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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Srish, N. Sridharan, S. Udhaya Kumar, S. Amrita School of Computing Computer Science Department Chennai India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354348

Call Data Records (CDR) are important evidence in cases involving cybercrime and crimes such as murder and robbery. Nonetheless, analyzing CDR is arduous work because the amount of data is enormous, and if a person does not know where to look, they would overlook valuable information. In today's world, officials do their best to solve crimes, but as the phrase goes, every piece of evidence counts, and CDR is no exception. This research investigates the many processes and techniques used in the analysis of CDR data, particularly in the context of telecommunications, including data analytics, pattern matching, geographical mapping, and visualization methods. Furthermore, the paper covers problems and prospects in CDR forensic analysis, emphasizing the importance of improved tools and approaches to deal with growing communication technologies and increasing cyber threats. © 2024 IEEE.

关键词： Crime

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Formal Modeling of Hybrid System Based on Semi-continuous Colored Petri Net: A Case Study of Adaptive Cruise Control System

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ACM Transactions on Embedded computing Systems 2025年第3期24卷 1-21页

作者： Yu, Wangyang Guo, Qi Cheng, Yumeng Liu, Lu Hao, Fei Zhai, Xiaojun Chen, Minsi The School of Computer Science Shaanxi Normal University Shaanxi Xi'an China The School of Computer Science Shaanxi Normal University Xi'an China University of Exeter Department of Computer Science Exeter United Kingdom University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom University of Huddersfield School of Computing and Engineering Huddersfield United Kingdom

Many Next-Generation consumer electronic devices would be distributed hybrid electronic systems, such as UAVs (Unmanned Aerial Vehicles) and smart electronic cars. The safety and risk control are the key issues for the sustainability of such consumer electronic systems. The modeling of hybrid electronic systems is difficult to be abstracted by traditional Petri Nets. This also makes the reachable marking graph unable to be applied to Petri Nets of the hybrid electronic systems. This paper proposes a novel Petri Net to model and analyze the hybrid electronic systems. We name it a Semi-continuous Colored Petri Net (SCPN) that inherits the excellent modeling capabilities and analysis methods of Petri Nets, and can formally depict hybrid quantities. In addition, we propose the construction algorithm for an SCPN reachable marking graph and prove its finiteness. Finally, we model and analyze an Adaptive Cruise Control (ACC) system of smart electronic cars as an example to prove the validity of SCPN. We use the proposed SCPN to model and analyze the running process of an ACC system under the continuous deceleration scenario of the front vehicle. The application study shows that the ACC system has logic flaws under the constant headway strategy when the front vehicle continues to decelerate. Based on this analysis, improvements to the SCPN of the ACC system are made, effectively enhancing its safety and logical correctness. Copyright © 2025 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Adaptive cruise control

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Incomplete Multi-View Clustering via Auto-Weighted Fusion in Partition Space

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Tsinghua science and Technology 2023年第3期28卷 595-611页

作者： Dongxue Xia Yan Yang Shuhong Yang School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China School of Computer Guangxi University of Science and TechnologyLiuzhou 545006China

As a class of effective methods for incomplete multi-view clustering,graph-based algorithms have recently drawn wide ***,most of them could use further improvement regarding the following ***,in some graph-based models,all views are forced to share a common similarity graph regardless of the severe consistency degeneration due to incomplete ***,similarity graph construction and cluster analysis are sometimes performed ***,the contribution difference of individual views is not always carefully *** address these issues simultaneously,this paper proposes an incomplete multi-view clustering algorithm based on auto-weighted fusion in partition *** our algorithm,the information of cluster structure is introduced into the process of similarity learning to construct a desirable similarity graph,information fusion is performed in partition space to alleviate the negative impact brought about by consistency degradation,and all views are adaptively weighted to reflect their different contributions to clustering ***,all the subtasks are collaboratively optimized in a united framework to reach an overall optimal *** results show that the proposed method compares favorably with the state-of-the-art methods.

关键词： Incomplete Multi-view Clustering(IMC) partition space auto-weighted fusion collaborative optimization

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Evolutionary Multi/Many-Objective Optimisation via Bilevel Decomposition

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1973-1986页

作者： Shouyong Jiang Jinglei Guo Yong Wang Shengxiang Yang School of Automation Central South UniversityChangsha 410083China Department of Computing Science University of AberdeenAberdeen AB243FXUK School of Computer Science Central China Normal UniversityWuhan 430079China School of Computer Science and Informatics De Montfort UniversityLeicester LE19BHUK

Decomposition of a complex multi-objective optimisation problem(MOP)to multiple simple subMOPs,known as M2M for short,is an effective approach to multi-objective ***,M2M facilitates little communication/collaboration between subMOPs,which limits its use in complex optimisation *** paper extends the M2M framework to develop a unified algorithm for both multi-objective and manyobjective *** bilevel decomposition,an MOP is divided into multiple subMOPs at upper level,each of which is further divided into a number of single-objective subproblems at lower *** subMOPs are allowed to share some subproblems so that the knowledge gained from solving one subMOP can be transferred to another,and eventually to all the *** bilevel decomposition is readily combined with some new mating selection and population update strategies,leading to a high-performance algorithm that competes effectively against a number of state-of-the-arts studied in this paper for both multiand many-objective *** analysis and component analysis have been also carried out to further justify the proposed algorithm.

关键词： Bilevel decomposition evolutionary algorithm many-objective optimisation multi-objective optimisation

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Real-Time Speech Enhancement Based on Convolutional Recurrent Neural Network

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Intelligent Automation & Soft computing 2023年第2期35卷 1987-2001页

作者： S.Girirajan A.Pandian Department of Computer Science and Engineering School of ComputingSRM Institute of Science and EngineeringKattankulathurTamil NaduIndia

Speech enhancement is the task of taking a noisy speech input and pro-ducing an enhanced speech *** recent years,the need for speech enhance-ment has been increased due to challenges that occurred in various applications such as hearing aids,Automatic Speech Recognition(ASR),and mobile speech communication *** of the Speech Enhancement research work has been carried out for English,Chinese,and other European *** a few research works involve speech enhancement in Indian regional *** this paper,we propose a two-fold architecture to perform speech enhancement for Tamil speech signal based on convolutional recurrent neural network(CRN)that addresses the speech enhancement in a real-time single channel or track of sound created by the *** theﬁrst stage mask based long short-term mem-ory(LSTM)is used for noise suppression along with loss function and in the sec-ond stage,Convolutional Encoder-Decoder(CED)is used for speech *** proposed model is evaluated on various speaker and noisy environments like Babble noise,car noise,and white Gaussian *** proposed CRN model improves speech quality by 0.1 points when compared with the LSTM base model and also CRN requires fewer parameters for *** performance of the pro-posed model is outstanding even in low Signal to Noise Ratio(SNR).

关键词： Speech enhancement convolutional encoder-decoder long short-term memory noise suppression speech restoration

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MalAware: A tabletop exercise for malware security awareness education and incident response training

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 280-292页

作者： Angafor, Giddeon Yevseyeva, Iryna Maglaras, Leandros School of Computer Science and Informatics De Montfort University Leicester United Kingdom School of Computing Edinburgh Napier University Edinburgh United Kingdom

Advancements in technology, including the Internet of Things (IoT) revolution, have enabled individuals and businesses to use systems and devices that connect, exchange data, and provide real-time information from far and near. Despite that, this interconnectivity and data sharing between systems and devices over the internet poses security and privacy risks as threat actors can intercept, steal, and use owners’ data for nefarious purposes. This paper discusses ’MalAware’, a ‘Malware Awareness Education’ and incident response (IR) scenario-based tabletop exercise and card game for malware threat mitigation training. It introduces the importance of incident management, highlights the dangers posed by malware for connected systems, and outlines the role of tabletop games and exercises in helping businesses mature their malware incident response capabilities. The study discusses the design of MalAware and summarises the results of 2 pilots undertaken to assess the concept, maintaining that the results highlighted the value of ‘MalAware’ as an essential tool to help students and staff master how to mitigate security threats caused by malware. It argues that MalAware can assist businesses in their IR preparedness endeavors, enabling incident management teams to review plans and processes to ensure they are fit for purpose. It enables staff to leverage scenario-based and simulated security breach examples, including role-play, to establish appropriate malware defences. MalAware's practical hands-on exercises can assist trainees in gaining essential malware and other threat mitigation skills, helping to protect the security and privacy of IoTs. © 2024 The Authors

关键词： Malware

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Resource investment for DDoS attack resistant SDN: a practical assessment

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science China(Information sciences) 2023年第7期66卷 112-129页

作者： Bin YUAN Fan ZHANG Jun WAN Huan ZHAO Shui YU Deqing ZOU Qiangsheng HUA Hai JIN School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security Shenzhen Huazhong University of Science and Technology Research Institute School of Computer Science and Technology Huazhong University of Science and Technology Cluster and Grid Computing Lab School of Computer Science University of Technology Sydney

Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of service(DDoS) attack, which aims to drain the resources of SDN switches and controllers,is one of the most common. Once the switch or controller is damaged, the network services can be *** defense schemes against DDoS attacks have been proposed from the perspective of attack detection;however, such defense schemes are known to suffer from a time consuming and unpromising accuracy, which could result in an unavailable network service before specific countermeasures are taken. To address this issue through a systematic investigation, we propose an elaborate resource-management mechanism against DDoS attacks in an SDN. Specifically, by considering the SDN topology, we leverage the M/M/c queuing model to measure the resistance of an SDN to DDoS attacks. Network administrators can therefore invest a reasonable number of resources into SDN switches and SDN controllers to defend against DDoS attacks while guaranteeing the quality of service(QoS). Comprehensive analyses and empirical data-based experiments demonstrate the effectiveness of the proposed approach.

关键词： SDN security DDoS attacks resource management queueing theory QoS

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A novel feature selection approach with integrated feature sensitivity and feature correlation for improved prediction of heart disease

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Journal of Ambient Intelligence and Humanized computing 2023年第9期14卷 12005-12019页

作者： Saranya, G. Pravin, A. Department of Computer Science and Engineering School of Computing Sathyabama Institute of Science and Technology Chennai600119 India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Chennai603203 India

This paper presents a random forest-feature sensitivity and feature correlation (RF-FSFC) technique for enhanced heart disease prediction. The proposed methodology is implemented using the Cleveland heart disease dataset which comprises a total of 120 heart disease patient records. Data imputation was utilized for missing values, and min–max normalization was utilized for data transformation. We attempted to construct an RF-based classifier for coronary heart disease in this paper by combining feature sensitivity and correlation analysis. The sensitivity-based feature selection process ranks features according to their value in assessing CHD risk, and the feature correlation analysis phase analyses if there are any correlations between features. The heart disease prediction accuracy of 81.16% was obtained using the proposed RF-FSFCA technique by omitting five features (sex, hemoglobin, TD, CRF, and cirrhosis). When compared to the Naïve Bayes, decision tree, regression analysis, and support vector machine models, the proposed model offered a higher accuracy of 86.141% without omitting any features. It also offered sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) scores of 87.321%, 87.364%, 91.23, and 91.02 respectively. Experiment findings demonstrated that the proposed RF-FSFC approach significantly improves prediction accuracy as compared to other approaches that do not use the integrated Feature selection method. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Sensitivity analysis

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TRS Scheduling for Improved QoS Performance in Cloud System

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computers, Materials & Continua 2023年第4期75卷 1547-1559页

作者： G.John Samuel Babu M.Baskar Department of Computer Science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India Department of Computing Technologies School of ComputingCollege of Engineering andTechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India

Numerous methods are analysed in detail to improve task schedulingand data security performance in the cloud environment. The methodsinvolve scheduling according to the factors like makespan, waiting time,cost, deadline, and popularity. However, the methods are inappropriate forachieving higher scheduling performance. Regarding data security, existingmethods use various encryption schemes but introduce significant serviceinterruption. This article sketches a practical Real-time Application CentricTRS (Throughput-Resource utilization–Success) Scheduling with Data Security(RATRSDS) model by considering all these issues in task scheduling anddata security. The method identifies the required resource and their claim timeby receiving the service requests. Further, for the list of resources as services,the method computes throughput support (Thrs) according to the number ofstatements executed and the complete statements of the service. Similarly, themethod computes Resource utilization support (Ruts) according to the idletime on any duty cycle and total servicing time. Also, the method computesthe value of Success support (Sus) according to the number of completions forthe number of allocations. The method estimates the TRS score (ThroughputResource utilization Success) for different resources using all these supportmeasures. According to the value of the TRS score, the services are rankedand scheduled. On the other side, based on the requirement of service requests,the method computes Requirement Support (RS). The selection of service isperformed and allocated. Similarly, choosing the route according to the RouteSupport Measure (RSM) enforced route security. Finally, data security hasgets implemented with a service-based encryption technique. The RATRSDSscheme has claimed higher performance in data security and scheduling.

关键词： Cloud task scheduling TRS quality of service RSM route security data security SDE RATRSDS

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Feature analysis of fake news: improving fake news detection in social media

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Journal of Cyber Security Technology 2023年第4期7卷 224-241页

作者： Leung, Johnathan Vatsalan, Dinusha Arachchilage, Nalin The School of Computer Science The University of Auckland Auckland New Zealand The School of Computing Macquarie University Sydney Australia

Fake news is a threat to society, and its spread can have real-world consequences in many situations. For example, attackers have weaponised fake news to influence user opinion by causing users to emotionally react to fake news. On the other hand, fake news can also be a threat to national democracy. Therefore, we investigate textual sentiment, visual sentiment, behavioural and metadata features that entice users, using a dataset of posts from Reddit and another from Twitter, that were already categorised into the labels of fake news and real news. First, we extract features, such as visual sentiment, textual sentiment, behavioural reactions, and metadata, and then analyse various features for fake news prediction. We then run a machine learning experiment to classify posts that help improve fake news detection in social media. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Metadata

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