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Provably Secure Pseudo-Random Generators
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This report is a literary study on provably secure pseudo-random generators. In the report we explain what provably secure pseudo-random generators are and what they are most commonly used for. We also discuss one-way functions which are closely related to our subject. Furthermore, two well-known generators are described and compared, one generator by Blum and Micali, and one by Blum, Blum and Shub. What we have concluded is that the x

2 mod N generator by Blum, Blum and Shub seems to be the better one concerning speed, security and application areas. You will also be able to read about how the Blum-Blum-Shub generator can be implemented and why we believe that implementation is suitable.

Abstract [sv]

Den här rapporten är en litteraturstudie om bevisbart säkra pseudo-slumpmässiga generatorer. I rapporten förklarar vi vad bevisbart säkra pseudo-slumpmässiga generatorer är och vad de vanligtvis används till. Vi tar dessutom upp envägsfunktioner som är starkt kopplat till vårt ämne. Vidare beskrivs och jämförs två kända sådana generatorer, en generator av Blum och Micali och en generator av Blum, Blum och Shub. Den slutsats som vi kommit fram till är att x

2 mod N generatorn av Blum, Blum och Shub verkar vara den bättre utav dem vad gäller hastighet, säkerhet och applikationsområden. Ni kommer även kunna läsa om hur en sådan generator kan implementeras och vi förklarar varför den presenterade koden är bra.

Place, publisher, year, edition, pages
Kandidatexjobb CSC, K13007
National Category
Computer Science
URN: urn:nbn:se:kth:diva-134830OAI: diva2:668253
Educational program
Master of Science in Engineering - Computer Science and Technology
Available from: 2013-12-13 Created: 2013-11-29 Last updated: 2013-12-13Bibliographically approved

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Provably Secure Pseudo-Random Generators(411 kB)664 downloads
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Type fulltextMimetype application/pdf

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