Visible to the public Biblio

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2022-07-13
Dolev, Shlomi, Kalma, Arseni.  2021.  Verifiable Computing Using Computation Fingerprints Within FHE. 2021 IEEE 20th International Symposium on Network Computing and Applications (NCA). :1—9.
We suggest using Fully Homomorphic Encryption (FHE) to be used, not only to keep the privacy of information but also, to verify computations with no additional significant overhead, using only part of the variables length for verification. This method supports the addition of encrypted values as well as multiplication of encrypted values by the addition of their logarithmic representations and is based on a separation between hardware functionalities. The computer/server performs blackbox additions and is based on the separation of server/device/hardware, such as the enclave, that may deal with additions of logarithmic values and exponentiation. The main idea is to restrict the computer operations and to use part of the variable for computation verification (computation fingerprints) and the other for the actual calculation. The verification part holds the FHE value, of which the calculated result is known (either due to computing locally once or from previously verified computations) and will be checked against the returned FHE value. We prove that a server with bit computation granularity can return consistent encrypted wrong results even when the public key is not provided. For the case of computer word granularity the verification and the actual calculation parts are separated, the verification part (the consecutive bits from the LSB to the MSB of the variables) is fixed across all input vectors. We also consider the case of Single Instruction Multiple Data (SIMD) where the computation fingerprints index in the input vectors is fixed across all vectors.
2019-11-25
Cassagne, Adrien, Aumage, Olivier, Barthou, Denis, Leroux, Camille, Jégo, Christophe.  2018.  MIPP: A Portable C++ SIMD Wrapper and Its Use for Error Correction Coding in 5G Standard. Proceedings of the 2018 4th Workshop on Programming Models for SIMD/Vector Processing. :2:1–2:8.
Error correction code (ECC) processing has so far been performed on dedicated hardware for previous generations of mobile communication standards, to meet latency and bandwidth constraints. As the 5G mobile standard, and its associated channel coding algorithms, are now being specified, modern CPUs are progressing to the point where software channel decoders can viably be contemplated. A key aspect in reaching this transition point is to get the most of CPUs SIMD units on the decoding algorithms being pondered for 5G mobile standards. The nature and diversity of such algorithms requires highly versatile programming tools. This paper demonstrates the virtues and versatility of our MIPP SIMD wrapper in implementing a high performance portfolio of key ECC decoding algorithms.
2018-09-12
Domínguez, A., Carballo, P. P., Núñez, A..  2017.  Programmable SoC platform for deep packet inspection using enhanced Boyer-Moore algorithm. 2017 12th International Symposium on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC). :1–8.

This paper describes the work done to design a SoC platform for real-time on-line pattern search in TCP packets for Deep Packet Inspection (DPI) applications. The platform is based on a Xilinx Zynq programmable SoC and includes an accelerator that implements a pattern search engine that extends the original Boyer-Moore algorithm with timing and logical rules, that produces a very complex set of rules. Also, the platform implements different modes of operation, including SIMD and MISD parallelism, which can be configured on-line. The platform is scalable depending of the analysis requirement up to 8 Gbps. High-Level synthesis and platform based design methodologies have been used to reduce the time to market of the completed system.