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When Software Security Meets Large Language Models:A Survey

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 317-334页

作者： Xiaogang Zhu Wei Zhou Qing-Long Han Wanlun Ma Sheng Wen Yang Xiang IEEE the School of Computer and Mathematical Sciences the University of Adelaide the School of Science Computing and Engineering Technologies Swinburne University of Technology

Software security poses substantial risks to our society because software has become part of our life. Numerous techniques have been proposed to resolve or mitigate the impact of software security issues. Among them, software testing and analysis are two of the critical methods, which significantly benefit from the advancements in deep learning technologies. Due to the successful use of deep learning in software security, recently,researchers have explored the potential of using large language models(LLMs) in this area. In this paper, we systematically review the results focusing on LLMs in software security. We analyze the topics of fuzzing, unit test, program repair, bug reproduction, data-driven bug detection, and bug triage. We deconstruct these techniques into several stages and analyze how LLMs can be used in the stages. We also discuss the future directions of using LLMs in software security, including the future directions for the existing use of LLMs and extensions from conventional deep learning research.

关键词： Large language models (LLMs) software analysis software security software testing

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The Security of Using Large Language Models:A Survey With Emphasis on ChatGPT

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 1-26页

作者： Wei Zhou Xiaogang Zhu Qing-Long Han Lin Li Xiao Chen Sheng Wen Yang Xiang the School of Science Computing and Engineering Technologies Swinburne University of Technology IEEE the School of Computer and Mathematical Sciences the University of Adelaide Adelaide the Faculty of Science and Engineering Southern Cross University the School of Information and Physical Sciences the University of Newcastle

ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.

关键词： Artificial intelligence (AI) ChatGPT large language models (LLMs) security

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Gender-Based Analysis of User Reactions to Facebook Posts

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Big Data Mining and Analytics 2024年第1期7卷 75-86页

作者： Yassine El Moudene Jaafar Idrais Rida El Abassi Abderrahim Sabour Mathematical Engineering and Computer Science Laboratory Faculty of SciencesIbn Zohr UniversityAgadir 8706Morocco Department of Computer Science Mathematical−High School of Technology Ibn Zohr UniversityAgadir 8706Morocco

Online Social Networks(OSNs)are based on the sharing of different types of information and on various interactions(comments,reactions,and sharing).One of these important actions is the emotional reaction to the *** diversity of reaction types available on Facebook(namely FB)enables users to express their feelings,and its traceability creates and enriches the users’emotional identity in the virtual *** paper is based on the analysis of 119875012 FB reactions(Like,Love,Haha,Wow,Sad,Angry,Thankful,and Pride)made at multiple levels(publications,comments,and sub-comments)to study and classify the users’emotional behavior,visualize the distribution of different types of reactions,and analyze the gender impact on emotion *** of these can be achieved by addressing these research questions:who reacts the most?Which emotion is the most expressed?

关键词： profiling knowledge extraction data mining emotion mining social media data crawling Facebook reactions gender

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AN ITERATIVE TWO-GRID METHOD FOR STRONGLY NONLINEAR ELLIPTIC BOUNDARY VALUE PROBLEMS

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Journal of Computational Mathematics 2025年第3期43卷 673-689页

作者： Jiajun Zhan Lei Yang Xiaoqing Xing Liuqiang Zhong School of Computer Science and Engineering Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao SAR 999078China School of Mathematical Sciences South China Normal UniversityGuangzhou 510631China

We design and analyze an iterative two-grid algorithm for the finite element discretizations of strongly nonlinear elliptic boundary value problems in this *** propose an iterative two-grid algorithm,in which a nonlinear problem is first solved on the coarse space,and then a symmetric positive definite problem is solved on the fine *** main contribution in this paper is to establish a first convergence analysis,which requires dealing with four coupled error estimates,for the iterative two-grid *** also present some numerical experiments to confirm the efficiency of the proposed algorithm.

关键词： Iterative two-grid method Convergence Strongly nonlinear elliptic problems

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Unmasking the Illusions: A Comprehensive Study on Deepfake Videos and Images 9

Unmasking the Illusions: A Comprehensive Study on Deepfake V...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Ranout, Ravikant Kumar, C.R.S. School of Computer Engineering And Mathematical Science Pune India

ISBN: (纸本)9798350394474

This research paper delves into the complex world of deepfakes, investigating recent advances in the creation and identification of synthetic content. It is becoming more important to comprehend the complex threats that deepfake technology presents to the credibility of digital media. This study deep dives into deepfake creation methods. We examine the toolbox of content manipulators, starting with early image-based alterations and moving on to more modern audio and video synthesis. The research sheds light on the technologies that allow for the misleading creation of synthetic material that seems very *** survey investigates the developments in deepfake detection tactics which complements the investigation of production methods. It delves at the history of forensic methods and how they have been augmented by machine learning algorithms that can differentiate between real and fake content. Given the never-ending back-and-forth between creators and detectors, the study takes a close look at the strengths, weaknesses, opportunities and threats of existing detection methods. The possible consequences for privacy, disinformation and society trust are illuminated as well as the ethical problems underlying deepfake technology. As the globe becomes more saturated with synthetic media our discussion moves on to examine the social and legal *** study seeks to provide a thorough overview of the synthetic reality world by combining the two viewpoints of deepfake creation and detection. Researchers, legislators and tech developers dealing with the serious consequences of deepfake technologies on digital content integrity and the information ecosystem as a whole will find this survey helpful because it outlines the present state-of-the-art as well as emerging trends. © 2024 IEEE.

关键词： Digital storage

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Impulse Synchronization Strategy of Nonlinear Finance Systems

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IAENG International Journal of Applied Mathematics 2024年第9期54卷 1814-1819页

作者： Peng, Yang Feng, Yuming School of Mathematical Physics Science Chongqing University of Science and Technology Chongqing401331 China School of Computer Science and Engineering Chongqing Three Gorges University Chongqing404020 China

In recent decades, impulse control has been increasingly applied as a discontinuous control method across diverse domains such as satellite orbit transfers, financial market regulation, chaos synchronization, and communication security. This paper investigates an impulse synchronization strategy specifically tailored for chaotic financial systems. We propose a novel strategy grounded in Lyapunov stability theory and the maximum Lyapunov exponent, designed to synchronize chaotic financial systems effectively. Simulation experiments are conducted to validate the efficacy of our proposed approach. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Lyapunov methods

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Auto-3D-house Design from Structured User Requirements

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Machine Intelligence Research 2025年第2期22卷 368-385页

作者： Minkui Tan Qi Chen Zixiong Huang Qi Wu Yuanqing Li Jiaqiu Zhou School of Software Engineering South China University of TechnologyGuangzhou 510006China Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide SA 5005Australia School of Automation Science and Engineering South China University of TechnologyGuangzhou 510006China

We study the task of automated house design,which aims to automatically generate 3D houses from user ***,in the automatic system,it is non-trivial due to the intrinsic complexity of house designing:1)the understanding of user requirements,where the users can hardly provide high-quality requirements without any professional knowledge;2)the design of house plan,which mainly focuses on how to capture the effective information from user *** address the above issues,we propose an automatic house design framework,called auto-3D-house design(A3HD).Unlike the previous works that consider the user requirements in an unstructured way(e.g.,natural language),we carefully design a structured list that divides the requirements into three parts(i.e.,layout,outline,and style),which focus on the attributes of rooms,the outline of the building,and the style of decoration,*** the processing of architects,we construct a bubble diagram(i.e.,graph)that covers the rooms′attributes and relations under the constraint of *** addition,we take each outline as a combination of points and orders,ensuring that it can represent the outlines with arbitrary ***,we propose a graph feature generation module(GFGM)to capture layout features from the bubble diagrams and an outline feature generation module(OFGM)for outline ***,we render 3D houses according to the given style requirements in a rule-based *** on two benchmark datasets(i.e.,RPLAN and T3HM)demonstrate the effectiveness of our A3HD in terms of both quantitative and qualitative evaluation metrics.

关键词： Automated house design user requirements understanding outline processing layout generation graph feature generation.

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Lexicon-based fine-tuning of multilingual language models for low-resource language sentiment analysis

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CAAI Transactions on Intelligence Technology 2024年第5期9卷 1116-1125页

作者： Vinura Dhananjaya Surangika Ranathunga Sanath Jayasena Department of Computer Science and Engineering University of MoratuwaMoratuwaSri Lanka School of Mathematical and Computational Sciences Massey UniversityPalmerston NorthNew Zealand

Pre-trained multilingual language models (PMLMs) such as mBERT and XLM-R have shown good cross-lingual transferability. However, they are not specifically trained to capture cross-lingual signals concerning sentiment words. This poses a disadvantage for low-resource languages (LRLs) that are under-represented in these models. To better fine-tune these models for sentiment classification in LRLs, a novel intermediate task fine-tuning (ITFT) technique based on a sentiment lexicon of a high-resource language (HRL) is introduced. The authors experiment with LRLs Sinhala, Tamil and Bengali for a 3-class sentiment classification task and show that this method outperforms vanilla fine-tuning of the PMLM. It also outperforms or is on-par with basic ITFT that relies on an HRL sentiment classification dataset.

关键词： deep learning natural languages natural language processing

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ANALYSIS OF TWO ANY ORDER SPECTRAL VOLUME METHODS FOR 1-D LINEAR HYPERBOLIC EQUATIONS WITH DEGENERATE VARIABLE COEFFICIENTS

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Journal of Computational Mathematics 2024年第6期42卷 1627-1655页

作者： Minqiang Xu Yanting Yuan Waixiang Cao Qingsong Zou College of Science Zhejiang University of TechnologyHangzhou 310023China School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510275China School of Mathematical Sciences Beijing Normal UniversityBeijing 100875China School of Computer Science and Engineering and Guangdong Province Key Laboratory of Computational ScienceSun Yat-sen UniversityGuangzhou 510275China

In this paper,we analyze two classes of spectral volume(SV)methods for one-dimensional hyperbolic equations with degenerate variable *** classes of SV methods are constructed by letting a piecewise k-th order(k≥1 is an integer)polynomial to satisfy the conservation law in each control volume,which is obtained by refining spectral volumes(SV)of the underlying mesh with k Gauss-Legendre points(LSV)or Radaus points(RSV)in each *** L^(2)-norm stability and optimal order convergence properties for both methods are rigorously proved for general non-uniform ***,we discover some very interesting superconvergence phenomena:At some special points,the SV flux function approximates the exact flux with(k+2)-th order and the SV solution itself approximates the exact solution with(k+3/2)-th order,some superconvergence behaviors for element averages errors have been also ***,these superconvergence phenomena are rigorously proved by using the so-called correction function *** theoretical findings are verified by several numerical experiments.

关键词： Spectral Volume Methods L^(2)stability Error estimates Superconvergence

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Electricity Cost Minimization for Multi-Workflow Allocation in Geo-Distributed Data Centers

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IEEE Transactions on Services Computing 2025年第03期18卷 1397-1411页

作者： Wang, Shuang Zhang, He Wu, Tianxing Zhang, Yueyou Zhang, Wei Emma Sheng, Quan Z. Southeast University School of Computer Science and Engineering Nanjing211189 China The University of Adelaide School of Computer and Mathematical Sciences Australian Institute for Machine Learning Australia Macquarie University School of Computing SydneyNSW2109 Australia

Worldwide, Geo-distributed Data Centers (GDCs) provide computing and storage services for massive workflow applications, resulting in high electricity costs that vary depending on geographical locations and time. How to reduce electricity costs while satisfying the deadline constraints of workflow applications is important in GDCs, which is determined by the execution time of servers, power, and electricity price. Determining the completion time of workflows with different server frequencies can be challenging, especially in scenarios with heterogeneous computing resources in GDCs. Moreover, the electricity price is also different in geographical locations and may change dynamically. To address these challenges, we develop a geo-distributed system architecture and propose an Electricity Cost aware Multiple Workflows Scheduling algorithm (ECMWS) for servers of GDCs with fixed frequency and power. ECMWS comprises four stages, namely workflow sequencing, deadline partitioning, task sequencing, and resource allocation where two graph embedding models and a policy network are constructed to solve the Markov Decision Process (MDP). After statistically calibrating parameters and algorithm components over a comprehensive set of workflow instances, the proposed algorithms are compared with the state-of-the-art methods over two types of workflow instances. The experimental results demonstrate that our proposed algorithm significantly outperforms other algorithms, achieving an improvement of over 15% while maintaining an acceptable computational time. The source codes are available at https://***/public-artifacts/ecmws-experiments. © 2025 IEEE.

关键词： Graph embeddings

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