Foundations of Cryptography
By H. Anand, Kushal Gupta. 2007
Subfields: Privacy & Security
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Privacy & Security
- David E. Evans
- Jonathan Katz
- Yan Huang
- Adrià Gascón
- Benny Pinkas
- Yehuda Lindell
- Thomas Schneider
- Matt J. Kusner
Citations in the corpus
- Generalization in anti-causal learning (2018, background): “Those are functions that can be computed in polynomial time, but the probability for any randomized algorithm to find an inverse is negligible, see e.g., (Goldreich, 2001).”
- Blind Justice: Fairness with Encrypted Sensitive Attributes (2018, background): “In MPC, privacy in the case of semi-honest adversaries is argued in the simulation paradigm (see (Goldreich, 2004) or (Lin-dell, 2016) for formal definitions and detailed proofs).”
- Fast, Privacy Preserving Linear Regression over Distributed Datasets based on Pre-Distributed Data (2015, methodology): “define (exact) secure two-party computation following Goldreich [17].”
- Building castles out of mud: practical access pattern privacy and correctness on untrusted storage (2008, unknown): “We require three cryptographic primitives with all the associated semantic security [13] properties: (i) a secure, collision-free hash function which builds a distribution from its input that is indistinguishable from a uniform random distribution, (ii) an encryption function that generates unique…”
- Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges (2017, background): “encryption plays a key role and encodes the information in such a way that only authorized user can read it in a correct way [112].”
- Secure k-nearest neighbor query over encrypted data in outsourced environments (2013, background): “The protocols developed in this paper are secure under the semi-honest model [14].”
- ANONIZE: A Large-Scale Anonymous Survey System (2014, unknown): “We assume the reader is familiar with signature schemes secure against adaptive-chosen message attacks [26], non-interactive commitment schemes [27], and pseudorandom functions [28]; see [29].”
- Private Set Intersection: Are Garbled Circuits Better than Custom Protocols? (2012, methodology): “This level of privacy is implied by the standard notion of security in the semi-honest setting [12] that we use in this work.”
- I Don't Want to Think About it Now: Decision Theory with Costly Computation (2010, unknown): “We omit the formal definition of an interactive Turing machine (see, for example, [Goldreich 2001]); roughly speaking, the machines use a special tape where the message to be sent is placed and another tape where a message to be received is written.”
- Searchable symmetric encryption: Improved definitions and efficient constructions (2006, unknown): “An alternative approach to security definitions is the so-called semantic security or “simulation-based” approach [20, 18].”
- TrustedDB: A Trusted Hardware-Based Database with Privacy and Data Confidentiality (2011, background): “Recall that current cryptographic constructs are based on trapdoor functions [18].”
- Fast Cut-and-Choose-Based Protocols for Malicious and Covert Adversaries (2013, background): “Informally speaking, a protocol is then secure if no real adversary attacking the real protocol can do more harm than an ideal adversary (or simulator) who interacts in the ideal model [12,10,24,2,4,11].”