Internet of Things (IoT) forms the foundation of next generation infrastructures, enabling development of future cities that are inherently sustainable. Intrusion detection for such paradigms is a non-trivial challenge which has attracted further significance due to extraordinary growth in the volume and variety of security threats for such systems. However, due to unique characteristics of such systems i.e., battery power, bandwidth and processor overheads and network dynamics, intrusion detection for IoT is a challenge, which requires taking into account the trade-off between detection accuracy and performance overheads. In this context, we are focused at highlighting this trade-off and its significance to achieve effective intrusion detection for IoT. Specifically, this paper presents a comprehensive study of existing intrusion detection systems for IoT systems in three aspects: computational overhead, energy consumption and privacy implications. Through extensive study of existing intrusion detection approaches, we have identified open challenges to achieve effective intrusion detection for IoT infrastructures. These include resource constraints, attack complexity, experimentation rigor and unavailability of relevant security data. Further, this paper is envisaged to highlight contributions and limitations of the state-of-the-art within intrusion detection for IoT, and aid the research community to advance it by identifying significant research directions.

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

The development of smart cities through digital communications has improved citizens' quality of life and well-being. In these cities, IoT technology generates vast amounts of data at any given time, which is analyzed to provide services to citizens. In the proper implementation of these cities, a critical challenge is the violation of citizens' privacy and security, which leads to a lack of trust and pessimism toward the services of the smart city. To ensure citizens' participation, smart city developers should adequately protect their security and privacy from gaining their trust. If citizens don't want to participate, the main benefits of a smart city will be lost. This article presents a comprehensive review of smart city security issues and privacy. It provides a basis for categorizing current and future developments in this area and developing a thematic classification to highlight the requirements and security strategies for designing a smart and safe city. The paper identifies current security and privacy solutions and describes open research challenges and issues. An output of this study is a systematic map of literature on the subject that identifies critical concepts, evidence, challenges, solutions, and gaps. It summarizes the findings into a body of evidence that has previously been heterogeneous and complex. 

A systematic review of technologies and solutions to improve security and privacy protection of citizens in the smart city

Internet of Things (IoT) represent a network of resource-constrained sensor devices connected through the open Internet, susceptible to misuse by intruders Traditional standalone intrusion detection systems (IDS) are tasked with monitoring device behaviours to identify malicious activities These systems not only require extensive network and system resources but also cause delays in detecting a malicious actor due to unavailability of a comprehensive view of the intruder's activities Collaboration among IoT devices enables considering knowledge from a collection of host and network devices to achieve improved detection accuracy in a timely manner However, collaboration introduces the challenge of energy efficiency and event processing which is particularly significant for resource-constrained devices In this paper, we present a collaborative intrusion detection framework (COLIDE) for IoT leveraging collaboration among resource-constrained sensor and border nodes for effective and timely detection of intruders The paper presents a detailed formal description of the proposed framework along with analysis to assess its effectiveness for a typical IoT system We implemented the COLIDE framework with Contiki OS and conducted thorough experimentation to evaluate its performance The evaluation demonstrates efficiency of COLIDE framework with respect to energy and processing overheads achieving effectiveness within an IoT system

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-net.2018.5036

COLIDE: a collaborative intrusion detection framework for Internet of Things

Internet of Things (IoT) is a disruptive technology with applications across diverse domains such as transportation and logistics systems, smart grids, smart homes, connected vehicles, and smart cities. Alongside the growth of these infrastructures, the volume and variety of attacks on these infrastructures has increased highlighting the significance of distinct protection mechanisms. Intrusion detection is one of the distinguished protection mechanisms with notable recent efforts made to establish effective intrusion detection for IoT and IoV. However, unique characteristics of such infrastructures including battery power, bandwidth and processors overheads, and the network dynamics can influence the operation of an intrusion detection system. This paper presents a comprehensive study of existing intrusion detection systems for IoT systems including emerging systems such as Internet of Vehicles (IoV). The paper analyzes existing systems in three aspects: computational overhead, energy consumption and privacy implications. Based on a rigorous analysis of the existing intrusion detection approaches, the paper also identifies open challenges for an effective and collaborative design of intrusion detection system for resource-constrained IoT system in general and its applications such as IoV. These efforts are envisaged to highlight state of the art with respect to intrusion detection for IoT and open challenges requiring specific efforts to achieve efficient intrusion detection within these systems.

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

With the recent increase in the adoption of Internet of Things (IoT) technology globally, cybersecurity-related issues have been raised, particularly with the limitations of IoT devices, privacy and other security standards guiding IoT development as wireless technology evolves. With the enterprise and the massive IoT market expected to reach $7.6 B and$1.2 B in 2024 respectively, according to Gartner, and several operational vertical IoT use cases and platforms experiencing cyber vulnerabilities. Based on the findings from our recent LPWANs IoT testbeds and their operational performance in certain use case scenarios, this paper summarizes the key wireless technology security requirements for IoT deployments. We first compare the security requirements of legacy and emerging IoT technologies as it relates to smart city applications and examined the effectiveness of the existing countermeasure opportunities as it affects the overall system performance in critical and non-critical machine type communications. We concluded by recommending countermeasures opportunities and frameworks to secure industrial IoT platforms to cope with future cybersecurity vulnerabilities.

/pdf/security-analysis-of-iot-networks-and-platforms-1vg70et9z5.pdf

Security Analysis of IoT Networks and Platforms

/pdf/security-management-for-the-internet-of-things-52o4ki94fk.pdf

Security Management for The Internet of Things

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Security Management for The Internet of Things