel-wise Hidden Information Removal with Low Visual Degradation

arXiv

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arXiv 2019年

作者： Jung, Dahuin Bae, Ho Choi, Hyun-Soo Yoon, Sungroh The Dept. of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Dept. of Cyber Security Ewha Womans University Seoul03760 Korea Republic of Dept. of Computer Science & Engineering Interdisciplinary Graduate Program in Medical Bigdata Convergence Kangwon National University Chuncheon 24341 Korea Republic of Ziovision Chuncheon24341 Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul08826 Korea Republic of

Recently, the field of steganography has experienced rapid developments based on deep learning (DL). DL based steganography distributes secret information over all the available bits of the cover image, thereby posing difficulties in using conventional steganalysis methods to detect, extract or remove hidden secret images. However, our proposed framework is the first to effectively disable covert communications and transactions that use DL based steganography. We propose a DL based steganalysis technique that effectively removes secret images by restoring the distribution of the original images. We formulate a problem and address it by exploiting sophisticated pixel distributions and an edge distribution of images by using a deep neural network. Based on the given information, we remove the hidden secret information at the pixel level. We evaluate our technique by comparing it with conventional steganalysis methods using three public benchmarks. As the decoding method of DL based steganography is approximate (lossy) and is different from the decoding method of conventional steganography, we also introduce a new quantitative metric called the destruction rate (DT). The experimental results demonstrate performance improvements of 10-20% in both the decoded rate and the DT. Copyright © 2019, The Authors. All rights reserved.

关键词： Steganography

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TOWARDS CAMERA IDENTIFICATION FROM CROPPED QUERY IMAGES

TOWARDS CAMERA IDENTIFICATION FROM CROPPED QUERY IMAGES

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IEEE International Conference on Image Processing

作者： Waheeb Yaqub Manoranjan Mohanty Nasir Memon Center for Cyber Security New York University Abu Dhabi UAE Department of Computer Science The University of Auckland New Zealand Department of Computer Science and Engineering New York University New York USA

PRNU (Photo Response Non-Uniformity)-based camera fingerprints are useful for identifying the source camera of an anonymous image. As the query image has to be correlated with each candidate camera fingerprint, one key concern of this approach is the high run time overhead when using a large camera database. Clever techniques have been proposed to reduce the computation and I/O time either by reducing the size of the fingerprint or by group testing where multiple candidate fingerprints can be eliminated by a single correlation operation. However, these techniques assume that the query images have not been scaled or cropped. In practice this may often not be the case, especially when query images are taken from social media sites. This paper presents a simple scaling-based approach for source camera identification when the query image is of full resolution or if it is cropped from an unknown location (of the original image). The proposed approach can also be easily combined with other known approaches for PRNU matching of scaled images. Experiments using 250 cameras showed that the run time overhead can decrease by a factor 13 when the query is a cropped image.

关键词： Cameras Correlation Databases Image resolution Interpolation Kernel Radio frequency

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Corrigendum to "Generation of a local lung respiratory motion model using a weighted sparse algorithm and motion prior-based registration" [Comput. Biol. Med. 123 (2020) 103913]

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computers in biology and medicine 2021年 140卷 104271页

作者： Dong Chen Hongzhi Xie Lixu Gu Jing Liu Liang Tian College of Computer and Cyber Security Hebei Normal University Shijiazhuang China Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics and Data Security Hebei Normal University Shijiazhuang China Key Laboratory of Augmented Reality College of Mathematics and Information Science Hebei Normal University Shijiazhuang China. Department of Cardiothoracic Surgery Peking Union Medical College Hospital Beijing China. School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China. Key Laboratory of Augmented Reality College of Mathematics and Information Science Hebei Normal University Shijiazhuang China. Electronic address: liujing01@***. Key Laboratory of Augmented Reality College of Mathematics and Information Science Hebei Normal University Shijiazhuang China. Electronic address: tianliang@***.

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Towards a User and Role-Based Behavior Analysis Method for Insider Threat Detection

Towards a User and Role-Based Behavior Analysis Method for I...

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IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)

作者： Qiujian Lv Yan Wang Leiqi Wang Dan Wang Institute of Information Engineering Chinese Academy of Sciences Beijing China China School of Cyber Security University of Chinese Academy of Science Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing China

Organizations are experiencing an ever-growing concern of how to identify and defend against insider threats. Existing methods have distinguished the minority of users who show suspicious behavior from the majority of users. However, these methods failed to apply the features reflecting the deviation between the behaviors of users and those of their user groups within the similar job roles. This paper focuses on insider threat detection by conducting both user and role behaviors analysis. It extracts multiple features that represent the details of activities conducted by each user and their deviations from the behaviors of their user groups. The malicious users are then detected by using an unsupervised algorithm, Isolation Forest Algorithm, which evaluates the variance that each user exhibits across multiple attributes, compared against the other users. To evaluate the performance of the proposed models comprehensively, we implement a series of experiments with the data lasting 17 months. We compare the proposed method with an existing state-of-the-art method and the results demonstrate the robust performance of the proposed detection method.

关键词： Feature extraction Hidden Markov models Media Organizations Forestry Prediction algorithms

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