A machine learning-based FinTech cyber threat attribution framework using high-level indicators of compromise

Volume: 96, Pages: 227 - 242
Published: Jul 1, 2019
Abstract
Cyber threat attribution identifies the source of a malicious cyber activity, which in turn informs cyber security mitigation responses and strategies. Such responses and strategies are crucial for deterring future attacks, particularly in the financial and critical infrastructure sectors. However, existing approaches generally rely on manual analysis of attack indicators obtained through approaches such as trace-back, firewalls, intrusion...
Paper Details
Title
A machine learning-based FinTech cyber threat attribution framework using high-level indicators of compromise
Published Date
Jul 1, 2019
Volume
96
Pages
227 - 242
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.