scholarly journals Securing the IOT Devices with Artificial Immune System

Security is the main concern for IOT devices as are expected to share a lot of crucial information about the user and his surroundings. The traditional security mechanisms are ineffective against sophisticated and advanced security attacks such as Man in the Middle Attack, Denial of Service attack, Identity cloning. Different solutions have been proposed for user authentication. Device authentication is crucial in IOT environment and cannot be neglected. Despite this device authentication has not gained equal attention from the research community. The aim of this research is to develop a lightweight and robust device authentication algorithm by Artificial Immune System to ensure data integrity in IoT networks. The concepts of Artificial Immune system are utilized for generating a non-redundant device signature which is used to differentiate between authentic and malicious nodes. The device signature is generated dynamically and is non reusable. This property makes the proposed algorithm secure against numerous high-level attacks such as frequency analysis attacks, Man in the Middle attack, side channel attacks, Denial of Service attack. The developed algorithm is tested in real time and prevents malicious nodes from entering the network. In addition to being immune against the high level attacks the proposed algorithm functions with low communication cost. The proposed algorithm can be used for providing security in IOT devices with limited battery life and processing power such as IOT enabled and remotely deployed Wireless Sensor Networks for forest fire detection, power plant monitoring , remote military applications and many others.

2019 ◽  
Vol 8 (1) ◽  
pp. 486-495 ◽  
Author(s):  
Bimal Kumar Mishra ◽  
Ajit Kumar Keshri ◽  
Dheeresh Kumar Mallick ◽  
Binay Kumar Mishra

Abstract Internet of Things (IoT) opens up the possibility of agglomerations of different types of devices, Internet and human elements to provide extreme interconnectivity among them towards achieving a completely connected world of things. The mainstream adaptation of IoT technology and its widespread use has also opened up a whole new platform for cyber perpetrators mostly used for distributed denial of service (DDoS) attacks. In this paper, under the influence of internal and external nodes, a two - fold epidemic model is developed where attack on IoT devices is first achieved and then IoT based distributed attack of malicious objects on targeted resources in a network has been established. This model is mainly based on Mirai botnet made of IoT devices which came into the limelight with three major DDoS attacks in 2016. The model is analyzed at equilibrium points to find the conditions for their local and global stability. Impact of external nodes on the over-all model is critically analyzed. Numerical simulations are performed to validate the vitality of the model developed.


Author(s):  
Ankur Dumka ◽  
Hardwari Lal Mandoria ◽  
Anushree Sah

The chapter surveys the analysis of all the security aspects of software-defined network and determines the areas that are prone to security attacks in the given software-defined network architecture. If the fundamental network topology information is poisoned, all the dependent network services will become immediately affected, causing catastrophic problems like host location hijacking attack, link fabrication attack, denial of service attack, man in the middle attack. These attacks affect the following features of SDN: availability, performance, integrity, and security. The flexibility in the programmability of control plane has both acted as a bane as well as a boon to SDN. Like the ARP poisoning in the legacy networks, there are several other vulnerabilities in the SDN architecture as well.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2932
Author(s):  
Ivan Vaccari ◽  
Maurizio Aiello ◽  
Enrico Cambiaso

Security of the Internet of Things is a crucial topic, due to the criticality of the networks and the sensitivity of exchanged data. In this paper, we target the Message Queue Telemetry Transport (MQTT) protocol used in IoT environments for communication between IoT devices. We exploit a specific weakness of MQTT which was identified during our research, allowing the client to configure the behavior of the server. In order to validate the possibility to exploit such vulnerability, we propose SlowITe, a novel low-rate denial of service attack aimed to target MQTT through low-rate techniques. We validate SlowITe against real MQTT services, considering both plain text and encrypted communications and comparing the effects of the threat when targeting different daemons. Results show that the attack is successful and it is able to exploit the identified vulnerability to lead a DoS on the victim with limited attack resources.


Internet of Things is a distributed collection of smart devices, where the smart device communicates with each other using Device to Device (D2D communication. Due to the resource constraint nature of IOT, the lightweight communication protocol is needed. Message Querying Telemetry Transport (MQTT) is one of the lightweight communication protocol which employs publish and subscribe method. The most of existing MQTT protocols are vulnerable to Denial of Service attack. In order to overcome the issues of the existing system, in this work a novel lightweight protocol by name EES-MQTT (Energy Efficient and Secured MQTT) is proposed which can be able to provide efficient authentication during data transmission by identifying the intruders and removing the malicious nodes. Moreover, the proposed protocol can be able to provide security with better energy optimization. The feasibility of EES-MQTT is carried out using MQTT.fx simulation tool and the Eclipse Paho. The results from the simulation proves that the EES-MQTT reduces impact of malicious nodes and optimizes the energy consumption during the data transmission.


2021 ◽  
Vol 11 (4) ◽  
pp. 1847
Author(s):  
Ladislav Huraj ◽  
Tibor Horak ◽  
Peter Strelec ◽  
Pavol Tanuska

Industry 4.0 collects, exchanges, and analyzes data during the production process to increase production efficiency. Internet of Things (IoT) devices are among the basic technologies used for this purpose. However, the integration of IoT technology into the industrial environment faces new security challenges that need to be addressed. This is also true for a production line. The production line is a basic element of industrial production and integrating IoT equipment allows one to streamline the production process and thus reduce costs. On the other hand, IoT integration opens the way for network cyberattacks. One possible cyberattack is the increasingly widely used distributed denial-of-service attack. This article presents a case study that demonstrates the devastating effects of a DDOS attack on a real IoT-based production line and the entire production process. The emphasis was mainly on the integration of IoT devices, which could potentially be misused to run DDoS. Next, the verification of the proposed solution is described, which proves that it is possible to use the sampled flow (sFlow) stream to detect and protect against DDoS attacks on the running production line during the production process.


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