R. Jayanthi
Malicious software typically resides furtively on a user’s computer and interacts with the user’s computing resources. The goal is to improve the trustworthiness of a host and its data by classifying the data to secure the file. Specifically, the new mechanism is provided that ensures the provenance of critical system information and prevents bots from utilizing host resources in peer to peer systems. Data integrity defines the security property which states that the source where a piece of data is generated cannot be spoofed or tampered. This project describes a cryptographic provenance verification approach and applying classification mechanism to find out the ratio of good and bad word count before rejection of original file. This ensures system properties and the system-data integrity, and then the application is demonstrated in the keystroke integrity verification. Specifically, it first designs and implements an efficient cryptographic protocol that provides data integrity. The protocol prevents the imitation of fake key events by malware under the reasonable assumptions. Then demonstrate the provenance verification approach by realizing the lightweight framework. If the verification fails each of the content is compared with trained data set to conclude the content must be malicious to the peer so on the attack basis is just warns the peer, otherwise the file will be received successfully and safe.