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Ashish Malgi

dblp:69/774 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Privacy and data protection
anonymity
0.112005
MuON: Epidemic Based Mutual Anonymity · ICNP 2005
Network security
anonymity networks
0.112005
MuON: Epidemic Based Mutual Anonymity · ICNP 2005
Network security › anonymity networks › anonymous communication
mutual anonymity
0.112005
MuON: Epidemic Based Mutual Anonymity · ICNP 2005
Network security › anonymity networks
peer-to-peer anonymity
0.112005
MuON: Epidemic Based Mutual Anonymity · ICNP 2005
Distributed systems
peer-to-peer systems
0.012005
MuON: Epidemic Based Mutual Anonymity · ICNP 2005

Methods — techniques the papers use, named apart from their topics

simulation · 0.1epidemic data dissemination · 0.1
YearPublicationVenuePosition
2008 MuON: Epidemic based mutual anonymity in unstructured P2P networks
Neelesh Bansod, Ashish Malgi, Byung Kyu Choi, Jean Mayo
Comput. Networks2
2005 MuON: Epidemic Based Mutual Anonymity
abstract
A 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
ICNP2