# A Review of Performance, Energy and Privacy of Intrusion Detection Systems for IoT  
[PERSON]  
1 School of Computing and Digital Technology, Birmingham City University, Birmingham B4 7 AP, UK College of Engineering and Technology, School of University of Derby, Derby DE22 1 GB, UK; [EMAIL_ADDRESS]  
[PERSON]  
2 College of Engineering and Technology, School of University of Derby, Derby DE22 1 GB, UK; [EMAIL_ADDRESS]  
[PERSON]  
3 Department of Computer Science & IT, NED University of Engineering and Technology, Karachi 75270, Pakistan; roohi  
For instance, smart grids enable improved management and maintenance of a country's electric grid in a cost effective manner by incorporating smart elements throughout the power generation, distribution and consumption chain. The evolution of smart cities and the role of CPS in this development is underpinned by IoT which are critical in realizing the next generation of infrastructures to develop technological solutions in a sustainable manner. Within this context, the ability of smart devices to communicate using internet connectivity is of fundamental significance, which has enabled IoT to achieve _connected_ infrastructures. However, the open network architecture of IoT has also attracted a significant increase in malicious threats for smart infrastructures as identified by [2]. Furthermore, a recent study by Gartner [3] has predicted IoT-based attacks to form 25% of all enterprise attacks by 2020, highlighting the need for distinct protection mechanisms. Due to the proliferation of such devices in almost every aspect of our life, the threats posed due to their insufficient security are unique, as insecure devices expose end users to serious security and privacy threats. For instance, if an attacker is able to compromise an in-car WiFi; in-car devices and data will be at risk. Once inside the car's network, an attacker can spoof the car, connect to outside data sources, and steal the owner's personal information including credit card data [4]. In view of such emerging threats, the need to address security challenges for infrastructures underpinning smart cities is paramount [5]. There have been a number of efforts to address different dimensions of security for IoT such as secure frameworks [6; 7], privacy of information [8], and authentication [9]. However, the challenge in the design of an effective secure system is two-fold: firstly, the devices which form these systems are typically resource-constrained limiting their ability to implement sophisticated security management system to monitor device activities in real time; secondly, the ad-hoc nature of IoT systems allows devices to connect to other devices at run-time, typically for short time periods, thereby creating a collaborative network. Therefore, efforts to address security challenges for IoT systems should take into account these factors to ensure effectiveness and applicability. Intrusion detection system (IDS) is one of the fundamental components of a typical security architecture, which provides visibility into the activities of a system, enabling timely detection and response to any undesired events. An IDS can be categorized into the following main approaches: misuse/signature-based detection systems, behavioural or anomaly-based detection, specification-based intrusion detection, and hybrid intrusion detection systems [10; 11; 12]. Moreover, intrusion detection can be performed at the network or host level typically driven by the security policy of the monitored system. In recent years, IDSs for IoT have received increased attention with a number of notable efforts such as [13; 14; 15; 16]. Within this context, the focus of our research is to investigate novel challenges to achieve efficient intrusion detection for IoT systems and explore potential solutions to address them.