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General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library,  Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2013 Vol.1(3): 314-318 ISSN: 2301-3559
DOI: 10.7763/LNSE.2013.V1.68

Indistinguishable of AES-Based PRNG against Modification Attack Based on Statistical Distance Tests and Entropy Measures

Santi Indarjani and Belawati Widjaja
Abstract—Due to previous research, AES-based PRNG is not affected by insertion attack (in random manner) under level of significant α = 0.01, even it caused some failed tests in randomness. Completing the research, the writers do the observation of the modification attack in random manner against the output sequence of AES-based PRNG that is limited to 1-bit modification attack. The tests are performed by applying statistical distance test between the output sequence before and after the attack. To assure the attack effect, we also measure the entropy values of the sequence before and after attack and compare them. The attack scenario is still the same as the previous research [see 3], except replacing the insertion with modification and parameter ε = 0.001. The results show that the modification attack does not give the significant effect on the randomness property of the AES-based PRNG. It was proved from 60 experiments of 1-bit modification attack, that the maximum statistical distances are still far away from ε= 0.001. And the change of the entropy source after the attack are very small and also still far away from the ε = 0.001.

Index Terms—AES based PRNG, modification attack, statistical distance, entropy.

Santi Indarjani is with National Crypto Institute, Indonesia (e-mail : santi.indarjani@stsn-nci.ac.id, santi_indarjani@yahoo.com).
Belawati Widjaja is with Faculty of Computer Science, University of Indonesia (e-mail : bela@cs.ui.ac.id).


Cite: Santi Indarjani and Belawati Widjaja, "Indistinguishable of AES-Based PRNG against Modification Attack Based on Statistical Distance Tests and Entropy Measures," Lecture Notes on Software Engineering vol. 1, no. 3, pp. 314-318, 2013.

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