Privacy issues in intrusion detection systems: A taxonomy, survey and future directions

2012 ◽

Vol 2012 ◽

pp. 1-20 ◽

Cited By ~ 15

Author(s):

Gulshan Kumar ◽

Krishan Kumar

Keyword(s):

Artificial Intelligence ◽

Intrusion Detection ◽

Supervised Learning ◽

Ensemble Learning ◽

Classification Performance ◽

Intrusion Detection Systems ◽

Future Directions ◽

Comprehensive Review ◽

Detection Systems ◽

Combination Methods

In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI-) based techniques play prominent role in development of ensemble for intrusion detection (ID) and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular) during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1) architecture & approach followed; (2) different methods utilized in different phases of ensemble learning; (3) other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs).

Download Full-text

Host–Based Intrusion Detection Systems

Architectures and Protocols for Secure Information Technology Infrastructures - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-4666-4514-1.ch007 ◽

2014 ◽

pp. 184-213

Author(s):

Vít Bukač ◽

Vashek Matyáš

Keyword(s):

Intrusion Detection ◽

Detection Method ◽

State Of The Art ◽

Research Trends ◽

The State ◽

Intrusion Detection Systems ◽

Future Directions ◽

Detection Systems ◽

Research Findings ◽

Art Research

In this chapter, the reader explores both the founding ideas and the state-of-the-art research on host-based intrusion detection systems. HIDSs are categorized by their intrusion detection method. Each category is thoroughly investigated, and its limitations and benefits are discussed. Seminal research findings and ideas are presented and supplied with comments. Separate sections are devoted to the protection against tampering and to the HIDS evasion techniques that are employed by attackers. Existing research trends are highlighted, and possible future directions are suggested.

Download Full-text

Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions

Neural Computing and Applications ◽

10.1007/s00521-019-04557-3 ◽

2019 ◽

Vol 32 (14) ◽

pp. 9827-9858 ◽

Cited By ~ 1

Author(s):

A. M. Aleesa ◽

B. B. Zaidan ◽

A. A. Zaidan ◽

Nan M. Sahar

Keyword(s):

Deep Learning ◽

Intrusion Detection ◽

Intrusion Detection Systems ◽

Future Directions ◽

Detection Systems ◽

Learning Techniques

Download Full-text

Cutting the Gordian Knot

Handbook of Research on Wireless Security ◽

10.4018/978-1-59904-899-4.ch033 ◽

2008 ◽

pp. 531-546

Author(s):

John Felix Charles Joseph ◽

Amitabha Das ◽

Boon-Chong Seet ◽

Bu-Sung Lee

Keyword(s):

Intrusion Detection ◽

Ad Hoc Networks ◽

Routing Protocols ◽

Intrusion Detection System ◽

Ad Hoc ◽

Detection System ◽

Intrusion Detection Systems ◽

Future Directions ◽

Detection Systems ◽

Hoc Networks

Intrusion detection in ad hoc networks is a challenge because of the inherent characteristics of these networks, such as, the absence of centralized nodes, the lack of infrastructure, and so forth. Furthermore, in addition to application-based attacks, ad hoc networks are prone to attacks targeting routing protocols. Issues in intrusion detection in ad hoc networks are addressed by numerous research proposals in literature. In this chapter, we first enumerate the properties of ad hoc networks which hinder intrusion detection systems. After that, significant intrusion detection system (IDS) architectures and methodologies proposed in the literature are elucidated. Strengths and weaknesses of these works are studied and are explained. Finally, the future directions which will lead to the successful deployment of intrusion detection in ad hoc networks are discussed.

Download Full-text