Demo Data from SIGIR 2026 / reviewers in the wild / expert
Mahnush Movahedi
dblp:29/7674
· DBLP profile ↗
12ranked-venue papers
4as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 6 · 1 first-authorTheory of computation · 3 · 1 first-authorSecurity and privacy · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
4 papers |
Blockchain and cryptocurrency security · 53% Cryptographic protocols and secure computation · 28% Network security · 19% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Distributed systems · 100% | |
| Theoretical computer science
3 papers |
Coding theory · 84% Algorithmic game theory and mechanism design · 16% | |
| Computer networks
1 paper |
Transport protocols and congestion control · 100% |
Topics — the 14 heaviest of 15, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory
interactive communication |
0.5 | 2 | 2018 | Interactive communication with unknown noise rate · Inf. Comput. 2018 Interactive Communication with Unknown Noise Rate · ICALP (2) 2015 |
Distributed systems › fault tolerance
byzantine fault tolerance |
0.4 | 2 | 2019 | RapidChain: Scaling Blockchain via Full Sharding · CCS 2018 Bootstrapping Public Blockchains Without a Trusted Setup · PODC 2019 |
Distributed systems
consensus |
0.4 | 2 | 2019 | RapidChain: Scaling Blockchain via Full Sharding · CCS 2018 Bootstrapping Public Blockchains Without a Trusted Setup · PODC 2019 |
Blockchain and cryptocurrency security › consensus protocol
permissionless consensus |
0.4 | 1 | 2019 | Bootstrapping Public Blockchains Without a Trusted Setup · PODC 2019 |
Network security › attack resilience › attack mitigation › sybil attack defense
sybil resistance |
0.4 | 1 | 2019 | Bootstrapping Public Blockchains Without a Trusted Setup · PODC 2019 |
Blockchain and cryptocurrency security
blockchain protocols |
0.3 | 1 | 2018 | RapidChain: Scaling Blockchain via Full Sharding · CCS 2018 |
Blockchain and cryptocurrency security › blockchain scalability
blockchain sharding |
0.3 | 1 | 2018 | RapidChain: Scaling Blockchain via Full Sharding · CCS 2018 |
Distributed systems
replication |
0.3 | 1 | 2018 | RapidChain: Scaling Blockchain via Full Sharding · CCS 2018 |
Cryptographic protocols and secure computation › game-theoretic security
rational cryptography |
0.1 | 1 | 2012 | Brief announcement: breaking the O(nm) bit barrier, secure multiparty computation with a static adversary · PODC 2012 |
Cryptographic protocols and secure computation
secure multiparty computation |
0.1 | 1 | 2012 | Brief announcement: breaking the O(nm) bit barrier, secure multiparty computation with a static adversary · PODC 2012 |
Cryptographic protocols and secure computation › secret sharing
rational secret sharing |
0.1 | 1 | 2011 | Scalable rational secret sharing · PODC 2011 |
Cryptographic protocols and secure computation
secret sharing |
0.1 | 1 | 2011 | Scalable rational secret sharing · PODC 2011 |
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
nash equilibrium |
0.1 | 1 | 2011 | Scalable rational secret sharing · PODC 2011 |
Coding theory
channel coding |
0.1 | 1 | 2018 | Interactive communication with unknown noise rate · Inf. Comput. 2018 |
Methods — techniques the papers use, named apart from their topics
gossiping protocol · 0.7block pipelining · 0.7coding for interactive communication · 0.4ε-nash equilibrium · 0.2mechanism design · 0.2synchronous message passing · 0.1circuit computation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Bootstrapping Public Blockchains Without a Trusted SetupabstractWe propose a protocol that allows the participants of a permissionless decentralized system to agree on a set of identities in the presence of a computationally-bounded Byzantine adversary. Our protocol guarantees that the fraction of identities belonging to the adversary in the set of identities is at most equal to the total computational hash power of the adversary. Abhinav Aggarwal, Mahnush Movahedi, Jared Saia, Mahdi Zamani |
PODC | 2 |
| 2018 | RapidChain: Scaling Blockchain via Full ShardingabstractA major approach to overcoming the performance and scalability limitations of current blockchain protocols is to use sharding which is to split the overheads of processing transactions among multiple, smaller groups of nodes. These groups work in parallel to maximize performance while requiring significantly smaller communication, computation, and storage per node, allowing the system to scale to large networks. However, existing sharding-based blockchain protocols still require a linear amount of communication (in the number of participants) per transaction, and hence, attain only partially the potential benefits of sharding. We show that this introduces a major bottleneck to the throughput and latency of these protocols. Aside from the limited scalability, these protocols achieve weak security guarantees due to either a small fault resiliency (e.g., 1/8 and 1/4) or high failure probability, or they rely on strong assumptions (e.g., trusted setup) that limit their applicability to mainstream payment systems. We propose RapidChain, the first sharding-based public blockchain protocol that is resilient to Byzantine faults from up to a 1/3 fraction of its participants, and achieves complete sharding of the communication, computation, and storage overhead of processing transactions without assuming any trusted setup. RapidChain employs an optimal intra-committee consensus algorithm that can achieve very high throughputs via block pipelining, a novel gossiping protocol for large blocks, and a provably-secure reconfiguration mechanism to ensure robustness. Using an efficient cross-shard transaction verification technique, our protocol avoids gossiping transactions to the entire network. Our empirical evaluations suggest that RapidChain can process (and confirm) more than 7,300 tx/sec with an expected confirmation latency of roughly 8.7 seconds in a network of 4,000 nodes with an overwhelming time-to-failure of more than 4,500 years. Mahdi Zamani, Mahnush Movahedi, Mariana Raykova 0001 |
CCS | 2 |
| 2018 | Interactive communication with unknown noise rate
Varsha Dani, Thomas P. Hayes, Mahnush Movahedi, Jared Saia, Maxwell Young |
Inf. Comput. | 3 |
| 2017 | Secure multi-party computation in large networks
Varsha Dani, Valerie King, Mahnush Movahedi, Jared Saia, Mahdi Zamani |
Distributed Comput. | 3 |
| 2015 | Interactive Communication with Unknown Noise Rate
Varsha Dani, Mahnush Movahedi, Jared Saia, Maxwell Young |
ICALP (2) | 2 |
| 2015 | Shuffle to Baffle: Towards Scalable Protocols for Secure Multi-party ShufflingabstractIn secure multi-party shuffling, multiple parties, each holding an input, want to agree on a random permutation of their inputs while keeping the permutation secret. This problem is important as a primitive in many privacy-preserving applications such as anonymous communication, location-based services, and electronic voting. Known techniques for solving this problem suffer from poor scalability, load-balancing issues, trusted party assumptions, and/or weak security guarantees. In this paper, we propose an unconditionally-secure protocol for multi-party shuffling that scales well with the number of parties and is load-balanced. In particular, we require each party to send only a polylogarithmic number of bits and perform a polylogarithmic number of operations while incurring only a logarithmic round complexity. We show security under universal compos ability against up to about n/3 fully-malicious parties. We also provide simulation results in the full version of this paper showing that our protocol improves significantly over previous work. For example, for one million parties, when compared to the state of the art, our protocol reduces the communication and computation costs by at least three orders of magnitude and slightly decreases the number of communication rounds. Mahnush Movahedi, Jared Saia, Mahdi Zamani |
ICDCS | 1 |
| 2015 | Secure Multi-party Shuffling
Mahnush Movahedi, Jared Saia, Mahdi Zamani |
SIROCCO | 1 |
| 2015 | Scalable mechanisms for rational secret sharing
Varsha Dani, Mahnush Movahedi, Jared Saia |
Distributed Comput. | 2 |
| 2014 | Secure Anonymous Broadcast
Mahnush Movahedi, Jared Saia, Mahdi Zamani |
DISC | 1 |
| 2014 | Privacy-Preserving Location-Based Services
Mahnush Movahedi, Mahdi Zamani |
DISC | 1 |
| 2012 | Brief announcement: breaking the O(nm) bit barrier, secure multiparty computation with a static adversaryabstractWe describe scalable algorithms for secure multiparty computation (SMPC). We assume a synchronous message passing communication model, but we do not assume the existence of a broadcast channel. Our main result holds for the case where there are n players, of which a 1/3-ε fraction are controlled by an adversary, for ε any positive constant. We describe an SMPC algorithm for this model that requires each player to send Õ(⁄n+mn + √n) messages and perform Õ(⁄n+mn + √n) computations to compute any function f, where m is the size of a circuit to compute f. We also consider a model where all players are rational. In this model, we describe a Nash equilibrium protocol that solves SMPC and requires each player to send Õ(⁄n+mn) messages and perform Õ(⁄n+mn) computations. These results significantly improve over past results for SMPC which require each player to send a number of bits and perform a number of computations that is Θ(n, m) Varsha Dani, Valerie King, Mahnush Movahedi, Jared Saia |
PODC | 3 |
| 2011 | Scalable rational secret sharingabstractWe consider the classical secret sharing problem in the case where all agents are selfish but rational. In recent work, Kol and Naor show that in the non-simultaneous communciation model (i.e. when rushing is possible), there is no Nash equilibrium that ensures all agents learn the secret. However, they describe a mechanism for this problem that is an ε-Nash equilibrium, i.e. it is close to an equilibrium in the sense that no player can gain more than ε utility by deviating from it. Varsha Dani, Mahnush Movahedi, Yamel Rodriguez, Jared Saia |
PODC | 2 |