scholarly journals Recent Advancements in Intrusion Detection Systems for the Internet of Things

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Zeeshan Ali Khan ◽  
Peter Herrmann
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Ad Hoc ◽  
Denial Of Service ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Future Research ◽  
Detection Systems ◽  
Iot Applications ◽  
Iot Devices

Many Internet of Things (IoT) systems run on tiny connected devices that have to deal with severe processor and energy restrictions. Often, the limited processing resources do not allow the use of standard security mechanisms on the nodes, making IoT applications quite vulnerable to different types of attacks. This holds particularly for intrusion detection systems (IDS) that are usually too resource-heavy to be handled by small IoT devices. Thus, many IoT systems are not sufficiently protected against typical network attacks like Denial-of-Service (DoS) and routing attacks. On the other side, IDSs have already been successfully used in adjacent network types like Mobile Ad hoc Networks (MANET), Wireless Sensor Networks (WSN), and Cyber-Physical Systems (CPS) which, in part, face limitations similar to those of IoT applications. Moreover, there is research work ongoing that promises IDSs that may better fit to the limitations of IoT devices. In this article, we will give an overview about IDSs suited for IoT networks. Besides looking on approaches developed particularly for IoT, we introduce also work for the three similar network types mentioned above and discuss if they are also suitable for IoT systems. In addition, we present some suggestions for future research work that could be useful to make IoT networks more secure.

A Compressive Compilation of Cyber Security for Internet of Energy (IoE)

2022 ◽  
pp. 883-910
Author(s):  
Gustavo Arroyo-Figueroa ◽  
Isai Rojas-Gonzalez ◽  
José Alberto Hernández-Aguilar
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Cyber Security ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Electrical Network ◽  
Future Research ◽  
Electrical Grid ◽  
Detection Systems ◽  
Security Challenges

Internet of energy (IoE) is the natural evolution of Smart Grid incorporating the paradigm of internet of things (IoT). This complicated environment has a lot of threats and vulnerabilities, so the security challenges are very complex and specialized. This chapter contains a compilation of the main threats, vulnerabilities, and attacks that can occur in the IoE environment and the critical structure of the electrical grid. The objective is to show the best cybersecurity practices that can support maintaining a safe, reliable, and available electrical network complying with the requirements of availability, integrity, and confidentially of the information. The study includes review of countermeasures, standards, and specialized intrusion detection systems, as mechanisms to solve security problems in IoE. Better understanding of security challenges and solutions in the IoE can be the light on future research work for IoE security.

A Compressive Compilation of Cyber Security for Internet of Energy (IoE)

2020 ◽  
pp. 267-294
Author(s):  
Gustavo Arroyo-Figueroa ◽  
Isai Rojas-Gonzalez ◽  
José Alberto Hernández-Aguilar
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Cyber Security ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Electrical Network ◽  
Future Research ◽  
Electrical Grid ◽  
Detection Systems ◽  
Security Challenges

Internet of energy (IoE) is the natural evolution of Smart Grid incorporating the paradigm of internet of things (IoT). This complicated environment has a lot of threats and vulnerabilities, so the security challenges are very complex and specialized. This chapter contains a compilation of the main threats, vulnerabilities, and attacks that can occur in the IoE environment and the critical structure of the electrical grid. The objective is to show the best cybersecurity practices that can support maintaining a safe, reliable, and available electrical network complying with the requirements of availability, integrity, and confidentially of the information. The study includes review of countermeasures, standards, and specialized intrusion detection systems, as mechanisms to solve security problems in IoE. Better understanding of security challenges and solutions in the IoE can be the light on future research work for IoE security.

scholarly journals Performance Assessment of Supervised Classifiers for Designing Intrusion Detection Systems: A Comprehensive Review and Recommendations for Future Research

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 690
Author(s):  
Ranjit Panigrahi ◽  
Samarjeet Borah ◽  
Akash Kumar Bhoi ◽  
Muhammad Fazal Ijaz ◽  
Moumita Pramanik ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Performance Measures ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Misclassification Rate ◽  
Future Research ◽  
Detection Systems ◽  
Network Intrusion ◽  
Supervised Classifiers ◽  
The Ideal

Supervised learning and pattern recognition is a crucial area of research in information retrieval, knowledge engineering, image processing, medical imaging, and intrusion detection. Numerous algorithms have been designed to address such complex application domains. Despite an enormous array of supervised classifiers, researchers are yet to recognize a robust classification mechanism that accurately and quickly classifies the target dataset, especially in the field of intrusion detection systems (IDSs). Most of the existing literature considers the accuracy and false-positive rate for assessing the performance of classification algorithms. The absence of other performance measures, such as model build time, misclassification rate, and precision, should be considered the main limitation for classifier performance evaluation. This paper’s main contribution is to analyze the current literature status in the field of network intrusion detection, highlighting the number of classifiers used, dataset size, performance outputs, inferences, and research gaps. Therefore, fifty-four state-of-the-art classifiers of various different groups, i.e., Bayes, functions, lazy, rule-based, and decision tree, have been analyzed and explored in detail, considering the sixteen most popular performance measures. This research work aims to recognize a robust classifier, which is suitable for consideration as the base learner, while designing a host-based or network-based intrusion detection system. The NSLKDD, ISCXIDS2012, and CICIDS2017 datasets have been used for training and testing purposes. Furthermore, a widespread decision-making algorithm, referred to as Techniques for Order Preference by Similarity to the Ideal Solution (TOPSIS), allocated ranks to the classifiers based on observed performance reading on the concern datasets. The J48Consolidated provided the highest accuracy of 99.868%, a misclassification rate of 0.1319%, and a Kappa value of 0.998. Therefore, this classifier has been proposed as the ideal classifier for designing IDSs.

scholarly journals Intrusion Detection Systems in Internet of Things and Mobile Ad-Hoc Networks

2022 ◽  
Vol 40 (3) ◽  
pp. 1199-1215
Author(s):  
Vasaki Ponnusamy ◽  
Mamoona Humayun ◽  
N. Z. Jhanjhi ◽  
Aun Yichiet ◽  
Maram Fahhad Almufareh
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Intrusion Detection Systems ◽  
Detection Systems ◽  
Mobile Ad Hoc ◽  
Hoc Networks

Distributed Intrusion Detection Systems

2007 ◽  
pp. 231-238
Author(s):  
Rosalind Deena Kumari ◽  
G. Radhamani
Keyword(s):  
Intrusion Detection ◽  
System Architecture ◽  
Intrusion Detection System ◽  
Detection System ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Future Research ◽  
Detection Systems ◽  
Distributed Intrusion Detection ◽  
Entire Network

The recent tremendous increase in the malicious usage of the network has made it necessary that an IDS should encapsulate the entire network rather than at a system. This was the inspiration for the birth of a distributed intrusion detection system (DIDS). Different configurations of DIDSs have been actively used and are also rapidly evolving due to the changes in the types of threats. This chapter will give the readers an overview of DIDS and the system architecture. It also highlights on the various agents that are involved in DIDS and the benefits of the system. Finally, directions for future research work are discussed.

Intrusion Detection Systems for Internet of Things

2020 ◽  
pp. 148-171
Author(s):  
Gayathri K. S. ◽  
Tony Thomas
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Remote Monitoring ◽  
Human Life ◽  
Intrusion Detection Systems ◽  
Security Vulnerabilities ◽  
Detection Systems ◽  
Iot Devices ◽  
And Storage ◽  
Security Of Iot

Internet of things (IoT) is revolutionizing this world with its evolving applications in various aspects of life such as sensing, healthcare, remote monitoring, and so on. These systems improve the comfort and efficiency of human life, but the inherent vulnerabilities in these IoT devices create a backdoor for intruders to enter and attack the entire system. Hence, there is a need for intrusion detection systems (IDSs) designed for IoT environments to mitigate IoT-related security attacks that exploit some of these security vulnerabilities. Due to the limited computing and storage capabilities of IoT devices and the specific protocols used, conventional IDSs may not be an option for IoT environments. Since the security of IoT systems is critical, this chapter presents recent research in intrusion detection systems in IoT systems.

scholarly journals Clinical Perspective on Internet of Things Applications for Care of the Elderly

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1925
Author(s):  
Soe Ye Yint Tun ◽  
Samaneh Madanian ◽  
Dave Parry
Keyword(s):  
Internet Of Things ◽  
Older People ◽  
Clinical Utility ◽  
Elderly Care ◽  
The Elderly ◽  
Aged Care ◽  
Information Technology Professionals ◽  
Future Research ◽  
Iot Applications ◽  
Iot Devices

The elderly population is increasing globally, putting more pressure on aged care and public health systems. To address this issue and help increase the independence of older people, different digital technologies, including the Internet of things (IoT), can play an important role. Although there has been an increase in the number of studies in this field, most of them concentrate on IoT applications in elderly care from a technology perspective, with very little contribution from the clinical side. Therefore, this paper aims to investigate and identify the available IoT applications and their clinical utility for common diseases in elderly people. The results of this study could be useful for information technology professionals in developing and understanding the clinical requirements for IoT applications in healthcare for older people. Clinicians will also be informed about the clinical possibilities of using IoT devices in this area. Based on our findings, future research should focus on enhancing the clinical utility of current IoT applications in different settings and on developing new applications to support practitioners and older people.

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