Deep Learning Assisted Cyber Criminal Profiling

This paper presents an approach for cybercriminal profiling using pre-trained DistilBert, LSTM, and BERT models. By analyzing criminal behaviors and linking them to offender characteristics, the proposed method utilizes structural and parameter learning techniques. Digital forensics, as a means to locate criminal and cybercriminal activity, is highlighted as increasingly important. The suggested strategy incorporates tools such as technical competency tests, a dynamic criminal knowledge base, and visualization to provide investigators with a comprehensive understanding of the case. The paper also discusses the potential benefits of integrating this approach into a cloud-based infrastructure, offering a faster and more cost-effective solution.