Oct 2026· Advances in computational intelligence and robotics book series· 26 references
Network Security and Intrusion Detection
Abstract
Cybersecurity is the core where protection is provided to digital resources like servers, Data centers and Networks. Adoption of Artificial Intelligence (AI) driven cybersecurity strengthens the digital ecosystem. Web Sites and Social media are engines in the modern digital world where organizations, customers and users are facing challenges due to theft of data, money, identity and cyber attacks. Cyber crimes like tampering of digital assets need to be detected with tools and techniques that should be automated. Autonomous Systems in various sectors try to prevent crimes through Anti malware, Antivirus, Firewalls, Encryption and Multi stage authorization. This chapter provides analytical study of various tools, research work carried out with AI techniques. Critical analysis of challenges in unified security frameworks, Models as well as an explainable AI framework for Cybersecurity presented in paper. Quantum Computing capabilities to crack algorithms and decryption of data. Quantum-safe cybersecurity explored along with challenges for the digital world that would arise in future.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
In Compton Lecture, the distinguished legal scholar warns of potential “loss of the Enlightenment” while suggesting ways innovations can meet our civic and cultural needs.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
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