| Title | : | Secure Multiparty Computation and its Application to Graph Analysis |
| Speaker | : | Nishat Koti (IISc) |
| Details | : | Thu, 26 Sep, 2024 10:00 AM @ MR1 or SSB 233 |
| Abstract: | : | The growing volumes of data being collected and its analysis to provide better services are creating worries about digital privacy. To address privacy concerns and give practical solutions, the literature has relied on secure multiparty computation (MPC) techniques. MPC enables a set of distrusting parties to carry out a joint computation on their inputs while ensuring that parties only learn the output and nothing beyond. MPC finds use in various domains such as healthcare, finance, and even the social sectors, facilitating privacy-preserving applications including but not limited to machine learning, fraud detection, recommendation systems, etc. In this talk, we will focus on the use-case of performing privacy-preserving computations on graph-structured data.
In general, privacy-preserving graph analysis allows performing computations on graphs that store sensitive information, while ensuring all the information about the topology of the graph as well as data associated with the nodes and edges remains hidden. The current work addresses this problem by designing a highly scalable framework, Graphiti, that allows securely realising any graph algorithm. Graphiti relies on the technique of secure multiparty computation (MPC) to design a generic framework that improves over the state-of-the-art framework of GraphSC by Araki et al. (CCS’21). The key technical contribution is that Graphiti has round complexity independent of the graph size, which in turn allows attaining the desired scalability. We also benchmark the performance of Graphiti to showcase its practicality.
This is a joint work with Varsha Bhat Kukkala, Arpita Patra and Bhavish Raj Gopal, and has been accepted to ACM CCS 2024.
Bio: Nishat Koti obtained her PhD from the Indian Institute of Science, Bangalore, where she was working with Prof. Arpita Patra. She then undertook a post-doctoral research position at TU Darmstadt, Germany. Prior to this, she obtained her M.Tech and B.Tech degrees in Computer Science and Engineering from the National Institute of Technology Goa. Nishat Koti works in the area of secure multiparty computation (MPC), with a focus on designing MPC protocols for privacy-conscious applications such as machine learning and graph algorithms. |
