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Parthasarathi Panda

dblp:180/5661 · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2026
0000-0003-0071-708XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Security and privacy · 1Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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
1 paper
Privacy and data protection · 100%
Computer networks
1 paper
Content delivery and video streaming · 100%
Theoretical computer science
1 paper
Information theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Content delivery and video streaming › caching
coded caching
0.312018
Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018
Privacy and data protection › web privacy
cache privacy
0.312018
Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018
Privacy and data protection › privacy metrics › privacy quantification
information-theoretic privacy
0.312018
Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018
Information theory › information-theoretic limits
information-theoretic lower bounds
0.112018
Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018

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

information-theoretic bounds · 1.0coded caching · 1.0
YearPublicationVenuePosition
2026 CRAFT: Clustered Regression for Adaptive Filtering of Training Data
Parthasarathi Panda, Asheswari Swain, Subhrakanta Panda
DATA (1)1
2018 Private Coded Caching
abstract
Recent work by Maddah-Ali and Niesen (2014) introduced coded caching which demonstrated the benefits of joint design of storage and transmission policies in content delivery networks. They studied a setup where a server communicates with a set of users, each equipped with a local cache, over a shared error-free link and proposed an order-optimal caching and delivery scheme. In this paper, we introduce the problem of private coded caching where we impose the additional constraint that no user learns any information about the contents of the files it did not request from what is stored in its cache and the server transmissions. We propose a feasible scheme for this setting and demonstrate its order-optimality by deriving information-theoretic lower bounds.
Vaishakh Ravindrakumar, Parthasarathi Panda, Nikhil Karamchandani, Vinod M. Prabhakaran
IEEE Trans. Inf. Forensics Secur.2
2016 Fundamental limits of secretive coded caching
abstract
Recent work by Maddah-Ali and Niesen introduced coded caching which demonstrated the benefits of joint design of storage and transmission policies in content delivery networks. They studied a setup where a server communicates with a set of users, each equipped with a local cache, over a shared error-free link and proposed an order-optimal caching and delivery scheme. In this paper, we introduce the problem of secretive coded caching where we impose the additional constraint that a user should not be able to learn anything, from either the content stored in its cache or the server transmissions, about a file it did not request. We propose a feasible scheme for this setting and demonstrate its order-optimality with respect to information-theoretic lower bounds.
Vaishakh Ravindrakumar, Parthasarathi Panda, Nikhil Karamchandani, Vinod M. Prabhakaran
ISIT2