ESDAM – Efficient and Secure Data Aggregation against Malicious Nodes in Iot Environment
Veerabadrappa1, Girisha M N2, P M Booma3
1Veerabadrappa*, Data Warehouse Engineer in the Banking Domain of Software Industry, Malaysia.
2Girisha M N, Master of Engineering in Bioinformatics from Department of CSE, UVCE College of Engineering affiliated to Bangalore University.
3Booma Poolan Marikannan, lecturer in School of Computing, Asia Pacific University of Technology & amp, Innovation, Malaysia.
Manuscript received on November 14, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 689-697 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6713129219/2019©BEIESP | DOI: 10.35940/ijitee.B6713.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Rapid expansion of IoT technologies and their devices has created the considerable convenience in the daily lives of the people. Modernization of technique in IoT has allowed them to perform just more than sensing that directly means the more energy consumption. It is a known fact that most of the IoT devices have the limited power supply and hence it is an obvious need to design the energy efficient model. Despite of IoT devices being so useful in daily life and in other industries, data security is one of the primary concern in the fields of IoT application such as healthcare, agriculture, defense etc., and it is a challenging task to provide the data security in these fields. In past, several methods have been proposed to address this challenge, however, either they failed to provide the security or they lack from the efficiency. In this paper, it introduces a methodology named as ESDAM (Efficient and Secure Data Aggregation against Malicious Nodes) that provides better security with improved efficiency. The proposed methodology is parted into two methods, which helps in discerning the malicious nodes. First method, is through extending coordinates and the second method, is through surveilling the adjacent nodes. Extensive simulation has been performed by applying various constraints through persuading various number of malicious and performance metrics such as energy utilization, number of failed nodes, packet mismatch rate and packet discern rate. The performance evaluation of the simulation results proves that proposed methodology performs better than the existing methods.
Keywords: IoT Security, Malicious Nodes, Secure Data Aggregation
Scope of the Article: IoT