BlindIDS

Canard, Sébastien; Diop, Aïda; Kheir, Nizar; Paindavoine, M.; Sabt, Mohamed

doi:10.1145/3052973.3053013

Cited by 52 publications

(12 citation statements)

References 13 publications

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“…Existing solutions that may be used to overcome the previous problem rely mainly on searchable encryption based techniques [1][2][3][4][5][6][7]21]. Unfortunately, these techniques suffer from at least one of the following limitations.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, these techniques suffer from at least one of the following limitations. First, the lack of support for pattern-matching with evolving patterns, such as virus signatures which are updated frequently (case of symmetric searchable encryption [2][3][4][5]21]); second, the lack of support for variable pattern lengths (e.g., tokenization-based techniques such as BlindBox [6]); third, the incompleteness of pattern detection methods which yield false negatives (case of BlindIDS [7]); and fourth, the disclosure of detection patterns (case of searchable encryption with shiftable trapdoors [1]). We provide a full comparison with related literature in Section 2.…”

Section: Introductionmentioning

confidence: 99%

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Privacy-Preserving Pattern Matching on Encrypted Data

Bkakria

Cuppens

2020

Advances in Cryptology – ASIACRYPT 2020

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Pattern matching is one of the most fundamental and important paradigms in several application domains such as digital forensics, cyber threat intelligence, or genomic and medical data analysis. While it is a straightforward operation when performed on plaintext data, it becomes a challenging task when the privacy of both the analyzed data and the analysis patterns must be preserved. In this paper, we propose new provably correct, secure, and relatively efficient (compared to similar existing schemes) public and private key based constructions that allow arbitrary pattern matching over encrypted data while protecting both the data to be analyzed and the patterns to be matched. That is, except the pattern provider (resp. the data owner), all other involved parties in the proposed constructions will learn nothing about the patterns to be searched (resp. the data to be inspected). Compared to existing solutions, the constructions we propose has some interesting properties: (1) the size of the ciphertext is linear to the size of plaintext and independent of the sizes and the number of the analysis patterns; (2) the sizes of the issued trapdoors are constant on the size of the data to be analyzed; and (3) the search complexity is linear on the size of the data to be inspected and is constant on the sizes of the analysis patterns. The conducted evaluations show that our constructions drastically improve the performance of the most efficient state of the art solution.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Privacy-Preserving Pattern Matching on Encrypted Data

Bkakria

Cuppens

2020

Advances in Cryptology – ASIACRYPT 2020

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“…MPC or Searchable Encryption [8,36,54,55,59,94,107,108,150,153,182,199,215,216,225,226,228,246,273,274,295,309,311,336,382] (total: 25) Trusted Execution Environment [78,104,157,158,213,271,294,295,328,339,356,357,369,380] (total: 14) Other [137,295,310,337,387] (total: 5)…”

Section: Corporate Network Monitoringmentioning

confidence: 99%

“…A typical setting is to detect or block specific keywords, websites, or content in TLS traffic, usually with no special hardware. MPC or Searchable Encryption [54,55,108,150,182,215,216,226,274,295,304,305,336] (total: 13) Trusted Execution Environment [328] (total: 1)…”

Section: Parental or Educational Controlmentioning

confidence: 99%

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SoK: Content Moderation for End-to-End Encryption

Scheffler

Mayer

2023

PoPETs

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Popular messaging applications now enable end-to-end-encryption (E2EE) by default, and E2EE data storage is becoming common. These important advances for security and privacy create new content moderation challenges for online services, because services can no longer directly access plaintext content. While ongoing public policy debates about E2EE and content moderation in the United States and European Union emphasize child sexual abuse material and misinformation in messaging and storage, we identify and synthesize a wealth of scholarship that goes far beyond those topics. We bridge literature that is diverse in both content moderation subject matter, such as malware, spam, hate speech, terrorist content, and enterprise policy compliance, as well as intended deployments, including not only privacy-preserving content moderation for messaging, email, and cloud storage, but also private introspection of encrypted web traffic by middleboxes. In this work, we systematize the study of content moderation in E2EE settings. We set out a process pipeline for content moderation, drawing on a broad interdisciplinary literature that is not specific to E2EE. We examine cryptography and policy design choices at all stages of this pipeline, and we suggest areas of future research to fill gaps in literature and better understand possible paths forward.

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