Sep 2026· Advances in computational intelligence and robotics book series· pp. 63-92· 35 references
Cybercrime and Law Enforcement Studies
Abstract
The fast growth of dark web processes has made cybercrime an adaptive and intelligence-driven phenomenon that warrants a change in thinking about digital policing, traditionally basing it on fixed rules and post hoc investigation. The strategy involves integrating transformer-based semantic analysis, time behavior and human-in-the-loop decision support in ensuring that the insights of analytical knowledge, which can be explained and traced, are either procedurally sound. The framework is the first that views AI as an epistemic type of assistance, which resides in the socio-legal constraints, but not as a means of enforcing law. Experimental analysis shows that the given framework has a threat detection accuracy of 88.9% and F1-score of 87.6, both being superior to similar AI-based methods by 4-7 percentage points and retaining higher evidentiary preparedness and ethical integrity. The temporal analysis also displays a less volatile threat scoring with the varying dark web activity. .
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.
Microsoft Research Blog· microsoft.comOct 22, 2026
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
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