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  • Open Access

    ARTICLE

    IoT-Based Women Safety Gadgets (WSG): Vision, Architecture, and Design Trends

    Sharad Saxena1, Shailendra Mishra2,*, Mohammed Baljon2,*, Shamiksha Mishra3, Sunil Kumar Sharma2, Prakhar Goel1, Shubham Gupta1, Vinay Kishore1

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1027-1045, 2023, DOI:10.32604/cmc.2023.039677

    Abstract In recent years, the growth of female employees in the commercial market and industries has increased. As a result, some people think travelling to distant and isolated locations during odd hours generates new threats to women’s safety. The exponential increase in assaults and attacks on women, on the other hand, is posing a threat to women’s growth, development, and security. At the time of the attack, it appears the women were immobilized and needed immediate support. Only self-defense isn’t sufficient against abuse; a new technological solution is desired and can be used as quickly as hitting a switch or button.… More >

  • Open Access

    ARTICLE

    Dis-NDVW: Distributed Network Asset Detection and Vulnerability Warning Platform

    Leilei Li1, Yansong Wang2, Dongjie Zhu2,*, Xiaofang Li3, Haiwen Du4, Yixuan Lu2, Rongning Qu3, Russell Higgs5

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 771-791, 2023, DOI:10.32604/cmc.2023.038268

    Abstract With the rapid development of Internet technology, the issues of network asset detection and vulnerability warning have become hot topics of concern in the industry. However, most existing detection tools operate in a single-node mode and cannot parallelly process large-scale tasks, which cannot meet the current needs of the industry. To address the above issues, this paper proposes a distributed network asset detection and vulnerability warning platform (Dis-NDVW) based on distributed systems and multiple detection tools. Specifically, this paper proposes a distributed message subscription and publication system based on Zookeeper and Kafka, which endows Dis-NDVW with the ability to parallelly… More >

  • Open Access

    ARTICLE

    A Model Training Method for DDoS Detection Using CTGAN under 5GC Traffic

    Yea-Sul Kim1, Ye-Eun Kim1, Hwankuk Kim2,*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1125-1147, 2023, DOI:10.32604/csse.2023.039550

    Abstract With the commercialization of 5th-generation mobile communications (5G) networks, a large-scale internet of things (IoT) environment is being built. Security is becoming increasingly crucial in 5G network environments due to the growing risk of various distributed denial of service (DDoS) attacks across vast IoT devices. Recently, research on automated intrusion detection using machine learning (ML) for 5G environments has been actively conducted. However, 5G traffic has insufficient data due to privacy protection problems and imbalance problems with significantly fewer attack data. If this data is used to train an ML model, it will likely suffer from generalization errors due to… More >

  • Open Access

    ARTICLE

    Network Security Situation Prediction Based on TCAN-BiGRU Optimized by SSA and IQPSO

    Junfeng Sun1, Chenghai Li1, Yafei Song1,*, Peng Ni2, Jian Wang1

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 993-1021, 2023, DOI:10.32604/csse.2023.039215

    Abstract The accuracy of historical situation values is required for traditional network security situation prediction (NSSP). There are discrepancies in the correlation and weighting of the various network security elements. To solve these problems, a combined prediction model based on the temporal convolution attention network (TCAN) and bi-directional gate recurrent unit (BiGRU) network is proposed, which is optimized by singular spectrum analysis (SSA) and improved quantum particle swarm optimization algorithm (IQPSO). This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data. Furthermore, a prediction model of TCAN-BiGRU… More >

  • Open Access

    ARTICLE

    Machine Learning Based Cybersecurity Threat Detection for Secure IoT Assisted Cloud Environment

    Z. Faizal Khan1, Saeed M. Alshahrani2,*, Abdulrahman Alghamdi2, Someah Alangari3, Nouf Ibrahim Altamami4, Khalid A. Alissa5, Sana Alazwari6, Mesfer Al Duhayyim7, Fahd N. Al-Wesabi8

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 855-871, 2023, DOI:10.32604/csse.2023.036735

    Abstract The Internet of Things (IoT) is determine enormous economic openings for industries and allow stimulating innovation which obtain between domains in childcare for eldercare, in health service to energy, and in developed to transport. Cybersecurity develops a difficult problem in IoT platform whereas the presence of cyber-attack requires that solved. The progress of automatic devices for cyber-attack classifier and detection employing Artificial Intelligence (AI) and Machine Learning (ML) devices are crucial fact to realize security in IoT platform. It can be required for minimizing the issues of security based on IoT devices efficiently. Thus, this research proposal establishes novel mayfly… More >

  • Open Access

    ARTICLE

    An Interoperability Cross-Block Chain Framework for Secure Transactions in IoT

    N. Anand Kumar1,*, A. Grace Selvarani2, P. Vivekanandan3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1077-1090, 2023, DOI:10.32604/csse.2023.034115

    Abstract The purpose of this research is to deal with effective block chain framework for secure transactions. The rate of effective data transactions and the interoperability of the ledger are the two major obstacles involved in Blockchain and to tackle this issue, Cross-Chain based Transaction (CCT) is introduced. Traditional industries have been restructured by the introduction of Internet of Things (IoT) to become smart industries through the feature of data-driven decision-making. Still, there are a few limitations, like decentralization, security vulnerabilities, poor interoperability, as well as privacy concerns in IoTs. To overcome this limitation, Blockchain has been employed to assure a… More >

  • Open Access

    ARTICLE

    A Cross Language Code Security Audit Framework Based on Normalized Representation

    Yong Chen1,*, Chao Xu1, Jing Selena He2, Sheng Xiao3

    Journal of Quantum Computing, Vol.4, No.2, pp. 75-84, 2022, DOI:10.32604/jqc.2022.031312

    Abstract With the rapid development of information technology, audit objects and audit itself are more and more inseparable from software. As an important means of software security audit, code security audit will become an important aspect of future audit that cannot be ignored. However, the existing code security audit is mainly based on source code, which is difficult to meet the audit needs of more and more programming languages and binary commercial software. Based on the idea of normalized transformation, this paper constructs a cross language code security audit framework (CLCSA). CLCSA first uses compile/decompile technology to convert different high-level programming… More >

  • Open Access

    ARTICLE

    Spatial Multi-Presence System to Increase Security Awareness for Remote Collaboration in an Extended Reality Environment

    Jun Lee1, Hyun Kwon2,*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 369-384, 2023, DOI:10.32604/iasc.2023.036052

    Abstract Enhancing the sense of presence of participants is an important issue in terms of security awareness for remote collaboration in extended reality. However, conventional methods are insufficient to be aware of remote situations and to search for and control remote workspaces. This study proposes a spatial multi-presence system that simultaneously provides multiple spaces while rapidly exploring these spaces as users perform collaborative work in an extended reality environment. The proposed system provides methods for arranging and manipulating remote and personal spaces by creating an annular screen that is invisible to the user. The user can freely arrange remote participants and… More >

  • Open Access

    ARTICLE

    Intrusion Detection System Through Deep Learning in Routing MANET Networks

    Zainab Ali Abbood1,2,*, Doğu Çağdaş Atilla3,4, Çağatay Aydin5

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 269-281, 2023, DOI:10.32604/iasc.2023.035276

    Abstract Deep learning (DL) is a subdivision of machine learning (ML) that employs numerous algorithms, each of which provides various explanations of the data it consumes; mobile ad-hoc networks (MANET) are growing in prominence. For reasons including node mobility, due to MANET’s potential to provide small-cost solutions for real-world contact challenges, decentralized management, and restricted bandwidth, MANETs are more vulnerable to security threats. When protecting MANETs from attack, encryption and authentication schemes have their limits. However, deep learning (DL) approaches in intrusion detection systems (IDS) can adapt to the changing environment of MANETs and allow a system to make intrusion decisions… More >

  • Open Access

    ARTICLE

    Multi-Attack Intrusion Detection System for Software-Defined Internet of Things Network

    Tarcízio Ferrão1,*, Franklin Manene2, Adeyemi Abel Ajibesin3

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4985-5007, 2023, DOI:10.32604/cmc.2023.038276

    Abstract Currently, the Internet of Things (IoT) is revolutionizing communication technology by facilitating the sharing of information between different physical devices connected to a network. To improve control, customization, flexibility, and reduce network maintenance costs, a new Software-Defined Network (SDN) technology must be used in this infrastructure. Despite the various advantages of combining SDN and IoT, this environment is more vulnerable to various attacks due to the centralization of control. Most methods to ensure IoT security are designed to detect Distributed Denial-of-Service (DDoS) attacks, but they often lack mechanisms to mitigate their severity. This paper proposes a Multi-Attack Intrusion Detection System… More >

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