VSS: A Storage System for Video Analytics

Haynes, Brandon; Daum, Maureen; He, D.; Mazumdar, Amrita; Balazinska, Magdalena; Cheung, Alvin; Ceze, Luís

doi:10.1145/3448016.3459242

Cited by 15 publications

(2 citation statements)

References 23 publications

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“…To illustrate the performance bottleneck of state-of-the-art HE schemes in the video analysis ecosystem [12,19], we provide a real-life example. In scenarios where existing data is updated or new data arrives, Symmetria [36], the best option available, can only (re-)encrypt the entire dataset.…”

Section: Motivation and Objectivesmentioning

confidence: 99%

Homomorphic Encryption Technology for Cloud Computing

Yang

2019

Procedia Computer Science

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Section: Motivation and Objectivesmentioning

confidence: 99%

Homomorphic Encryption Technology for Cloud Computing

Yang

2019

Procedia Computer Science

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“…Although SHE delivers much faster encryption than the conventional PHE, both schemes assume that the underlying data is static. That is, they are not designed for frequentlyupdated data or streaming data that are commonly found in applications like video analysis [11,19]. If existing data are updated or new data arrive, the best a SHE scheme can do is to (re-)encrypt the data in its entirety.…”

Section: Introductionmentioning

confidence: 99%

INCHE: High-Performance Encoding for Relational Databases through Incrementally Homomorphic Encryption

Zhao

2021

Preprint

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Homomorphic encryption (HE) offers data confidentiality by executing queries directly on encrypted fields in the database-as-a-service (DaaS) paradigm. While fully HE exhibits great expressiveness but prohibitive performance overhead, a better balance between flexibility and efficiency can be achieved by partially HE schemes. Performance-wise, however, the encryption rate of state-of-theart HE schemes is still orders of magnitude lower than the I/O throughput, rendering the HE scheme the performance bottleneck.This paper proposes INCHE, an incrementally homomorphic encryption scheme, which aims to boost the performance of HE schemes by incrementally encrypting fields in relational databases.The key idea of INCHE is to explore the intrinsic correlation between plaintexts and cache them for future reuse such that expensive HE primitives from plaintexts to ciphertexts are avoided. We prove the semantic security of INCHE under the chosen-plaintext attack (CPA) model and show that its time complexity is linear in the plaintext length. We implement an INCHE prototype by extending the Symmetria cryptosystem and verify its effectiveness on both randomly-generated data and the TPC-H benchmark.

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