Biblio

The use of video surveillance (VS) has grown significantly using the internet as a platform. Thus security issues on such videos must be addressed. Video frames can have multiple objects and various features over video length. Moving object detection (MOD) and real-time tracking requires security strategies designed to protect videos. This paper is proposed to design an asymmetric encryption method (RSA). The paper has contributed in two stages. In the first phase the fast video segmentation method based on a global variable threshold is designed to facilitate MOD. Later in second pass the RSA-based encryption is used to maintain the efficiency of the object detection. The secure key generation method is demonstrated. The performances of two global thresholds are demonstrated and compared under the encrypted video data. It is found that that method is very effective in finding objects under the context of video surveillance in real time.

Named Data Networking (NDN) is an emerging network architecture, which is built by keeping data as its pivotal point. The in-network cache, one of the important characteristics, makes data packets to be available from multiple locations on the Internet. Hence data access control and their enforcement mechanisms become even more critical in the NDNs. In this paper, we propose a novel encryption-based data access control scheme using Role-Based Encryption (RBE). The inheritance property of our scheme provides a natural way to achieve efficient data access control over hierarchical content. This in turn makes our scheme suitable for large scale real world content-centric applications and services such as Netflix. Further, the proposed scheme introduces an anonymous signature-based authentication mechanism to reject bogus data requests nearer to the source, thereby preventing them from entering the network. This in turn helps to mitigate better denial of service attacks. In addition, the signature mechanism supports unlinkability, which is essential to prevent leakages of individual user's access patterns. Another major feature of the proposed scheme is that it provides accountability of the Internet Service Providers (ISPs) using batch signature verification. Moreover, we have developed a transparent and secure dispute resolution and payment mechanism using smart-contract and blockchain technologies. We present a formal security analysis of our scheme to show it is provably secure against Chosen Plaintext Attacks. We also demonstrate that our scheme supports more functionalities than the existing schemes and its performance is better in terms of computation, communication and storage.

The contemporary struggle that rests upon security risk assessment of Information Systems is its feasibility in the presence of an indeterminate environment when information is insufficient, conflicting, generic or ambiguous. But as pointed out by the security experts, most of the traditional approaches to risk assessment of information systems security are no longer practicable as they fail to deliver viable support on handling uncertainty. Therefore, to address this issue, we have anticipated a comprehensive risk assessment model based on Bayesian Belief Network (BBN) and Fuzzy Inference Scheme (FIS) process to function in an indeterminate environment. The proposed model is demonstrated and further comparisons are made on the test results to validate the reliability of the proposed model.