Demo Data from EDBT 2026 / reviewers in the wild / expert
Ashish Malgi
dblp:69/774
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2
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
1 paper |
Network security · 75% Privacy and data protection · 25% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection
anonymity |
0.1 | 1 | 2005 | MuON: Epidemic Based Mutual Anonymity · ICNP 2005 |
Network security
anonymity networks |
0.1 | 1 | 2005 | MuON: Epidemic Based Mutual Anonymity · ICNP 2005 |
Network security › anonymity networks › anonymous communication
mutual anonymity |
0.1 | 1 | 2005 | MuON: Epidemic Based Mutual Anonymity · ICNP 2005 |
Network security › anonymity networks
peer-to-peer anonymity |
0.1 | 1 | 2005 | MuON: Epidemic Based Mutual Anonymity · ICNP 2005 |
Distributed systems
peer-to-peer systems |
0.0 | 1 | 2005 | MuON: Epidemic Based Mutual Anonymity · ICNP 2005 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.1epidemic data dissemination · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | MuON: Epidemic based mutual anonymity in unstructured P2P networks
Neelesh Bansod, Ashish Malgi, Byung Kyu Choi, Jean Mayo |
Comput. Networks | 2 |
| 2005 | MuON: Epidemic Based Mutual AnonymityabstractA mutually anonymous service hides the identity of a client from the service provider and vice-versa. Providing mutual anonymity usually requires a large number of participants. While peer-to-peer (P2P) networks are capable of recruiting a large number of participants, reliable anonymous communication in these architectures, with low bandwidth usage, still needs further investigation. This paper presents MuON, a protocol to achieve mutual anonymity in unstructured P2P networks. MuON leverages epidemic-style data dissemination to deal with the high churn (changes in system membership) characteristic of unstructured P2P networks. The results from our security analysis and simulation show that MuON provides mutual anonymity over unstructured P2P networks while maintaining predictable latencies, high reliability, and low communication overhead Neelesh Bansod, Ashish Malgi, Byung Kyu Choi, Jean Mayo |
ICNP | 2 |