Cypress: compression and encryption of data and code for embedded multimedia systems

Lekatsas, H.; Henkel, Jörg; Chakradhar, Srimat; Jakkula, Venkata

doi:10.1109/mdt.2004.55

Cited by 10 publications

(2 citation statements)

References 5 publications

(1 reference statement)

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“…This dual use of compression algorithms saves time and effort when dealing with embedded multimedia systems [1]. Recently, the cryptanalysis of Huffman coding [2] is presented by Mohtashemi [3].…”

Section: Introductionmentioning

confidence: 99%

Security using Shannon-Fano-Elias codes

Katti

Ghosh

2009

2009 IEEE International Symposium on Circuits and Systems

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In this paper we propose using the compression method, Shannon-Fano-Elias coding, for encryption. ShannonFano-Elias codes lend themselves for encryption because codewords depend on the order in which the symbols that need to be coded are written and it does not matter if the probability mass function of the symbols is known to everyone. If there are n symbols then there are n! orderings, each leading to a new code. Using an ordering as a key for encryption for small n leads to a weak encryption scheme. We therefore propose a new scheme called adaptive Shannon-Fano-Elias code that makes the complexity of attacks exponential in m, where m is the length of the string being compressed. Since m is usually very large (> 2 20 ), the security of our scheme is very high. The main reason why our scheme's security depends on m is the fact that all attacks require the ciphertext to be scanned from left to right.

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Section: Introductionmentioning

confidence: 99%

Security using Shannon-Fano-Elias codes

Katti

Ghosh

2009

2009 IEEE International Symposium on Circuits and Systems

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“…Prior research in code compression has studied both static and dynamic compression techniques, focusing in particular on efficient implementation strategies [Abali et al 2001;Benini et al 2002Benini et al , 1999Lekatsas et al 2000bLekatsas et al , 2000aErnst et al 1997;Cooper and McIntosh 1999;Lingappan et al 2005;Lekatsas et al 2004;Lekatsas et al 2005;Shogan and Childers 2004;Cooper and Harvey 1998;Wolfe and Chanin 1992;Ros and Sutton 2004;Xie et al 2003;Debray and Evans 2002;Tunstall 1967;Lin et al 2004;Benveniste et al 2001;Yang et al 2000;Lee et al 1999]. One potential problem with most of these techniques is that the compression and decompression decisions are taken in an applicationinsensitive manner; that is, the same compression/decompression strategy is employed for all applications independent of their specific instruction access patterns.…”

Section: Introductionmentioning

confidence: 99%

Access pattern-based code compression for memory-constrained systems

Öztürk

Kandemir

Chen

2008

ACM Trans. Des. Autom. Electron. Syst.

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As compared to a large spectrum of performance optimizations, relatively less effort has been dedicated to optimize other aspects of embedded applications such as memory space requirements, power, real-time predictability, and reliability. In particular, many modern embedded systems operate under tight memory space constraints. One way of addressing this constraint is to compress executable code and data as much as possible. While researchers on code compression have studied efficient hardware and software based code compression strategies, many of these techniques do not take application behavior into account; that is, the same compression/decompression strategy is used irrespective of the application being optimized. This article presents an application-sensitive code compression strategy based on control flow graph (CFG) representation of the embedded program. The idea is to start with a memory image wherein all basic blocks of the application are compressed, and decompress only the blocks that are predicted to be needed in the near future. When the current access to a basic block is over, our approach also decides the point at which the block could be compressed. We propose and evaluate several compression and decompression strategies that try to reduce memory requirements without excessively increasing the original instruction cycle counts. Some of our strategies make use of profile data, whereas others are fully automatic. Our experimental evaluation using seven applications from the MediaBench suite and three large embedded applications reveals that the proposed code compression strategy is very successful in practice. Our results also indicate that working at a basic block granularity, as opposed to a procedure granularity, is important for maximizing memory space savings. © 2008 ACM

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Information-Theoretic Cryptography: A Maneuver in the Trade-Off Space of Cryptography in IoT

Zolfaghari

Bibak

2022

Perfect Secrecy in IoT

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Cypress: compression and encryption of data and code for embedded multimedia systems

Cited by 10 publications

References 5 publications

Security using Shannon-Fano-Elias codes

Security using Shannon-Fano-Elias codes

Access pattern-based code compression for memory-constrained systems

Information-Theoretic Cryptography: A Maneuver in the Trade-Off Space of Cryptography in IoT

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