Mahdi Zamani

Recent Results in Scalable Multi-Party Computation

Secure multi-party computation (MPC) allows multiple parties to compute a known function over inputs held by each party, without any party having to reveal its private input. Unfortunately, traditional MPC algorithms do not scale well to large numbers of parties. In this paper, we describe several recent MPC algorithms that are designed to handle large networks. All of these algorithms rely on recent techniques from the Byzantine agreement literature on forming and using quorums. Informally, a quorum is a small set of parties, most of which are trustworthy. We describe the advantages and disadvantages of these scalable algorithms, and we propose new ideas for improving practicality of current techniques. Finally, we conduct simulations to measure bandwidth cost for several current MPC algorithms.

A DDoS-Aware IDS Model Based on Danger Theory and Mobile Agents

Most of the security problems in large and distributed information systems are vastly complex. Few research on detection of burgeoning Distributed Denial of Service (DDoS) attacks, leads us to expand our perspectives to a comprehensive architectural approach in which particular issues like arrangement and communication of system components appear. In this paper, many useful ideas from the behaviour of biological immune systems are elicited based on the results of the latest immunological researches, especially Danger Theory. They are applied to create a model for immunization of distributed intrusion detection systems (IDSs) that are resistant to DDoS. Although a general model for various IDSs is proposed and implemented in this research, a particular simulation scenario for detecting DDoS in a wireless sensor network (WSN) is planned as an example to assess the general ability of the proposed model in detecting undesirable events.

Secure multi-party computation in large networks

We describe scalable protocols for solving the secure multi-party computation (MPC) problem among a significant number of parties. We consider both the synchronous and the asynchronous communication models. In the synchronous setting, our protocol is secure against a static malicious adversary corrupting less than a 1/3 fraction of the parties. In the asynchronous environment, we allow the adversary to corrupt less than a 1/8 fraction of parties. For any deterministic function that can be computed by an arithmetic circuit with m gates, both of our protocols require each party to send a number of messages and perform an amount of computation that is

Secure location sharing

\tilde{O}(m/n + \sqrt{n})

RapidChain: Scaling Blockchain via Full Sharding

O~(m/n+n). We also show that our protocols provide statistical and universally-composable security. To achieve our asynchronous MPC result, we define the threshold counting problem and present a distributed protocol to solve it in the asynchronous setting. This protocol is load balanced, with computation, communication and latency complexity of

Shuffle to Baffle: Towards Scalable Protocols for Secure Multi-party Shuffling

O(\log {n})