Intrusion detection systems in the Internet of things: A comprehensive investigation

2019 ◽  
Vol 160 ◽  
pp. 165-191 ◽  
Author(s):  
Somayye Hajiheidari ◽  
Karzan Wakil ◽  
Maryam Badri ◽  
Nima Jafari Navimipour
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection Systems ◽  
The Internet ◽  
Comprehensive Investigation ◽  
Detection Systems ◽  
The Internet Of Things

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.

scholarly journals MADS Based on DL Techniques on the Internet of Things (IoT): Survey

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2598
Author(s):  
Hussah Talal ◽  
Rachid Zagrouba
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection Systems ◽  
The Internet ◽  
Detection Systems ◽  
Iot Applications ◽  
New Generation ◽  
The Internet Of Things ◽  
Great Development ◽  
Comprehensive Study

Technologically speaking, humanity lives in an age of evolution, prosperity, and great development, as a new generation of the Internet has emerged; it is the Internet of Things (IoT) which controls all aspects of lives, from the different devices of the home to the large industries. Despite the tremendous benefits offered by IoT, still there are some challenges regarding privacy and information security. The traditional techniques used in Malware Anomaly Detection Systems (MADS) could not give us as robust protection as we need in IoT environments. Therefore, it needed to be replaced with Deep Learning (DL) techniques to improve the MADS and provide the intelligence solutions to protect against malware, attacks, and intrusions, in order to preserve the privacy of users and increase their confidence in and dependence on IoT systems. This research presents a comprehensive study on security solutions in IoT applications, Intrusion Detection Systems (IDS), Malware Detection Systems (MDS), and the role of artificial intelligent (AI) in improving security in IoT.

scholarly journals Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Hector Alaiz-Moreton ◽  
Jose Aveleira-Mata ◽  
Jorge Ondicol-Garcia ◽  
Angel Luis Muñoz-Castañeda ◽  
Isaías García ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Ensemble Methods ◽  
Intrusion Detection Systems ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Classification Models ◽  
Sensors And Actuators ◽  
Detection Systems ◽  
Learning Techniques ◽  
The Internet Of Things

The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems (IDS) are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems (IDS) can be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results.

scholarly journals An adaptive intrusion detection and prevention system for Internet of Things

2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988810
Author(s):  
Sheikh Tahir Bakhsh ◽  
Saleh Alghamdi ◽  
Rayan A Alsemmeari ◽  
Syed Raheel Hassan
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Computer Network ◽  
The Internet ◽  
Detection Systems ◽  
Internet Users ◽  
Prevention System ◽  
Network Technologies ◽  
The Internet Of Things ◽  
Intrusion Detection And Prevention

The revolution of computer network technologies and telecommunication technologies increases the number of Internet users enormously around the world. Thus, many companies nowadays produce various devices having network chips, each device becomes part of the Internet of Things and can run on the Internet to achieve various services for its users. This led to the increase in security threats and attacks on these devices. Due to the increased number of devices connected to the Internet, the attackers have more opportunities to perform their attacks in such an environment. Therefore, security has become a big challenge more than before. In addition, confidentiality, integrity, and availability are required components to assure the security of Internet of Things. In this article, an adaptive intrusion detection and prevention system is proposed for Internet of Things (IDPIoT) to enhance security along with the growth of the devices connected to the Internet. The proposed IDPIoT enhances the security including host-based and network-based functionality by examining the existing intrusion detection systems. Once the proposed IDPIoT receives the packet, it examines the behavior, the packet is suspected, and it blocks or drops the packet. The main goal is accomplished by implementing one essential part of security, which is intrusion detection and prevention system.

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.

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