Deterministic, Stash-Free Write-Only ORAM

Write-Only Oblivious RAM (WoORAM) protocols provide privacy by encrypting the contents of data and also hiding the pattern of write operations over that data. WoORAMs provide better privacy than plain encryption and better performance than more general ORAM schemes (which hide both writing and reading access patterns), and the write-oblivious setting has been applied to important applications of cloud storage synchronization and encrypted hidden volumes. In this paper, we introduce an entirely new technique for Write-Only ORAM, called DetWoORAM. Unlike previous solutions, DetWoORAM uses a deterministic, sequential writing pattern without the need for any "stashing" of blocks in local state when writes fail. Our protocol, while conceptually simple, provides substantial improvement over prior solutions, both asymptotically and experimentally. In particular, under typical settings the DetWoORAM writes only 2 blocks (sequentially) to backend memory for each block written to the device, which is optimal. We have implemented our solution using the BUSE (block device in user-space) module and tested DetWoORAM against both an encryption only baseline of dm-crypt and prior, randomized WoORAM solutions, measuring only a 3x-14x slowdown compared to an encryption-only baseline and around 6x-19x speedup compared to prior work

Roadmap on optical security

Postprint (author's final draft

Security of discrete log cryptosystems in the random oracle and the generic model

We introduce novel security proofs that use combinatorial counting arguments rather than reductions to the discrete logarithm or to the Diffie-Hellman problem. Our security results are sharp and clean with no polynomial reduction times involved. We consider a combination of the random oracle model and the generic model. This corresponds to assuming an ideal hash function H given by an oracle and an ideal group of prime order q, where the binary encoding of the group elements is useless for cryptographic attacks In this model, we first show that Schnorr signatures are secure against the one-more signature forgery : A generic adversary performing t generic steps including l sequential interactions with the signer cannot produce l+1 signatures with a better probability than (t 2)/q. We also characterize the different power of sequential and of parallel attacks. Secondly, we prove signed ElGamal encryption is secure against the adaptive chosen ciphertext attack, in which an attacker can arbitrarily use a decryption oracle except for the challenge ciphertext. Moreover, signed ElGamal encryption is secure against the one-more decryption attack: A generic adversary performing t generic steps including l interactions with the decryption oracle cannot distinguish the plaintexts of l + 1 ciphertexts from random strings with a probability exceeding (t 2)/q

Error Function Attack of chaos synchronization based encryption schemes

Different chaos synchronization based encryption schemes are reviewed and compared from the practical point of view. As an efficient cryptanalysis tool for chaos encryption, a proposal based on the Error Function Attack is presented systematically and used to evaluate system security. We define a quantitative measure (Quality Factor) of the effective applicability of a chaos encryption scheme, which takes into account the security, the encryption speed, and the robustness against channel noise. A comparison is made of several encryption schemes and it is found that a scheme based on one-way coupled chaotic map lattices performs outstandingly well, as judged from Quality Factor

A parallel block-based encryption schema for digital images using reversible cellular automata

AbstractWe propose a novel images encryption schema based on reversible one-dimensional cellular automata. Contrasting to the sequential operating mode of several existing approaches, the proposed one is fully parallelizable since the encryption/decryption tasks can be executed using multiple processes running independently for the same single image. The parallelization is made possible by defining a new RCA-based construction of an extended pseudorandom permutation that takes a nonce as a supplementary parameter. The defined PRP exploit the chaotic behavior and the high initial condition's sensitivity of the RCAs to ensure perfect cryptographic security properties. Results of various experiments and analysis show that high security and execution performances can be achieved using the approach, and furthermore, it provides the ability to perform a selective area decryption since any part of the ciphered-image can be deciphered independently from others, which is very useful for real time applications

DeepSecure: Scalable Provably-Secure Deep Learning

This paper proposes DeepSecure, a novel framework that enables scalable execution of the state-of-the-art Deep Learning (DL) models in a privacy-preserving setting. DeepSecure targets scenarios in which neither of the involved parties including the cloud servers that hold the DL model parameters or the delegating clients who own the data is willing to reveal their information. Our framework is the first to empower accurate and scalable DL analysis of data generated by distributed clients without sacrificing the security to maintain efficiency. The secure DL computation in DeepSecure is performed using Yao's Garbled Circuit (GC) protocol. We devise GC-optimized realization of various components used in DL. Our optimized implementation achieves more than 58-fold higher throughput per sample compared with the best-known prior solution. In addition to our optimized GC realization, we introduce a set of novel low-overhead pre-processing techniques which further reduce the GC overall runtime in the context of deep learning. Extensive evaluations of various DL applications demonstrate up to two orders-of-magnitude additional runtime improvement achieved as a result of our pre-processing methodology. This paper also provides mechanisms to securely delegate GC computations to a third party in constrained embedded settings