# A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT

**Authors:** Junaid Arshad, Muhammad Ajmal Azad, Khaled Salah, Wei Jie, Razi Iqbal, Mamoun Alazab  
**arXiv:** [1812.09160](https://arxiv.org/abs/1812.09160)  
**Date:** 2018-12-21  
**Summary page:** https://www.summarizepaper.com/en/paper/1812.09160v1/

## Key points

- The Internet of Things (IoT) is a disruptive technology with applications in various domains
- Attacks on IoT infrastructures have increased, highlighting the need for effective protection mechanisms like intrusion detection
- Intrusion detection systems for IoT and Internet of Vehicles (IoV) have unique challenges due to limited battery power, bandwidth constraints, processor overheads, and network dynamics
- A comprehensive study was conducted on existing intrusion detection systems for IoT and IoV, analyzing them from perspectives of computational overhead, energy consumption, and privacy implications
- Open challenges were identified in designing an effective and collaborative intrusion detection system for resource-constrained IoT systems and their applications like IoV
- The efforts made in this study aim to provide insights into state-of-the-art intrusion detection techniques for IoT while highlighting specific challenges that require further attention
- Authors of the review paper are Junaid Arshad, Muhammad Ajmal Azad, Khaled Salah, Wei Jie Razi Iqbal, and Mamoun Alazab.

## Summary

The Internet of Things (IoT) is a disruptive technology with applications in various domains such as transportation and logistics systems, smart grids, smart homes, connected vehicles, and smart cities. As these infrastructures continue to grow, the number and types of attacks on them have also increased. This emphasizes the need for effective protection mechanisms like intrusion detection which has seen significant advancements in recent years for IoT systems and the emerging field of Internet of Vehicles (IoV). However, the unique characteristics of these infrastructures such as limited battery power, bandwidth constraints, processor overheads and network dynamics can impact the operation of intrusion detection systems. To address this challenge, a comprehensive study was conducted on existing intrusion detection systems for IoT systems including IoV. The study analyzed these systems from three perspectives: computational overhead, energy consumption and privacy implications. By rigorously analyzing existing approaches to intrusion detection, the study also identified open challenges in designing an effective and collaborative intrusion detection system for resource-constrained IoT systems and their applications like IoV. The efforts made in this study aim to provide insights into the state-of-the-art intrusion detection techniques for IoT while highlighting specific challenges that require further attention to achieve efficient intrusion detection within these systems. The authors of this review paper are Junaid Arshad, Muhammad Ajmal Azad, Khaled Salah, Wei Jie Razi Iqbal and Mamoun Alazab.