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  • Open Access


    Deep Learning-Based Swot Analysis in Construction and Demolition Waste Management

    R. Rema*, N. Nalanth

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1497-1506, 2023, DOI:10.32604/iasc.2023.032540

    Abstract Researchers worldwide have employed a varied array of sources to calculate the successful management of Construction and Demolition (C&DW). Limited research has been undertaken in the domain of Construction and Demolition Waste Management (C&DWM) and consequently leaving a large gap in the availability of effective management techniques. Due to the limited time available for building removal and materials collection, preparing for building materials reuse at the end of life is frequently a challenging task. In this research work Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) is proposed to predict the number of waste materials that are obtained from a building at… More >

  • Open Access


    A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

    R. T. Pavendan1,*, K. Sankar1, K. A. Varun Kumar2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3331-3348, 2023, DOI:10.32604/iasc.2023.028029

    Abstract Attacks on the cyber space is getting exponential in recent times. Illegal penetrations and breaches are real threats to the individuals and organizations. Conventional security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats (APTs) they fails. These APTs are targeted, more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing defenses. Hence, there is a need for an effective defense system that can achieve a complete reliance of security. To address the above-mentioned issues, this paper proposes a novel honeypot system that tracks the anonymous behavior… More >

  • Open Access


    Automated Machine Learning Enabled Cybersecurity Threat Detection in Internet of Things Environment

    Fadwa Alrowais1, Sami Althahabi2, Saud S. Alotaibi3, Abdullah Mohamed4, Manar Ahmed Hamza5,*, Radwa Marzouk6

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 687-700, 2023, DOI:10.32604/csse.2023.030188

    Abstract Recently, Internet of Things (IoT) devices produces massive quantity of data from distinct sources that get transmitted over public networks. Cybersecurity becomes a challenging issue in the IoT environment where the existence of cyber threats needs to be resolved. The development of automated tools for cyber threat detection and classification using machine learning (ML) and artificial intelligence (AI) tools become essential to accomplish security in the IoT environment. It is needed to minimize security issues related to IoT gadgets effectively. Therefore, this article introduces a new Mayfly optimization (MFO) with regularized extreme learning machine (RELM) model, named MFO-RELM for Cybersecurity… More >

  • Open Access


    Advanced Authentication Mechanisms for Identity and Access Management in Cloud Computing

    Amjad Alsirhani, Mohamed Ezz, Ayman Mohamed Mostafa*

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 967-984, 2022, DOI:10.32604/csse.2022.024854

    Abstract Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security strategies and models to overcome… More >

  • Open Access


    Insider Threat Detection Based on NLP Word Embedding and Machine Learning

    Mohd Anul Haq1, Mohd Abdul Rahim Khan1,*, Mohammed Alshehri2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 619-635, 2022, DOI:10.32604/iasc.2022.021430

    Abstract The growth of edge computing, the Internet of Things (IoT), and cloud computing have been accompanied by new security issues evolving in the information security infrastructure. Recent studies suggest that the cost of insider attacks is higher than the external threats, making it an essential aspect of information security for organizations. Efficient insider threat detection requires state-of-the-art Artificial Intelligence models and utility. Although significant have been made to detect insider threats for more than a decade, there are many limitations, including a lack of real data, low accuracy, and a relatively low false alarm, which are major concerns needing further… More >

  • Open Access


    Design of Cybersecurity Threat Warning Model Based on Ant Colony Algorithm

    Weiwei Lin1,2,*, Reiko Haga3

    Journal on Big Data, Vol.3, No.4, pp. 147-153, 2021, DOI:10.32604/jbd.2021.017299

    Abstract In this paper, a cybersecurity threat warning model based on ant colony algorithm is designed to strengthen the accuracy of the cybersecurity threat warning model in the warning process and optimize its algorithm structure. Through the ant colony algorithm structure, the local global optimal solution is obtained; and the cybersecurity threat warning index system is established. Next, the above two steps are integrated to build the cybersecurity threat warning model based on ant colony algorithm, and comparative experiment is also designed. The experimental results show that, compared with the traditional qualitative differential game-based cybersecurity threat warning model, the cybersecurity threat… More >

  • Open Access


    Enterprise Cyberspace Threat Landscape: An Analysis

    Emmanuel U. Opara1,*, Oredola A. Soluade2

    Journal of Cyber Security, Vol.3, No.3, pp. 167-176, 2021, DOI:10.32604/jcs.2021.019158

    Abstract The ecosystem security platform described in this research is already impacting the threat spectrum in quantifiable ways. The global network has undergone a dramatic transformation over the course of 2020, with an unprecedented destabilization of events. Security breaches of all kinds are growing in complexity, sophistication, and impact. The bad actors are bypassing predictable security devices at will by breaching network systems at an escalating rate. This study will analyze these developments by creating awareness among security practitioners so they can be prepared to defend their enterprise systems. More >

  • Open Access


    Extensive Study of Cloud Computing Technologies, Threats and Solutions Prospective

    Mwaffaq Abu-Alhaija1, Nidal M. Turab1,*, AbdelRahman Hamza2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 225-240, 2022, DOI:10.32604/csse.2022.019547

    Abstract Infrastructure as a Service (IaaS) provides logical separation between data, network, applications and machines from the physical constrains of real machines. IaaS is one of the basis of cloud virtualization. Recently, security issues are also gradually emerging with virtualization of cloud computing. Different security aspects of cloud virtualization will be explored in this research paper, security recognizing potential threats or attacks that exploit these vulnerabilities, and what security measures are used to alleviate such threats. In addition, a discussion of general security requirements and the existing security schemes is also provided. As shown in this paper, different components of virtualization… More >

  • Open Access


    Web Security: Emerging Threats and Defense

    Abdulwahed Awad Almutairi1, Shailendra Mishra2,*, Mohammed AlShehri1

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1233-1248, 2022, DOI:10.32604/csse.2022.019427

    Abstract Web applications have become a widely accepted method to support the internet for the past decade. Since they have been successfully installed in the business activities and there is a requirement of advanced functionalities, the configuration is growing and becoming more complicated. The growing demand and complexity also make these web applications a preferred target for intruders on the internet. Even with the support of security specialists, they remain highly problematic for the complexity of penetration and code reviewing methods. It requires considering different testing patterns in both codes reviewing and penetration testing. As a result, the number of hacked… More >

  • Open Access


    Secure Multifactor Remote Access User Authentication Framework for IoT Networks

    Mohammed Mujib Alshahrani*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3235-3254, 2021, DOI:10.32604/cmc.2021.015310

    Abstract The term IoT refers to the interconnection and exchange of data among devices/sensors. IoT devices are often small, low cost, and have limited resources. The IoT issues and challenges are growing increasingly. Security and privacy issues are among the most important concerns in IoT applications, such as smart buildings. Remote cybersecurity attacks are the attacks which do not require physical access to the IoT networks, where the attacker can remotely access and communicate with the IoT devices through a wireless communication channel. Thus, remote cybersecurity attacks are a significant threat. Emerging applications in smart environments such as smart buildings require… More >

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