Leakage-Abuse Attacks Against Searchable Encryption

By David Cash, Paul Grubbs, Jason Perry, Thomas Ristenpart. IACR Cryptology ePrint Archive, 2015

678 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/9aa8bf1e8028b9e5074e2f59c5d7bb65bc8d0adb

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Citations in the corpus

From Keys to Databases - Real-World Applications of Secure Multi-Party Computation (2018, background): “These admittedly leaky schemes [12] are part of Jana so that we can characterize performance-leakage trade-offs in diverse applications, with the goal of charting out some small part of that trade-space during the course of our research.”
SGX-LKL: Securing the Host OS Interface for Trusted Execution (2019, methodology): “tiﬁers for I/O operations, event handling and threading. Similar to address ranges, passing identiﬁers to the host reveals access patterns. For example, for database searches using a TEE, Cash et al. [17] show that an adversary can learn queries by observing record accesses. Generally, pure identiﬁe”
PanORAMa: Oblivious RAM with Logarithmic Overhead (2018, background): “This is leakage that is not only ruled out by the strong formal definition of privacy preserving data outsourcing but has also been proven to be detrimental in many practical outsourcing settings [1], [2].”
Analyzing Information Leakage of Updates to Natural Language Models (2019, background): “earchable encryption. An attacker who has control over data in an update to an encrypted database can learn information about the content of the database as well as previous encrypted searches on it (Cash et al., 2015). Pan-privacy (Dwork et al., 2010), on the other hand, studies the problem of main”
All Your Queries Are Belong to Us: The Power of File-Injection Attacks on Searchable Encryption (2016, methodology): “Compared to prior work [10, 4], our attacks are both more effective in terms of the fraction of queries recovered and far less demanding in terms of the prior information the server knows.”
∑oφoς: Forward Secure Searchable Encryption (2016, background): “For larger leakage, the authors of [CGPR15] show that full plaintext recovery of the encrypted database is possible.”
Generic Attacks on Secure Outsourced Databases (2016, background): “Thus, unlike prior work [28, 3, 31, 11, 38] our adversary is passive (does not choose the queries) and does not get any auxiliary information about the data.”
Forward and Backward Private Searchable Encryption from Constrained Cryptographic Primitives (2017, background): “Amid a growing awareness of privacy concerns however, a diﬀerent line of work has uncovered devastating and fairly generic attacks against many SSE schemes [CGPR15, ZKP16].”
A Pragmatic Introduction to Secure Multi-Party Computation (2019, background): “Several attacks have shown that data leaked for the sake of e ciency can often be exploited (Islam et al., 2012; Naveed et al., 2015; Cash et al., 2015).”
Inference Attacks on Property-Preserving Encrypted Databases (2015, positive): “Furthermore, a recent study by Cash, Grubbs, Perry and Ristenpart [18] shows that the accuracy of the IKK attack is so low that it is not usable in practice (unless the adversary already knows most of the underlying data).”