Advance persistent threat prediction using knowledge graph

Abstract

Advanced persistent threats (APTs) are a major threat to cybersecurity, and they are typically attributed to nation-state actors or well-organized groups with sophisticated capabilities. This knowledge graph is intended to help you understand and attribute APT organizations by providing a framework for understanding their characteristics, attributing challenges, attributing clues, attributing methodologies, and attributing limitations. By understanding APT organizations and attributing challenges, clues, methodologies, and attribution limitations, you can gain valuable insights and methods for unraveling the mystery surrounding APT organizations. The graph highlights the difficulties and intricacies associated with attribution, such as false flags, use of proxies, cooperation between APTs and the evolving tactics employed by threat actors. State- sponsored attribution is based on government statements or intelligence agency reports; private sector attribution is based on cybersecurity firms’ reports or threat intelligence sharing; and academia and independent research is based on academic and non-academic sources. The graph serves as a resource for cybersecurity professionals, analysts and researchers looking for a systematic framework to improve their understanding and ability to attribute cyberattacks to attack actors. It offers in-depth analysis and practical advice to navigate the complex landscape of APP attribution in today’s rapidly changing cybersecurity landscape.