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GRATDet:Smart Contract Vulnerability Detector Based on Graph Representation and Transformer

Computers, Materials & Continua 2023年第8期76卷 1439-1462页

作者： Peng Gong Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Information science and Engineering Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur autonomous region Xinjiang UniversityUrumqi830000China Key Laboratory of Multilingual Information technology in Xinjiang Uygur autonomous region Xinjiang UniversityUrumqi830000China

Smart contracts have led to more efficient development in finance and healthcare,but vulnerabilities in contracts pose high risks to their future *** current vulnerability detection methods for contracts are either based on fixed expert rules,which are inefficient,or rely on simplistic deep learning techniques that do not fully leverage contract semantic ***,there is ample room for improvement in terms of detection *** solve these problems,this paper proposes a vulnerability detector based on deep learning techniques,graph representation,and Transformer,called *** method first performs swapping,insertion,and symbolization operations for contract functions,increasing the amount of small sample *** line of code is then treated as a basic semantic element,and information such as control and data relationships is extracted to construct a new representation in the form of a Line Graph(LG),which shows more structural features that differ from the serialized presentation of the ***,the node information and edge information of the graph are jointly learned using an improved Transformer-GP model to extract information globally and locally,and the fused features are used for vulnerability *** effectiveness of the method in reentrancy vulnerability detection is verified in experiments,where the F1 score reaches 95.16%,exceeding stateof-the-art methods.

关键词： Vulnerability detection smart contract graph representation deep learning source code

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DFE-GCN: Dual Feature Enhanced Graph Convolutional Network for Controversy Detection

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Computers, Materials & Continua 2023年第10期77卷 893-909页

作者： Chengfei Hua Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Software Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur autonomous region Xinjiang UniversityUrumqi830000China Key Laboratory of Multilingual Information technology in Xinjiang Uygur autonomous region Xinjiang UniversityUrumqi830000China

With the development of social media and the prevalence of mobile devices,an increasing number of people tend to use social media platforms to express their opinions and attitudes,leading to many online *** online controversies can severely threaten social stability,making automatic detection of controversies particularly *** controversy detection methods currently focus on mining features from text semantics and propagation ***,these methods have two drawbacks:1)limited ability to capture structural features and failure to learn deeper structural features,and 2)neglecting the influence of topic information and ineffective utilization of topic *** light of these phenomena,this paper proposes a social media controversy detection method called Dual Feature Enhanced Graph Convolutional Network(DFE-GCN).This method explores structural information at different scales from global and local perspectives to capture deeper structural features,enhancing the expressive power of structural ***,to strengthen the influence of topic information,this paper utilizes attention mechanisms to enhance topic features after each graph convolutional layer,effectively using topic *** validated our method on two different public datasets,and the experimental results demonstrate that our method achieves state-of-the-art performance compared to baseline *** the Weibo and Reddit datasets,the accuracy is improved by 5.92%and 3.32%,respectively,and the F1 score is improved by 1.99%and 2.17%,demonstrating the positive impact of enhanced structural features and topic features on controversy detection.

关键词： Controversy detection graph convolutional network feature enhancement social media

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The Detection of Fraudulent Smart Contracts Based on ECA-EfficientNet and Data Enhancement

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Computers, Materials & Continua 2023年第12期77卷 4073-4087页

作者： Xuanchen Zhou Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao College of Software Xinjiang UniversityUrumqi830000China Key Laboratory of Signal Detection and Processing in Xinjiang Uygur autonomous region Urumqi830000China Key Laboratory of Multilingual Information technology in Xinjiang Uygur autonomous region Urumqi830000China

With the increasing popularity of Ethereum,smart contracts have become a prime target for fraudulent activities such as Ponzi,honeypot,gambling,and phishing *** some researchers have studied intelligent fraud detection,most research has focused on identifying Ponzi contracts,with little attention given to detecting and preventing gambling or phishing *** are three main issues with current ***,there exists a severe data imbalance between fraudulent and non-fraudulent ***,the existing detection methods rely on diverse raw features that may not generalize well in identifying various classes of fraudulent ***,most prior studies have used contract source code as raw features,but many smart contracts only exist in *** address these issues,we propose a fraud detection method that utilizes Efficient Channel Attention EfficientNet(ECA-EfficientNet)and data *** method begins by converting bytecode into Red Green Blue(RGB)three-channel images and then applying channel exchange data *** then use the enhanced ECA-EfficientNet approach to classify fraudulent smart contract RGB *** proposed method achieves high F1-score and Recall on both publicly available Ponzi datasets and self-built multi-classification datasets that include Ponzi,honeypot,gambling,and phishing smart *** results of the experiments demonstrate that our model outperforms current methods and their variants in Ponzi contract *** research addresses a significant problem in smart contract security and offers an effective and efficient solution for detecting fraudulent contracts.

关键词： Fraud detection smart contract ECA-EfficientNet Ethereum

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Single-pulse Emissions of PSRs J1611-0114 and J1617+1123

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Research in Astronomy and Astrophysics 2024年第11期24卷 1-10页

作者： Shifang Liu Zhigang Wen Shuangqiang Wang Feifei Kou Wenming Yan Jianping Yuan Qingdong Wu De Zhao Chenchen Miao Na Wang Menyao Xue Di Li Pei Wang Shengnan Sun Weiwei Zhu Juntao Bai School of Physics and technology Xinjiang UniversityUrumqi 830046China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830046China University of Chinese Academy of sciences Beijing 100049China Xinjiang Key Laboratory of Radio Astrophysics Urumqi 830046China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Department of Astronomy Tsinghua UniversityBeijing 100084China

In this paper,the emissions from two pulsars,PSRs J1611-0114 and J1617+1123,were investigated using th Five-hundred-meter Aperture Spherical radio Telescope operating at a central frequency of 1250 *** average pulse profile of PSR J1611-0114 shows two components,the first of which is relatively weak in intensity The two-dimensional pulse stack exhibits an obvious nulling phenomenon,with an estimated nulling fraction o40.1%±5.4%.The durations of the nulls and bursts are consistent with power-law distributions,and no periodi nulling phenomenon is *** results from PSR J1617+1123 demonstrate that the average pulse profile i composed of four *** peak intensity of the fourth component varies significantly,causing an unstabl integrated *** addition,the modulation characteristics of J1611-0114 and J1617+1123 were studied by analyzing the modulation index,longitude resolved fluctuation spectrum and two-dimensional fluctuation spectrum using the software *** was found that the two pulsars exhibit intensity *** particular,J1611-0114 displays even-odd modulation,with the modulation period of approximately two *** modulation period of J1617+1123 is relatively *** is an obvious subpulse drift phenomenon,and the value of P_(2)i~0.125c/P_(0),corresponding to 12 pulse longitude bins,and the drift rate(P_(2)/P_(3))is about 0.29.

关键词： stars neutron-(stars:)pulsars general-(stars:)pulsars individual(PSRs J1611-0114 and J1617+1123)

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The Bright Single Pulse Emission from PSR B1133+16

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Research in Astronomy and Astrophysics 2024年第4期24卷 253-261页

作者： Jun Tan Zhi-Gang Wen Zhen Wang Xue-Feng Duan Hong-Guang Wang Na Wang Vishal Gajjar Jian-Ping Yuan Rai Yuen Wen-Ming Yan Jian-Ling Chen Wei Han Hui Wang Cheng-Bing Lyu Ai-Jun Dong Maths and Information technology School Yuncheng UniversityYuncheng 044000China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China Xinjiang Key Laboratory of Radio Astrophysics Urumqi 830011China School of Physics and Materials science Guangzhou UniversityGuangzhou 510006China Space science Laboratory University of CaliforniaBerkeley 94710USA Department of Physics and Electronic Engineering Yuncheng UniversityYuncheng 044000China School of Physics and Electronic science Guizhou Normal UniversityGuiyang 550025China

We have conducted a comprehensive investigation into the bright single pulse emission from PSR B1133+16using the Giant Metrewave Radio *** time resolution data(61μs)were obtained at a center frequency of 322 MHz with a bandwidth of 32 MHz over a continuous observation period of 7.45 hr.A total of 1082 bright pulses were sporadically detected with peak flux densities ranging from 10 to 23 times stronger than the average pulse ***,no giant pulse-like emission with a relative pulse energy larger than 10 and extremely short duration was detected,indicating that these bright pulses cannot be categorized as giant pulse *** majority of these bright pulses are concentrated in pulse phases at both the leading and trailing windows of the average pulse profile,with an occurrence ratio of approximately *** pulse energy distribution for all individual pulses can be described by a combination of two Gaussian components and a cutoff power-law with an index of α=-*** updated nulling fraction of 15.35%±0.45% was determined from the energy *** emission of individual pulses follows a log-normal distribution in peak flux density *** is imperative that regular phase drifting in bright pulse sequence is identified in both the leading and trailing components for the first *** physical mechanisms are discussed in detail to provide insights into these observations.

关键词： (stars:)pulsars:general (stars:)pulsars:individual(PSR B1133+16) methods:observational methods:data analysis

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Reciprocating Magnetic Fields in the Pulsar Wind Observed from the Black Widow Pulsar J1720-0534

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Research in Astronomy and Astrophysics 2023年第10期23卷 255-266页

作者： Chen-Chen Miao Victoria Blackmon Wei-Wei Zhu Dong-Zi Li Ming-Yu Ge Xiao-Peng You Maura McLaughlin Di Li Na Wang Pei Wang Jia-Rui Niu M.Cruces Jian-Ping Yuan Jun-Tao Bai D.J.Champion Yu-Tong Chen Ming-Min Chi P.C.C.Freire Yi Feng Zhen-Ye Gan M.Kramer Fei-Fei Kou Yu-Xi Li Xue-Li Miao Ling-Qi Meng Chen-Hui Niu Sheng-Nan Sun Zhong-Yi Sun H.M.Tedila Shuang-Qiang Wang Qing-Dong Wu Jing-Bo Wang Zhi-Gang Wen Shen Wang Ya-Biao Wang Cheng-Jie Wang Meng-Yao Xue You-Ling Yue Mao Yuan Ju-Mei Yao Wen-Ming Yan Ru-Shuang Zhao Lei Zhang De Zhao National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Astronomy and Space science University of Chinese Academy of SciencesBeijing 100049China West Virginia University 1500 University AveMorgantownWV 26506USA Institute for Frontiers in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China Cahill Center for Astronomy and Astrophysics California Institute of Technology1216 E California BoulevardPasadenaCA 91125USA Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China School of Physical science and technology Southwest UniversityChongqing 400715China Research Center for Intelligent Computing Platforms Zhejiang LaboratoryHangzhou 311100China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China Max-Planck Institut für Radioastronomie Auf dem Hügel 69D-53121 BonnGermany School of Computer science Fudan UniversityShanghai 200433China Tencent Youtu Lab Shanghai 200233China College of Physical science and technology Central China Normal UniversityWuhan 430079China Institute of Optoelectronic technology Lishui UniversityLishui 323000China Guizhou Normal University Guiyang 550001China

We report the radio observations of the eclipsing black widow pulsar J1720-0534, a 3.26 ms pulsar in orbit with a low mass companion of mass 0.029 to 0.034 M⊙. We obtain the phase-connected timing ephemeris and polarization profile of this millisecond pulsar(MSP) using the Five-hundred-meter Aperture Spherical radio Telescope(FAST), the Green Bank Telescope(GBT), and the Parkes Telescope. For the first time from such a system, an oscillatory polarization angle change was observed from a particular eclipse egress with partial depolarization, indicating 10-milliGauss-level reciprocating magnetic fields oscillating in a length scale of 5 ×10^(3)km(assuming an orbital inclination angle of 90°) outside the companion's magnetosphere. The dispersion measure variation observed during the ingresses and egresses shows the rapid raising of the electron density in the shock boundary between the companion's magnetosphere and the surrounding pulsar wind. We suggest that the observed oscillatory magnetic fields originate from the pulsar wind outside the companion's magnetosphere.

关键词： (stars:)pulsars:general (stars:)pulsars:individual(J1720-0534) (stars:)binaries:eclipsing

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