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3rd Annual International Conference on Network and Information Systems for Computers, ICNISC 2017

作者： Yan, Xue-Xiong Ma, Heng-Tai Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Beijing China

ISBN: (纸本)9781538616185

as for detecting taint-style vulnerabilities in PHP codes, this paper introduces function calling control vulnerability, which is a new kind of taint-style vulnerabilities in PHP codes without sensitive function, and enriches classical update rules for taint analysis with a new transfer function definition, which is used to deal with statements with a single function call. The new static vulnerabilities analysis algorithm is implemented in a tool named POSE, and the experiment results of the POSE show that the new algorithm is valid for detecting more type of taint-style vulnerabilities in PHP codes. © 2019 IEEE.

关键词： Codes (symbols)

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SmartGift: Learning to Generate Practical Inputs for Testing Smart Contracts

SmartGift: Learning to Generate Practical Inputs for Testing...

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International Conference on Software Maintenance (ICSM)

作者： Teng Zhou Kui Liu Li Li Zhe Liu Jacques Klein Tegawendé F. Bissyandé Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of Safety-Critical Software Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Monash University Melbourne Australia Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg

With the boom of Initial Coin Offerings (ICO) in the financial markets, smart contracts have gained rapid popularity among consumers. Smart contract vulnerabilities however made them a prime target to malicious attacks that are leading to huge losses. The research community is thus applying various software engineering technologies to smart contracts to address them. In general, to detect vulnerabilities in smart contracts, mutation and fuzz based testing approaches have been widely studied and indeed achieved promising performance on benchmark datasets. Generating test inputs with mutation approaches essentially relies on the available test cases in a smart contract program. In our preliminary study, however, we observed that 56.4% of 218 identified open-source smart contract project repositories do not provide any test case for validation. Fuzzing test inputs leads to random values and lacks practical usefulness. Our work addresses this problem: we propose an approach, Smartgift, which generates practical inputs for testing smart contracts by learning from the transaction records of real-world smart contracts. Leveraging a collected set of over 60 thousand transaction records, Smartgift is able to generate relevant test inputs for ~77% smart contract functions, largely outperforming the traditional fuzzing approach (successful for only 60% functions). We further demonstrate the practicality of the test inputs by using them to replace the test inputs of the ContractFuzzer state of the art smart contract vulnerability detector: with inputs by Smartgift, ContractFuzzer can now detect 131 of the 154 vulnerabilities in its benchmark.

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Multi-Variant Execution Research of Software Diversity

Multi-Variant Execution Research of Software Diversity

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2019 International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2019

作者： Liu, Zhenwu Zhang, Zheng Zhang, Jiexin Liu, Hao State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University ZhengZhou HeNan450001 China

As more and more software products are threatened by malicious reverse analysis, along with software products are pirated, tampered with and so on, it is of great significance to study software security protection technology in depth. As a software security protection technology, software diversification introduces uncertainty into the target program and provides probabilistic protection for the target program. Multi-Variant Execution (MVE) are fine-grained implementation of software diversification that produces functionally identical variants at the system call level. This article first introduces the related concepts of multi-variant execution. Secondly, it expounds the key technologies of multi-variant execution implementation-variant generation, variant monitor, input/output and synchronization, monitor-variant communication. Security of monitors and different variant communication technologies are analyzed and compared, their advantages and defects are pointed out respectively. Several implementation methods of multi-variant execution design are summarized. Finally, the reasons for the false negatives and false positives of attack events are analyzed, and the prospects and challenges of using multi-variant execution techniques to implement security systems are summarized. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Artificial intelligence

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Robust second-order correlation of twin parametric beams generated by amplified spontaneous parametric down-conversion

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Chinese Optics Letters 2020年第12期18卷 63-67页

作者： Kunpeng Jia Xiaohan Wang Xinjie LV Ping Xu Zhenlin Wang ZhiWei Wuang Gang Zhao Yan-Xiao Gong Zhenda Xie Shining Zhu National Laboratory of Solid State Microstructures School of PhysicsSchool of Electronic Science and EngineeringCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China Institute for Quantum Information and State Key Laboratory of High Performance Computing.College of Computing National University of Defense TechnologyChangsha 410073China Mesoscopic Optics and Quantum Electronics Laboratory University of California Los AngelesCciliforniaCA 90095USA

We report an observation of the second-order correlation between twin beams generated by amplified spontaneous parametric down-conversion operating above threshold with kilowatt-level peak power, from a periodically poled Li Ta O3 crystal via a single-pass scheme. Photocurrent correlation was measured because of the bright photon streams, with raw visibility of 37.9% or 97.3% after electronic filtering. As expected in our theory, this correlation is robust and insensitive to parametric gain and detection loss, enabling important applications in optical communications, precision measurement, and nonlocal imaging.

关键词： amplified spontaneous parametric down-con version robust second-order correlation high-gain twin beams

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Double JPEG Compression Detection Based on Markov Model 18th

Double JPEG Compression Detection Based on Markov Model

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18th International Workshop on Digital Forensics and Watermarking, IWDW 2019

作者： Wang, Jinwei Huang, Wei Luo, Xiangyang Shi, Yung-Qing Nanjing University of Information Science and Technology Nanjing210044 China Department of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu210044 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China State Key Laboratory of Information Security Institute Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Electrical Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9783030435745

In this paper, a feature based on the Markov model in quaternion discrete cosine transform (QDCT) domain is proposed for double JPEG compression detection. Firstly, a given JPEG image is extracted from blocked images to obtain amplitude and three angles (ψ, φ, and θ). Secondly, when extracting the Markov features, we process the transition probability matrix with the corresponding refinement. Our proposed refinement method not only reduces redundant features, but also makes the acquired features more efficient for detection. Finally, a support vector machine (SVM) is employed for NA-DJPEG compression detection. It is well known that detecting NA-DJPEG compressed images with (Formula Presented) is a challenging task, and when the images with small size (i.e., 64 × 64), the detection will be more difficult. The experimental result indicates that our method can still achieve a high classification accuracy in this case. © 2020, Springer Nature Switzerland AG.

关键词： Support vector machines

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GNN-Geo: A Graph Neural Network-based Fine-grained IP geolocation Framework

arXiv

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arXiv 2021年

作者： Ding, Shichang Luo, Xiangyang Wang, Jinwei Fu, Xiaoming State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou276800 China School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China Institute of Computer Science University of Göttingen Göttingen37077 Germany

Rule-based fine-grained IP geolocation methods are hard to generalize in computer networks which do not follow hypothetical rules. Recently, deep learning methods, like multi-layer perceptron (MLP), are tried to increase generalization capabilities. However, MLP is not so suitable for graph-structured data like networks. MLP treats IP addresses as isolated instances and ignores the connection information, which limits geolocation accuracy. In this work, we research how to increase the generalization capability with an emerging graph deep learning method - Graph Neural Network (GNN). First, IP geolocation is re-formulated as an attributed graph node regression problem. Then, we propose a GNN-based IP geolocation framework named GNN-Geo. GNN-Geo consists of a preprocessor, an encoder, messaging passing (MP) layers and a decoder. The preprocessor and encoder transform measurement data into the initial node embeddings. MP layers refine the initial node embeddings by modeling the connection information. The decoder maps the refined embeddings to nodes' locations and relieves the convergence problem by considering prior knowledge. The experiments in 8 real-world IPv4/IPv6 networks in North America, Europe and Asia show the proposed GNN-Geo clearly outperforms the state-of-art rule-based and learning-based baselines. This work verifies the great potential of GNN for fine-grained IP geolocation. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep learning

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Influence of Small-Size Contaminations on Thin Film Structural Properties

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Chinese Physics Letters 2019年第3期36卷 82-85页

作者： F.V.Grigoriev V.B.Sulimov Jinlong Zhang Xinbin Cheng Zhanshan Wang A.V.Tikhonravov Research Computing Center M.V.Lomonosov Moscow State University MOE Key Laboratory of Advanced Micro-Structured Materials Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji University IFSA Collaborative Innovation Center Shanghai Jiao Tong University

An approach for studying the influence of nano-particles on the structural properties of deposited thin films is proposed. It is based on the molecular dynamic modeling of the deposition process in the presence of contaminating nano-particles. The nano-particle is assumed to be immobile and its interaction with film atoms is described by a spherically symmetric potential. The approach is applied to the investigation of properties of silicon dioxide films. Visualization tools are used to investigate the porosity associated with nano-particles. The structure of the film near the nano-particle is studied using the radial distribution function. It is found that fluctuations of film density near the nano-particles are essentially different in the cases of low-energy and high-energy deposition processes.

关键词： Influence Small-Size Properties

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An OFDM based interference reducing scheme with trajectory and resource optimization for UAV-powered IoT Networks

An OFDM based interference reducing scheme with trajectory a...

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General Assembly and Scientific Symposium, URSI

作者： Yuan Gao Jiang Cao Yang Guo Ping Wang Siming Yang Jing Wang Weidang Lu Peiyuan Si Ming Zhao Xiao Wu Academy of Military Science of the PLA China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China College of Information Engineering Zhejiang University of Technology Hangzhou China Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing China

The massive and pervasive deployment of sensors for information collecting in IoT networks result to the scarcity of energy. Unmanned aerial vehicle (UAV) enabled wireless power transfer (WPT) is a feasible solution to provide energy for pervasively deployed sensors. In this paper, we propose an orthogonal frequency division multiplexing (OFDM) based interference reducing scheme with trajectory and resource optimization for UAV-powered IoT networks. The simulation results show that our proposed scheme outperforms two benchmark schemes in sum transmission rate.

关键词： OFDM Simulation Interference Wireless power transfer Benchmark testing Unmanned aerial vehicles Trajectory

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Current switching of the antiferromagnetic Néel vector in Pd/CoO/MgO(001)

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Physical Review B 2022年第21期106卷 214405-214405页

作者： M. Yang Q. Li T. Wang B. Hong C. Klewe Z. Li X. Huang P. Shafer F. Zhang C. Hwang W. S. Yan R. Ramesh W. S. Zhao Y. Z. Wu Xixiang Zhang Z. Q. Qiu Institute of Physical Science and Information Technology Anhui University Hefei Anhui 230601 China National Synchrotron Radiation Laboratory University of Science and Technology of China Hefei Anhui 230029 China Department of Physics University of California Berkeley California 94720 USA Fert Beijing Research Institute School of Integrated Circuit Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Materials Science and Engineering University of California Berkeley California 94720 USA Korea Research Institute of Standards and Science Yuseong Daejeon 305-340 Korea Department of Physics State Key Laboratory of Surface Physics Fudan University Shanghai 200433 China Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia

Recently, the electrical switching of antiferromagnetic (AFM) order has been intensively investigated because of its application potential in data storage technology. Herein, we report the current switching of the AFM Néel vector in epitaxial Pd/CoO films as a function of temperature. Using combined measurements of Hall resistance (HR) and x-ray magnetic linear dichroism (XMLD) below and above the AFM Néel temperature, we unambiguously identified both magnetic and nonmagnetic contributions to the current-induced HR change. Through magnetic field-induced HR measurements, we quantitatively determined the percentage of current-induced CoO spin switching. Further, we showed that the thermal effect dominated the CoO magnetic switching more in samples with a thinner Pd layer and that samples with a thicker CoO layer required higher thermal activation for current-induced magnetic switching. These results provide a clear and comprehensive picture of current-induced AFM spin switching across the AFM Néel temperature.

关键词： Hall effect Magnetism Spintronics X-ray magnetic linear dichroism

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Efficient stego key recovery based on distribution differences of extracting message bits

Efficient stego key recovery based on distribution differenc...

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作者： Liu, Jiufen Gan, Junjun Wang, Junchao Xu, Che Luo, Xiangyang Zhengzhou Science and Technology Institute Zhengzhou450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

The extraction of embedded messages, i.e., extraction attacks are the ultimate purpose of steganalysis, with great practical significance to obtain covert communication content and covert communication forensics. For steganography using a stego key, the extraction attacks are equivalent to the stego key recovery. This paper mainly studies the methods of efficient stego key recovery for LSB steganography in JPEG domain. According to the distribution differences of extracting message bits generated by the correct and incorrect keys, stego key recovery is transformed into the hypothesis test of the message bits distribution extracted by the correct and incorrect keys. Firstly, by fitting the message bits distribution extracted by the correct key, a stego key recovery method based on nonparametric hypothesis test is proposed. Secondly, by utilizing the distribution differences between message bits extracted by the correct and incorrect keys, a stego key recovery method based on parametric hypothesis test is proposed. And then, formulas are given for calculating the sample size and threshold in the proposed stego key recovery model, on the basis of type I error and type II error. Experimental results show that the proposed method can successfully recover the stego key of OutGuess 0.13b, OutGuess0.2, JPEG domain random LSB matching steganography and random F3 steganography, the performance is superior to that of existing methods. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Extraction

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