A survey on graph neural networks for intrusion detection systems: methods, trends and challenges

M Zhong, M Lin, C Zhang, Z Xu - Computers & Security, 2024 - Elsevier
Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …

[HTML][HTML] Evolving techniques in cyber threat hunting: A systematic review

A Mahboubi, K Luong, H Aboutorab, HT Bui… - Journal of Network and …, 2024 - Elsevier
In the rapidly changing cybersecurity landscape, threat hunting has become a critical
proactive defense against sophisticated cyber threats. While traditional security measures …

Graph neural networks for intrusion detection: A survey

T Bilot, N El Madhoun, K Al Agha, A Zouaoui - IEEE Access, 2023 - ieeexplore.ieee.org
Cyberattacks represent an ever-growing threat that has become a real priority for most
organizations. Attackers use sophisticated attack scenarios to deceive defense systems in …

Flash: A comprehensive approach to intrusion detection via provenance graph representation learning

MU Rehman, H Ahmadi… - 2024 IEEE Symposium on …, 2024 - ieeexplore.ieee.org
Recently, provenance-based Intrusion Detection Systems (IDSes) have gained popularity for
their potential in detecting sophisticated Advanced Persistent Threat (APT) attacks. These …

{PROGRAPHER}: An anomaly detection system based on provenance graph embedding

F Yang, J Xu, C **ong, Z Li, K Zhang - 32nd USENIX Security …, 2023 - usenix.org
In recent years, the Advanced Persistent Threat (APT), which involves complex and
malicious actions over a long period, has become one of the biggest threats against the …

Sok: Pragmatic assessment of machine learning for network intrusion detection

G Apruzzese, P Laskov… - 2023 IEEE 8th European …, 2023 - ieeexplore.ieee.org
Machine Learning (ML) has become a valuable asset to solve many real-world tasks. For
Network Intrusion Detection (NID), however, scientific advances in ML are still seen with …

Temporal link prediction: A unified framework, taxonomy, and review

M Qin, DY Yeung - ACM Computing Surveys, 2023 - dl.acm.org
Dynamic graphs serve as a generic abstraction and description of the evolutionary
behaviors of various complex systems (eg, social networks and communication networks) …

A survey on malware detection with graph representation learning

T Bilot, N El Madhoun, K Al Agha, A Zouaoui - ACM Computing Surveys, 2024 - dl.acm.org
Malware detection has become a major concern due to the increasing number and
complexity of malware. Traditional detection methods based on signatures and heuristics …

LogFiT: Log anomaly detection using fine-tuned language models

C Almodovar, F Sabrina, S Karimi… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
System logs are a valuable source of information for monitoring and maintaining the security
and stability of computer systems. Techniques based on Deep Learning and Natural …

" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences

D Olszewski, A Lu, C Stillman, K Warren… - Proceedings of the …, 2023 - dl.acm.org
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …