Survey of intrusion detection systems: techniques, datasets and challenges
Обзор систем обнаружения вторжений: методы, наборы данных и проблемы
2019-07-17
SCID: 54.1/3dcaukgy
Discuss with AI
anomaly-based intrusion detectioncyber-attack evasion techniquesintrusion detection datasetsintrusion detection systemssignature-based intrusion detection
Figures from the paper
Abstract (AI)
Cyber-attacks are becoming more sophisticated and thereby presenting increasing challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade the credibility of security services, e.g. data confidentiality, integrity, and availability. Numerous intrusion detection methods have been proposed in the literature to tackle computer security threats, which can be broadly classified into Signature-based Intrusion Detection Systems (SIDS) and Anomaly-based Intrusion Detection Systems (AIDS). This survey paper presents a taxonomy of contemporary IDS, a comprehensive review of notable recent works, and an overview of the datasets commonly used for evaluation purposes. It also presents evasion techniques used by attackers to avoid detection and discusses future research challenges to counter such techniques so as to make computer systems more secure.
Key Findings
1
Commonly used datasets for evaluating intrusion detection systems are systematically overviewed.
2
Increasingly sophisticated cyber-attacks make accurate intrusion detection more difficult, threatening data confidentiality, integrity, and availability.
3
Intrusion detection systems are broadly classified into signature-based and anomaly-based approaches for addressing computer security threats.
4
The paper examines attacker evasion techniques that can circumvent intrusion detection and identifies future research challenges for improving security.
5
The survey develops a taxonomy of contemporary intrusion detection systems and reviews notable recent research on these methods.
Research Object
Intrusion detection systems (IDS) for computer security
Research Subject
detection techniques, evaluation datasets, evasion methods, and research challenges concerning intrusion detection
Publication Details
Publication Date
2019-07-17
Journal
Publisher
ISSN
Open access PDF
Access Type
Author Information
Download PDF
Subscribe to digest