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Title: Relaxed Locally Correctable Codes in Computationally Bounded Channels*
Error-correcting codes that admit {\em local} decoding and correcting algorithms have been the focus of much recent research due to their numerous theoretical and practical applications. An important goal is to obtain the best possible tradeoffs between the number of queries the algorithm makes to its oracle (the {\em locality} of the task), and the amount of redundancy in the encoding (the {\em information rate}). In Hamming's classical adversarial channel model, the current tradeoffs are dramatic, allowing either small locality, but superpolynomial blocklength, or small blocklength, but high locality. However, in the computationally bounded, adversarial channel model, proposed by Lipton (STACS 1994), constructions of locally decodable codes suddenly exhibit small locality and small blocklength, but these constructions require strong trusted setup assumptions e.g., Ostrovsky, Pandey and Sahai (ICALP 2007) construct private locally decodable codes in the setting where the sender and receiver already share a symmetric key. We study variants of locally decodable and locally correctable codes in computationally bounded, adversarial channels, in a setting with no public-key or private-key cryptographic setup. The only setup assumption we require is the selection of the {\em public} parameters (seed) for a collision-resistant hash function. Specifically, we provide constructions of {\em relaxed locally correctable} and more » {\em relaxed locally decodable codes} over the binary alphabet, with constant information rate, and poly-logarithmic locality. Our constructions, which compare favorably with their classical analogues in the computationally unbounded Hamming channel, crucially employ {\em collision-resistant hash functions} and {\em local expander graphs}, extending ideas from recent cryptographic constructions of memory-hard functions. « less
Authors:
; ; ;
Award ID(s):
1755708
Publication Date:
NSF-PAR ID:
10092900
Journal Name:
Relaxed Locally Correctable Codes in Computationally Bounded Channels
Page Range or eLocation-ID:
2414 to 2418
Sponsoring Org:
National Science Foundation
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