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Ahmad, Ishtiyaque; Sarker, Laboni; Agrawal, Divyakant; Abbadi, Amr El; Gupta, Trinabh

doi:10.1145/3477132.3483586

Cited by 9 publications

(5 citation statements)

References 54 publications

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“…In 2021, Mughees et al [31] presented OnionPIR, a PIR scheme capable of reducing server response sizes. In the same year, Ahmad et al [32] designed FastPIR, a PIR scheme that decreases server computational costs by increasing client request sizes. In 2023, Mughees and Ren [33] introduced BatchPIR, a PIR scheme based on the BFV encryption scheme that allows for batch processing.…”

Section: Private Information Retrieval (Pir)mentioning

confidence: 99%

A Secure Face Verification Scheme Based on Fully Homomorphic Encryption with Anonymity

Wang,

2024

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With the widespread adoption of cloud computing, the face verification process often requires the client to upload the face to an untrusted cloud server to obtain the verification results. Privacy leakage issues may arise if the client’s private information is not protected. This paper proposes a secure and anonymous face verification scheme using fully homomorphic encryption technology and SealPIR. Our scheme is a three-party solution that requires a third-party server trusted by the client. This scheme not only prevents the client’s facial data from being obtained by untrusted data servers but also prevents the data server from learning the index corresponding to the face that the client wants to verify. In a single-face verification process, the client only needs to perform one upload operation and one download operation, with a communication volume of 264 KB. We can complete a privacy-protected anonymous face verification process in 84.91 ms.

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Section: Private Information Retrieval (Pir)mentioning

confidence: 99%

A Secure Face Verification Scheme Based on Fully Homomorphic Encryption with Anonymity

Wang,

2024

Information

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“…Beams et al [10] proposed a privacypreserving packet scheduling scheme that prevents a malicious adversary from obtaining the victim's private information by launching a side-channel attack and observing how the switch schedules packets. Ahmad et al [27] proposed a new voice communication scheme that enables metadata privacy-preserving voice communication over a completely untrusted infrastructure. However, all the above privacy-preserving resource allocation schemes do not consider malicious edge nodes.…”

Section: Related Workmentioning

confidence: 99%

Metadata-Private Resource Allocation in Edge Computing Withstands Semi-Malicious Edge Nodes

Zhang,

Li,

et al. 2024

Sensors

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Edge computing provides higher computational power and lower transmission latency by offloading tasks to nearby edge nodes with available computational resources to meet the requirements of time-sensitive tasks and computationally complex tasks. Resource allocation schemes are essential to this process. To allocate resources effectively, it is necessary to attach metadata to a task to indicate what kind of resources are needed and how many computation resources are required. However, these metadata are sensitive and can be exposed to eavesdroppers, which can lead to privacy breaches. In addition, edge nodes are vulnerable to corruption because of their limited cybersecurity defenses. Attackers can easily obtain end-device privacy through unprotected metadata or corrupted edge nodes. To address this problem, we propose a metadata privacy resource allocation scheme that uses searchable encryption to protect metadata privacy and zero-knowledge proofs to resist semi-malicious edge nodes. We have formally proven that our proposed scheme satisfies the required security concepts and experimentally demonstrated the effectiveness of the scheme.

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“…The number of rows in the database, number of rows for aggregation, and number of indexes of aggregate queries batched are kept constant batched together fixed at p = 2 14 , r = 2 16 , and u = 6 respectively. The number of rows over which aggregation occurs varies from 2 1 to 2 11 . The experiment is performed with a 256-bit modulus.…”

Section: A Benchmarking Experimentsmentioning

confidence: 99%

“…It is thus also limited in the aggregations it can support. Ahmad et al [11] proposes a scheme somewhat similar to what our protocol aims to achieve. They present a system for oblivious document ranking and retrieval with a pipeline for sending keywords to a server, a ranked list of documents sent back by the server in response, and one of the documents selected and opened.…”

Section: B Benchmarking Query Throughput On Cpumentioning

confidence: 99%

Private Aggregate Queries to Untrusted Databases

Hafiz,

Gupta,

Wnuck

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

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An essential part of ensuring privacy for internet service users is to protect what data they access so that the database host cannot infer sensitive information (e.g., political affiliation, sexual orientation, etc.) from the query pattern to exploit it or share it with third parties. Often, database users submit aggregate queries (e.g., SUM, MEAN, etc.) with searching and filtering constraints to extract statistically meaningful information from a database by seeking the privacy of its query's sensitive values and database interactions. Private information retrieval (PIR), a privacy-preserving cryptographic tool, solves a simplified version of this problem by hiding the database item that a client accesses. Most PIR protocols require the client to know the exact row index of the intended database item, which cannot support the complicated aggregation-based statistical query in a similar setting. Some works in the PIR space contain keyword searching and SQL-like queries, but most need multiple interactions between the PIR client and PIR servers. Some schemes support searching SQL-like expressive queries in a single round but fail to enable aggregate queries. These schemes are the main focus of this paper. To bridge the gap, we have built a general-purpose novel information-theoretic PIR (IT-PIR) framework that permits a user to fetch the aggregated result, hiding all sensitive sections of the complex query from the hosting PIR server in a single round of interaction. In other words, the server will not know which records contribute to the aggregation. We then evaluate the feasibility of our protocol for both benchmarking and real-world application settings. For instance, in a complex aggregate query to the Twitter microblogging database of 1 million tweets, our protocol takes 0.014 seconds for a PIR server to generate the result when the user is interested in one of ∼ 3𝑘 user handles. In contrast, for a much-simplified task, not an aggregate but a positional query, Goldberg's regular IT-PIR (Oakland 2007) takes 1.13 seconds. For all possible user handles, 300𝑘, it takes equal time compared to the regular IT-PIR. This example shows that complicated aggregate queries through our framework do not incur additional overhead if not less, compared to the conventional query.

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Coeus

Cited by 9 publications

References 54 publications

A Secure Face Verification Scheme Based on Fully Homomorphic Encryption with Anonymity

A Secure Face Verification Scheme Based on Fully Homomorphic Encryption with Anonymity

Metadata-Private Resource Allocation in Edge Computing Withstands Semi-Malicious Edge Nodes

Private Aggregate Queries to Untrusted Databases

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