scholarly journals Energy Efficient and Secured MQTT Protocol using IoT

2020 ◽  
Vol 9 (4) ◽  
pp. 11-14
Keyword(s):  
Data Transmission ◽  
Energy Efficient ◽  
Communication Protocol ◽  
Denial Of Service ◽  
Smart Devices ◽  
Smart Device ◽  
Simulation Tool ◽  
Malicious Nodes ◽  
Denial Of Service Attack ◽  
Service Attack

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.

scholarly journals Threshold-Based Method for Detection of Distributed Denial of Service Attack in IoT

2019 ◽  
Vol 8 (4) ◽  
pp. 3002-3007
Keyword(s):  
Internet Of Things ◽  
Network Performance ◽  
Denial Of Service ◽  
Research Work ◽  
Distributed Denial Of Service ◽  
Malicious Nodes ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Malicious Node Detection ◽  
The Internet Of Things

The internet of things is the decentralized type of network in which sensor devices can join or leave the network when they want. Due to such nature of the network malicious nodes enter the network which affects network performance in terms of certain parameters. This research work is based on the detection and isolation of distributed denial of service attack in internet of things. The distributed denial of service attack is the denial of service type attack which affects network performance to large extent. In the existing techniques there are two main drawbacks. The first drawback is that the technique does not pin point malicious nodes from the network. The second drawback is that the malicious node detection time is very high. In this research, the new technique will be proposed for the isolation of malicious nodes from the network. In this technique, similarity of the traffic is analyzed using the cosine similarity. The sensor node which is generated dissimilar type of traffic is detected as malicious nodes. The proposed technique has been implemented in MATLAB and results have been analyzed in terms of certain parameters. It is expected that proposed technique detect malicious nodes in least amount of time.

scholarly journals Securing the IOT Devices with Artificial Immune System

2019 ◽  
Vol 9 (2) ◽  
pp. 5193-5196
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Denial Of Service ◽  
Artificial Immune ◽  
Malicious Nodes ◽  
Denial Of Service Attack ◽  
Man In The Middle ◽  
Service Attack ◽  
Iot Devices ◽  
High Level

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.

scholarly journals Detection of Blackhole Attacks in Wireless Sensor Networks

2019 ◽  
Vol 8 (11S) ◽  
pp. 1203-1205
Keyword(s):  
Sensor Networks ◽  
Data Storage ◽  
Denial Of Service ◽  
Information Storage ◽  
Third Party ◽  
Smart Devices ◽  
Denial Of Service Attack ◽  
Digital World ◽  
Publication Procedure ◽  
Service Attack

Information storage and security is one of key areas where much research is been done in this digital world where we communicate the data over using third party devices such as cloud by using smart devices such as mobiles so the security is an quite challenging factor where we access our data across the globe and with the social media coming into factor for the storage and accessibility of the data so there are many risk factors coming into process so we need to implement a smart and secure system for the authentication threats so here in this paper we implement a smart system in which face recognition aunthication system is implement between the cloud and mobile activity which give more security in terms of data storage and communication and then we evaluate using different graphs and also analyses the attacksThe Remote Sensor Networks (WSN) are subjected to different assaults in which Blackhole a sort of Denial of Service attack(DoS) assaults is exceptionally hard to distinguish and secure. Inblackholeattack,theviolater catches and reprograms lot of hubs in system to hinder bundles they get as opposed to sending them towards the base station.The data ensures the malicious node and when it enters the zone it will be known and cannot be allowed into the field and very less output may occur. The lesser amount measure of work is improved the situation location and anticipation of blackhole assault in the WSN making its recognition and aversion extremely critical according to organize perfomance is assured.In our concept at first the effect of blackhole assault to be estimated on the system limitations pursued by proposition of a publication procedure for discovery & avoidance of blackhole assault in WSN.

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