Open Access
REVIEW
Abdulrahman M. Abdulghani1,*, Azizol Abdullah1, A. R. Rahiman1, Nor Asilah Wati Abdul Hamid1,2, Bilal Omar Akram3,4, Hafsa Raissouli1
Computer Systems Science and Engineering, DOI:10.32604/csse.2024.058314
Abstract This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks (SD-WANs), with a particular emphasis on the multi-objective Controller Placement Problem (CPP). As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management, the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge. This review delves into recent innovations in multi-objective controller placement strategies, including clustering techniques, heuristic-based approaches, and the integration of machine learning and deep learning models. Each methodology is critically More >
Open Access
ARTICLE
Verónica C. Tapia1,2,*, Carlos M. Gaona2
Computer Systems Science and Engineering, DOI:10.32604/csse.2024.056979
Abstract In recent years, automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market. The integration of artificial intelligence (AI) tools, particularly those using natural language processing (NLP) like ChatGPT, has opened new possibilities for automating various stages of the development lifecycle. The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development. An artificial intelligence (AI) tool was developed using the OpenAI—Application Programming Interface (API), incorporating two key functionalities: 1) generating user stories based on case or process… More >
Open Access
ARTICLE
Khadija El Fellah1,*, Ikram El Azami2,*, Adil El Makrani2, Habiba Bouijij3, Oussama El Azzouzy4
Computer Systems Science and Engineering, DOI:10.32604/csse.2024.057754
（This article belongs to the Special Issue: Blockchain, Artificial Intelligence, Internet of Things and 6G Convergence)
Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >
Open Access
ARTICLE
Sameh Zarif1,2,*, Hadier Moawad2, Khalid Amin2, Abdullah Alharbi3, Wail S. Elkilani4, Shouze Tang5, Marian Wagdy6
Computer Systems Science and Engineering, DOI:10.32604/csse.2024.057439
Abstract Authentication is the most crucial aspect of security and a predominant measure employed in cybersecurity. Cloud computing provides a shared electronic device resource for users via the internet, and the authentication techniques used must protect data from attacks. Previous approaches failed to resolve the challenge of making passwords secure, memorable, usable, and time-saving. Graphical Password (GP) is still not widely utilized in reality because consumers suffer from multiple login stages. This paper proposes an Indexed Choice-Based Graphical Password (ICGP) scheme for improving the authentication part. ICGP consists of two stages: registration and authentication. At the… More >
Open Access
ARTICLE
Xianju Gao*, Huachun Zhou, Weilin Wang, Jingfu Yan
Computer Systems Science and Engineering, DOI:10.32604/csse.2024.058327
（This article belongs to the Special Issue: Artificial Intelligence for Cyber Security)
Abstract The network security knowledge base standardizes and integrates network security data, providing a reliable foundation for real-time network security protection solutions. However, current research on network security knowledge bases mainly focuses on their construction, while the potential to optimize intelligent security services for real-time network security protection requires further exploration. Therefore, how to effectively utilize the vast amount of historical knowledge in the field of network security and establish a feedback mechanism to update it in real time, thereby enhancing the detection capability of security services against malicious traffic, has become an important issue. Our… More >
Open Access
ARTICLE
Nishit Patil, Shubhalaxmi Joshi*
Computer Systems Science and Engineering, DOI:10.32604/csse.2024.057702
（This article belongs to the Special Issue: Artificial Intelligence for Cyber Security)
Abstract Intrusion detection (ID) is a cyber security practice that encompasses the process of monitoring network activities to identify unauthorized or malicious actions. This includes problems like the difficulties of existing intrusion detection models to identify emerging attacks, generating many false alarms, and their inability and difficulty to adapt themselves with time when it comes to threats, hence to overcome all those existing challenges in this research develop a Prairie Araneida optimization based fused Convolutional Neural Network model (PAO-CNN) for intrusion detection. The fused CNN (Convolutional Neural Netowrk) is a remarkable development since it combines statistical… More >
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