scholarly journals Intrusion Detection into Cloud-Fog-Based IoT Networks Using Game Theory

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Poria Pirozmand ◽  
Mohsen Angoraj Ghafary ◽  
Safieh Siadat ◽  
Jiankang Ren
Keyword(s):  
Game Theory ◽  
Nash Equilibrium ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Detection System ◽  
Human Life ◽  
Intrusion Detection Systems ◽  
The Internet ◽  
Detection Systems ◽  
The Internet Of Things

The Internet of Things is an emerging technology that integrates the Internet and physical smart objects. This technology currently is used in many areas of human life, including education, agriculture, medicine, military and industrial processes, and trade. Integrating real-world objects with the Internet can pose security threats to many of our day-to-day activities. Intrusion detection systems (IDS) can be used in this technology as one of the security methods. In intrusion detection systems, early and correct detection (with high accuracy) of intrusions is considered very important. In this research, game theory is used to develop the performance of intrusion detection systems. In the proposed method, the attacker infiltration mode and the behavior of the intrusion detection system as a two-player and nonparticipatory dynamic game are completely analyzed and Nash equilibrium solution is used to create specific subgames. During the simulation performed using MATLAB software, various parameters were examined using the definitions of game theory and Nash equilibrium to extract the parameters that had the most accurate detection results. The results obtained from the simulation of the proposed method showed that the use of intrusion detection systems in the Internet of Things based on cloud-fog can be very effective in identifying attacks with the least amount of errors in this network.

scholarly journals A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ansam Khraisat ◽  
Ammar Alazab
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Communication Systems ◽  
Intrusion Detection Systems ◽  
The Internet ◽  
Detection Systems ◽  
Advantages And Disadvantages ◽  
Deployment Strategy ◽  
The Internet Of Things ◽  
Validation Strategy

AbstractThe Internet of Things (IoT) has been rapidly evolving towards making a greater impact on everyday life to large industrial systems. Unfortunately, this has attracted the attention of cybercriminals who made IoT a target of malicious activities, opening the door to a possible attack on the end nodes. To this end, Numerous IoT intrusion detection Systems (IDS) have been proposed in the literature to tackle attacks on the IoT ecosystem, which can be broadly classified based on detection technique, validation strategy, and deployment strategy. This survey paper presents a comprehensive review of contemporary IoT IDS and an overview of techniques, deployment Strategy, validation strategy and datasets that are commonly applied for building IDS. We also review how existing IoT IDS detect intrusive attacks and secure communications on the IoT. It also presents the classification of IoT attacks and discusses future research challenges to counter such IoT attacks to make IoT more secure. These purposes help IoT security researchers by uniting, contrasting, and compiling scattered research efforts. Consequently, we provide a unique IoT IDS taxonomy, which sheds light on IoT IDS techniques, their advantages and disadvantages, IoT attacks that exploit IoT communication systems, corresponding advanced IDS and detection capabilities to detect IoT attacks.

A Survey on SDN-based Intrusion Detection Systems on the Internet of Thing: Concepts, Issues, and Blockchain Applications

2021 ◽  
Author(s):  
Heba A. Hassan ◽  
Ezz E. Hemdan ◽  
Walid El-Shafai ◽  
Mona Shokair ◽  
Fathi E. Abd El-Samie
Keyword(s):  
Intrusion Detection ◽  
Computer Networks ◽  
Detection System ◽  
Intrusion Detection Systems ◽  
Survey Study ◽  
The Internet ◽  
Detection Systems ◽  
Systems Software ◽  
The Internet Of Things ◽  
Sdn Controller

Abstract With the accelerated development of computer networks utilization and the enormous growth of the number of applications running on top of it, network security becomes more significant. Intrusion Detection Systems (IDS) is considered as one of the essential tools utilized to protect computer networks and information systems. Software-defined network (SDN) architecture is used to provide network monitoring and analysis mechanism due to the programming environment of the SDN controller. On the other hand intrusion detection system is developed to monitor incoming traffic to the SDN network; hence it enables SDN to adjust security service insertion. This paper presents a survey study for SDN with the Internet of Things (IoT) and its improved versions like SDN-based IDS and SDN-based IoT. Likewise, discussing the IoT and its problems, especially the security aspects and solutions to overcome these problems. Finally, a brief description of the Blockchain concept and how it can be merged with an SDN-based IoT system to further enhance its security aspects is provided.

A Survey

2019 ◽  
Vol 13 (1) ◽  
pp. 86-105 ◽  
Author(s):  
Sarika Choudhary ◽  
Nishtha Kesswani
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Detection System ◽  
Human Life ◽  
Cyber Attacks ◽  
Internet Technology ◽  
General Idea ◽  
The Internet ◽  
Detection Techniques ◽  
The Internet Of Things

The latest buzzword in internet technology nowadays is the Internet of Things. The Internet of Things (IoT) is an ever-growing network which will transform real-world objects into smart or intelligent virtual objects. IoT is a heterogeneous network in which devices with different protocols can connect with each other in order to exchange information. These days, human life depends upon the smart things and their activities. Therefore, implementing protected communications in the IoT network is a challenge. Since the IoT network is secured with authentication and encryption, but not secured against cyber-attacks, an Intrusion Detection System is needed. This research article focuses on IoT introduction, architecture, technologies, attacks and IDS. The main objective of this article is to provide a general idea of the Internet of Things, various intrusion detection techniques, and security attacks associated with IoT.

scholarly journals Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1977 ◽  
Author(s):  
Geethapriya Thamilarasu ◽  
Shiven Chawla
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Learning Algorithm ◽  
Detection System ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Systems ◽  
The Internet Of Things

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.

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