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作者： Sun, Shiwen Xia, Chengyi Wang, Li School of Computer and Communication Engineering Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China

ISBN: (纸本)9789881725592

Large-scale software systems represent an important class of artificial complex systems, which can be investigated from the complex network perspective. Based on the collaboration network model, the collaboration relationships between header files from source code of large-scale computer software systems are explored. It has been found that the generated network displays a high degree of heterogeneity in connectivity. The structural heterogeneity also leads to network's another important feature - Robust yet fragile. That is the network displays an unexpected degree of robustness to random attack or disturbance, but is extremely vulnerable to intentional attack, i.e. to the removal of a few of highly connected nodes. These findings can help people to get a better understanding of the organizational principles and evolving mechanism of complex software systems. © 2011 Chinese Assoc of Automati.

关键词： Complex networks

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A new clustering strategy in ambulatory electrocardiogram waveform

A new clustering strategy in ambulatory electrocardiogram wa...

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2009 International Conference on Information engineering and Computer Science, ICIECS 2009

作者： Yu, Tian Zheng, Gang School of Computer and Communication Engineering Tianjin University of Technology China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300191 Tianjin China

ISBN: (纸本)9781424449941

Ambulatory electrocardiogram is used to record about 24 hours electrocardiogram waveform. The purpose is to find out the conspicuous variation in the recording data. A new strategy used to cluster the electrocardiogram waveform is presented in this paper. The aim of that is to obtain more accurate clustering results. After the controlled trial on MIT/BIH data, it can be safely concluded that the clustering result achieved by improved strategy can got more accurate than that by the traditional clustering algorithm. An average accuracy ratio is about 94.6%, 1.6% higher than k-means algorithm averagely and 1.3% higher than Simulated Annealing algorithm averagely. ©2009 IEEE.

关键词： Electrocardiograms

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Directed differential evolution based on directional derivative for numerical optimization problems

Directed differential evolution based on directional derivat...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Jun Zhang Wenjian Luo School of Computer Science and Technology University of Science and Technology Hefei Anhui China Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology Hefei Anhui China

Differential Evolution is one kind of Evolutionary Algorithms, which has been successfully applied to solve many optimization problems. In this paper, a directed differential mutation (DDM), which utilizes the directional derivative to decide a suitable search direction and a proper mutation step size, is proposed. It is merged into the classical DE to form a new algorithm, named directed differential evolution (DDE). The performance of the DDE is tested on 23 classical problems for numerical optimization. The experimental results demonstrate that the performance of the DDE outperforms the classical DE on most functions.

关键词： Optimization Vectors Equations Hybrid intelligent systems Algorithms Programming Maintenance engineering

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Mining important topological properties in large-scale computer software systems base on complex networks

Mining important topological properties in large-scale compu...

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World Congress on software engineering

作者： Sun, Shiwen Xia, Chengyi Wang, Li Wang, Lanying School of Computer and Communication Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China Periodical Department Hebei University Baoding China

ISBN: (纸本)9780769543031

Recently, large-scale computer software systems have attached a great deal of attention when they are regarded as complex networks composed of interacting units. In this paper, the collaboration relationships between header files in the source code of Linux kernels are analyzed by constructing a weighted File Collaboration Network(FCN): each node represents a header file, two nodes are connected if corresponding header files are both included in the same source file at least once, also the link weight is assigned to evaluate the intensity of co-inclusion of two header files. Through using appropriate non-weighted and weighted quantities, structural properties of FCNs are characterized and analyzed. The study of large-scale softwares from the viewpoint of complex networks can provide a better description of the organizational principles and evolving mechanism of complex software systems. © 2010 IEEE.

关键词： Complex networks

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Exploring the Role of Large Language Models in Cybersecurity: A Systematic Survey

arXiv

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arXiv 2025年

作者： Tian, Shuang Zhang, Tao Liu, Jiqiang Wang, Jiacheng Wu, Xuangou Zhu, Xiaoqiang Zhang, Ruichen Zhang, Weiting Yuan, Zhenhui Mao, Shiwen Kim, Dong In School of Software Engineering Beijing Jiaotong University Beijing100044 China School of Cyberspace Science and Technology Beijing Jiaotong University Beijing100044 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore School of Computer Science and Technology An hui Province Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui University of Technology Anhui243002 China College of Computing and Data Science Nanyang Technological University Singapore School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China School of Engineering University of Warwick CoventryCV4 7AL United Kingdom Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States Department of Electrical and Computer Engineering College of Information and Communication Engineering Sungkyunkwan University Suwon16419 Korea Republic of

—With the rapid development of technology and the acceleration of digitalisation, the frequency and complexity of cyber security threats are increasing. Traditional cybersecurity approaches, often based on static rules and predefined scenarios, are struggling to adapt to the rapidly evolving nature of modern cyberattacks. There is an urgent need for more adaptive and intelligent defence strategies. The emergence of Large Language Model (LLM) provides an innovative solution to cope with the increasingly severe cyber threats, and its potential in analysing complex attack patterns, predicting threats and assisting real-time response has attracted a lot of attention in the field of cybersecurity, and exploring how to effectively use LLM to defend against cyberattacks has become a hot topic in the current research field. This survey examines the applications of LLM from the perspective of the cyber attack lifecycle, focusing on the three phases of defense reconnaissance, foothold establishment, and lateral movement, and it analyzes the potential of LLMs in Cyber Threat Intelligence (CTI) tasks. Meanwhile, we investigate how LLM-based security solutions are deployed and applied in different network scenarios. It also summarizes the internal and external risk issues faced by LLM during its application. Finally, this survey also points out the facing risk issues and possible future research directions in this domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Cyber attacks

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Theoretical and empirical analyses of Evolutionary Negative Selection Algorithms for a combinational optimization problem

Theoretical and empirical analyses of Evolutionary Negative ...

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International Conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Xingxin Pei Wenjian Luo Nature Inspired Computation and Application Laboratory School of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China

Evolutionary Negative Selection Algorithms (ENSAs) could be regarded as hybrid algorithms of Evolutionary Algorithms (EAs) and Negative Selection Algorithms (NSAs). The average time complexity of ENSAs on combinational optimization problems has never been studied before. In this paper, the average time complexity of ENSAs on one combinational optimization problem is analyzed. The theoretical results demonstrate that, for the Two Max function, the ENSA with an appropriate matching threshold could perform better than the traditional (N+N) EA. Some simulation experiments on the combinational problem are also done, and the experimental results are consistent with theoretical results.

关键词： Algorithm design and analysis software algorithms Immune system Convergence Laboratories Computer applications Application software Computer science Evolutionary computation Biology computing

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A Clustering System for Gene Expression Data Based upon Genetic Programming and the HS-Model

A Clustering System for Gene Expression Data Based upon Gene...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Guiquan Liu Xiufang Jiang Lingyun Wen Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Cluster analysis is a major method to study gene function and gene regulation information for there is a lack of prior knowledge for gene data. Many clustering methods existed at present usually need manual operations or predetermined parameters, which are difficult for gene data. Besides, gene data possess their own characteristics, such as large scale, high-dimension, and noise. Therefore, a systematic clustering algorithm should be proposed to effectively deal with gene data. In this paper, a novel genetic programming (GP) clustering system for gene data based on hierarchical statistical model (HS-model) is proposed. And an appropriate fitness function is also proposed in this system. This clustering system can largely eliminate the infection of data scale and dimension. The proposed GP clustering system is applied to cluster the whole intact yeast gene data without dimensionality reduction. The experimental results indicate that the algorithm is highly efficient and can effectively deal with missing values in gene dataset

关键词： genetic programming cluster analysis missing value fitness function

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Extracting Qualitative States from Nonlinear Time Series Using Integration of Fuzzy c-Means and Hierarchical Clustering

Extracting Qualitative States from Nonlinear Time Series Usi...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Chenxi Shao Jinfeng Fan Xiaoping Chen Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui China

A novel method combined fuzzy c-means (FCM) and hierarchical agglomerative clustering (HAC) is presented to extract the qualitative states from reconstructed phase space by considering the dynamical relations of underlying nonlinear system. The qualitative state, in which all points have similar properties, is characterized by three measures, linear density, temporal reachability, and stable degree, which are defined as the criteria of merging subclasses. The time series sampled from a classic nonlinear system, Lorenz system, and electroencephalogram (EEG) signals are used to test this method. The results show that the qualitative states can be efficiently distinguished from these time series by the proposed method.

关键词： Space technology Nonlinear systems Clustering methods Fuzzy systems Merging Electroencephalography Chaotic communication Delay Computer science Laboratories

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A fast algorithm for finding community structure based on community closeness

A fast algorithm for finding community structure based on co...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Xiufang Jiang Guiquan Liu Zhiting Lin Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Recently, the characterization of community structures in complex networks has received a considerable amount of attentions. Effective identification of these communities or clusters is a general problem in the field of data mining. In this paper we present a /ast hierarchical agglomerative algorithm based on community closeness (FHACC) algorithm, for detecting community structure which is very efficient and faster than many other competing algorithms. FHACC tends to agglomerate such communities that share the most common vertices into larger ones. Its running time on a sparse network with n vertices and m edges is O(mk + mt), where k denotes the mean vertex degree, and t is the iteration times of community agglomeration in FHACC algorithm. The algorithm was tested on several real-world networks and proved to be high efficient and effective in community finding.

关键词： community structure complex network data mining community closeness

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A hormone based tracking strategy for wireless sensor network

A hormone based tracking strategy for wireless sensor networ...

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IEEE International Conference on Intelligent computing and Intelligent Systems (ICIS)

作者： Yipeng Zhang Haifeng You Xufa Wang Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology Hefei China

In this paper, we present a hormone based tracking strategy called Hormone based Activation (HA) for mobile target tracking in wireless sensor networks inspired by the bio-endocrine system. Hormone messages are used in sensor networks to coordinate sensor nodes for mobile target tracking in a self-adaptive way. Three kinds of hormones are introduced into sensor network for mobile target tracking: Base Hormone (BH),Wakeup Hormone (WH) and Sleep Hormone (SH).Based on different hormone messages, sensor nodes can choose to be asleep or awake in order to get good tracking results with less energy consumed. Comparative experiment shows that our strategy needs fewer nodes to wake up and has a much higher usage ratio of sensor nodes than other tracking strategies.

关键词： Biochemistry Wireless sensor networks Target tracking Biosensors Intelligent sensors Computer networks Mobile communication Sleep Energy efficiency communication system control

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