PROJECT TITLE :

Towards Building Forensics Enabled Cloud Through Secure Logging-as-a-Service

ABSTRACT:

Collection and analysis of varied logs (e.g., method logs, network logs) are fundamental activities in computer forensics. Ensuring the security of the activity logs is so crucial to ensure reliable forensics investigations. But, as a result of of the black-box nature of clouds and therefore the volatility and co-mingling of cloud knowledge, providing the cloud logs to investigators while preserving users' privacy and the integrity of logs is difficult. The present secure logging schemes, that consider the logger as trusted can't be applied in clouds since there is a likelihood that cloud providers (logger) collude with malicious users or investigators to alter the logs. In this paper, we have a tendency to analyze the threats on cloud users' activity logs considering the collusion between cloud users, providers, and investigators. Based mostly on the threat model, we propose Secure-Logging-as-a-Service ( SecLaaS), which preserves varied logs generated for the activity of virtual machines running in clouds and ensures the confidentiality and integrity of such logs. Investigators or the court authority will only access these logs by the RESTful APIs provided by SecLaaS, that ensures confidentiality of logs. The integrity of the logs is ensured by hash-chain theme and proofs of past logs printed periodically by the cloud suppliers. In prior analysis, we have a tendency to used two accumulator schemes Bloom filter and RSA accumulator to make the proofs of past logs. During this paper, we propose a new accumulator scheme - Bloom-Tree, which performs higher than the opposite two accumulators in terms of time and area requirement.