Zulfa Shaikh

Single and Multi Trusted Third Party: Comparison, Identification and Reduction of Malicious Conduct by Trusted Third Party in Secure Multiparty Computing Protocol

SMC is a problem of n parties with inputs (x1, x2…xn) , hand over their inputs to third party for computation f(x1, x2…xn) and third party announces the result in the form of y. During joint computation of inputs, all the organizations involved in computation wish to preserve privacy of their inputs. So need is to define a protocol which maintains privacy, security and correctness parameters of SMC. In this paper, single third party and multi third party model are defined and compared. The probabilistic evidences for single and multi third party SMC model have been analyzed with security analysis graphs. In this paper, we have also worked on identification and reduction of malicious conduct of TTPs in multi TTP environment.

Congestion Control during Data Privacy in Secure Multiparty Computation

In this paper, we propose the methodology and design an algorithm to control congestion during Secure Multiparty Computation (SMC). As per our literature serve a lot of work has been done in SMC but they have worked only the main part of the SMC, privacy and correctness. Congestion control is one of the important components for the performance of the network and also is the most challenging one. This paper deals with the way of shaping the traffic to improve quality of service (QoS) in SMC. Under the congestion situation, the queue length may become very large in a short time, resulting in buffer overflow a\nd packet loss. So congestion control is necessary to ensure that users get the negotiated QoS. The objectives of traffic control and congestion control for SMC are: Support a set of QoS parameters and minimize network and endsystem complexity while maximizing network utilization. In our paper we carried out experiments for computing the FIFO length that ensures zero packet loss for different clock rate of the router.

Analysis of Data in Secure Multiparty Computation

A protocol is secure if the parties who want to compute their inputs hands it to the trusted parties. Trusted parties in turn compute the inputs using the function f and give the result to the respective parties after computation in such a way that no party can identify others party data. During computation of inputs, we had considered the factor, what if trusted third parties are malicious? Considering different probabilities for the malicious users, we have tried to find out the correctness of the result and percentage of system acceptability. We then tried to increase the number of TTPs in order to get the accuracy of the result. The aim of our proposed work is to identify what probability of malicious users will lead to the system in an unacceptable state.