Research Area:  Blockchain Technology

Abstract:

Blockchain is one of the fast growing technologies that has significant role in the area of criminal investigation. The security is becoming a great threat to all the industries, Electronic Health Record (EHR), Banking, Smart Applications (SA), Supply Chain Management (SCM) and IoT environment in recent years. In this research, we have developed a novel framework that will monitor the activities that takes place on particular data evidence, We create a Cloud based Software Defined Network (SDN), its consists of 100 - mobile Nodes (IOT devices), open flow switch and Blockchain based controllers, cloud server, Authentication Server (AS) and investigator. Initially all users are registered with AS and obtain their secret key from AS based on the Harmony Search Optimization (HSO). In the mobile nodes the packets are encrypted by using Elliptic Curve Integrated Encryption Scheme (ECIES) algorithm and transfer to the cloud server. SDN controller maintains blockchain to preserve evidences collected from data and signature of the users based on the SHA-256 Cryptographic Hash Algorithm. Authorized investigator performs following processes: identification, evidence collection, evidence analysis, and report generation based on the Logical Graph of Evidences (LGoE). we plot the resultant graph for Response time versus Number of users, Evidence insertion time versus number of users, Evidence verification time versus Number of users, Computational overhead versus number of users, Total change rate versus Number of users, Hash computation time versus number of users, Key generation time versus number of users, Encryption time versus number of users and Decryption time versus number of users. Finally, the investigator or other legal people can obtain the evidences from the controller and construct as a Logical Graph of Evidence (LGoE). The experimental analysis revealed the fact that the proposed system obtained better performance in terms of response time, accuracy, increasing throughput and total change security parameters.

Keywords:  

Author(s) Name:  P. Velmurugadass, S. Dhanasekaran, S. Shasi Anand, V. Vasudevan

Publisher name:  Elsevier

DOI:  10.1016/j.matpr.2020.08.519

Volume Information:  Volume 37, Part 2, 2021, Pages 2653-2659

Paper Link:   https://www.sciencedirect.com/science/article/pii/S2214785320364014