Host-based IDS: A review and open issues of an anomaly detection system in IoT

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Martins, I (Author) Other; Resende, JS (Author) Other; Sousa, PR (Author) Other; Silva, S (Author) Other; antunes, l (Author) FCUP; João Gama (Author) FEP

Journal

Title: Future Generation Computer Systems

Vol. 133

Pages: 95-113

ISSN: 0167-739X

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 47 Citations

Scopus - 79 Citations

Other information

Authenticus ID: P-00W-8S2

DOI: 10.1016/j.future.2022.03.001

Abstract (EN): The Internet of Things (IoT) envisions a smart environment powered by connectivity and heterogeneity where ensuring reliable services and communications across multiple industries, from financial fields to healthcare and fault detection systems, is a top priority. In such fields, data is being collected and broadcast at high speed on a continuous and real-time scale, including IoT in the streaming processing paradigm. Intrusion Detection Systems (IDS) rely on manually defined security policies and signatures that fail to design a real-time solution or prevent zero-day attacks. Therefore, anomaly detection appears as a prominent solution capable of recognizing patterns, learning from experience, and detecting abnormal behavior. However, most approaches do not fit the urged requirements, often evaluated on deprecated datasets not representative of the working environment. As a result, our contributions address an overview of cybersecurity threats in IoT, important recommendations for a real-time IDS, and a real-time dataset setting to evaluate a security system covering multiple cyber threats. The dataset used to evaluate current host-based IDS approaches is publicly available and can be used as a benchmark by the community.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19