Performance Analysis of Scattered Record Utilizing Block chain for Identifying Visual Substance Imitation

Visual content captured by monitoring devices are vulnerable to local or remote malicious modifications of visual information by offenders. These malicious visual content code changes (called forgeries) are divided into Cloning, Splicing, Inter-frame and Intra-frame forgeries. Rapidly improving editing software tools have made visual content manipulation feasible. Consequently, malicious attackers are trying to manipulate the visual content. Detecting visual content tampering is a major need for many applications Distributed databases can be used to detect visual content tampering by storing the evidence created by hashing the visual content at the source itself. However, these distributed databases lack in data transparency and security against Byzantine failures in an untrusted environment. Blockchain is a technology with the inherent ability to store data in a chronological chained link of events: establishing an irrefutable database. Using cryptographic hashes together with blockchain one can generate cryptographic hashes of the data content from a video recording, and consequently transmit these hashes to a blockchain. In this thesis we have proposed a model called Evidence chain based on Blockchain to ensure the credibility of the visual content. Unlike bitcoin which is a digital currency the proposed system documents content hash by using IPFS, Hash based technology, RSA, Elliptic Curve Cryptography. Image and Video segments are hashed and stored in chronological order as a chain of blocks which are detectable and non-altering guaranteeing the validity of the information. This research is significant in establishing the trust between any two parties.