VLDB 2026 Research / reviewers in the wild / expert
Darshika Khandelwal
dblp:264/9048
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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 |
Cryptographic primitives and cryptanalysis · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic primitives and cryptanalysis
homomorphic encryption |
0.4 | 1 | 2020 | Efficient Confidentiality-Preserving Data Analytics over Symmetrically Encrypted Datasets · Proc. VLDB Endow. 2020 |
Cloud and datacenter computing › cloud security
confidential cloud computing |
0.1 | 1 | 2020 | Efficient Confidentiality-Preserving Data Analytics over Symmetrically Encrypted Datasets · Proc. VLDB Endow. 2020 |
Methods — techniques the papers use, named apart from their topics
multiplicative homomorphic encryption · 0.9additive-homomorphic encryption · 0.4additive homomorphic encryption · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Efficient Confidentiality-Preserving Data Analytics over Symmetrically Encrypted DatasetsabstractIn the past decade, cloud computing has emerged as an economical and practical alternative to in-house datacenters. But due to security concerns, many enterprises are still averse to adopting third party clouds. To mitigate these concerns, several authors have proposed to use partially homomorphic encryption (PHE) to achieve practical levels of confidentiality while enabling computations in the cloud. However, these approaches are either not performant or not versatile enough. We present two novel PHE schemes, an additive and a multiplicative homomorphic encryption scheme, which, unlike previous schemes, are symmetric. We prove the security of our schemes and show they are more efficient than state-of-the-art asymmetric PHE schemes, without compromising the expressiveness of homomorphic operations they support. The main intuition behind our schemes is to trade strict ciphertext compactness for good "relative" compactness in practice, while in turn reaping improved performance. We build a prototype system called Symmetria that uses our proposed schemes and demonstrate its performance improvements over previous work. Symmetria achieves up to 7× average speedups on standard benchmarks compared to asymmetric PHE-based systems. Savvas Savvides, Darshika Khandelwal, Patrick Eugster |
Proc. VLDB Endow. | 2 |