A holistic and proactive approach to forecasting cyber threats

Zaid Almahmoud, Paul D. Yoo, Omar Alhussein, Ilyas Farhat, Ernesto Damiani

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Traditionally, cyber-attack detection relies on reactive, assistive techniques, where pattern-matching algorithms help human experts to scan system logs and network traffic for known virus or malware signatures. Recent research has introduced effective Machine Learning (ML) models for cyber-attack detection, promising to automate the task of detecting, tracking and blocking malware and intruders. Much less effort has been devoted to cyber-attack prediction, especially beyond the short-term time scale of hours and days. Approaches that can forecast attacks likely to happen in the longer term are desirable, as this gives defenders more time to develop and share defensive actions and tools. Today, long-term predictions of attack waves are mostly based on the subjective perceptiveness of experienced human experts, which can be impaired by the scarcity of cyber-security expertise. This paper introduces a novel ML-based approach that leverages unstructured big data and logs to forecast the trend of cyber-attacks at a large scale, years in advance. To this end, we put forward a framework that utilises a monthly dataset of major cyber incidents in 36 countries over the past 11 years, with new features extracted from three major categories of big data sources, namely the scientific research literature, news, blogs, and tweets. Our framework not only identifies future attack trends in an automated fashion, but also generates a threat cycle that drills down into five key phases that constitute the life cycle of all 42 known cyber threats. © 2023, Crown.
Original languageAmerican English
JournalScientific Reports
Volume13
Issue number1
DOIs
StatePublished - 2023

Keywords

  • article
  • big data
  • blogging
  • computer security
  • cyberattack
  • forecasting
  • human
  • life cycle
  • machine learning
  • prediction
  • algorithm
  • Algorithms
  • Big Data
  • Blogging
  • Computer Security
  • Humans
  • Machine Learning

Fingerprint

Dive into the research topics of 'A holistic and proactive approach to forecasting cyber threats'. Together they form a unique fingerprint.

Cite this