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Read e-book online Advances in Information and Computer Security: 8th PDF

By Masaya Sato, Toshihiro Yamauchi (auth.), Kazuo Sakiyama, Masayuki Terada (eds.)

ISBN-10: 364241382X

ISBN-13: 9783642413827

ISBN-10: 3642413838

ISBN-13: 9783642413834

This e-book constitutes the refereed lawsuits of the eighth foreign Workshop on defense, IWSEC 2013, held in Okinawa, Japan, in November 2013. The 20 revised chosen papers awarded during this quantity have been conscientiously reviewed and chosen from sixty three submissions. they're geared up in topical sections named: software program and method safeguard, cryptanalysis, privateness and cloud computing, public key cryptosystems, and protection protocols.

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Read or Download Advances in Information and Computer Security: 8th International Workshop on Security, IWSEC 2013, Okinawa, Japan, November 18-20, 2013, Proceedings PDF

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Additional resources for Advances in Information and Computer Security: 8th International Workshop on Security, IWSEC 2013, Okinawa, Japan, November 18-20, 2013, Proceedings

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3. Distinguish harmless integer overflow. There are some benign integer overflow existing in programs[8], for example, GCC compiler use integer overflow to reduce a comparison instruction, we cannot treat them as vulnerabilities. Another harmless integer overflow with integer overflow checking, such as: add eax, ebx cmp eax, ebx ja target In this case, programmer has checked whether the sum is overflow, so we should treat it as harmless integer overflow. 3 System Overview In this section, we will describe the architecture and working process of EIOD.

Okuno Fig. 4. N-state left-to-right HMM. Observed sequence O is generated by sequence of hidden states Z. Z has form of Markov chain in states S. 2 HMM HMM is a probabilistic model for a sequential observation. Given an observed sequence, O = o1 , . . , oT , an HMM, λ = {π , A, B} calculates the likelihood, P(O|λ ). O is assumed to be generated by a sequence of hidden states Z = z1 , . . , zT , which has the form of a Markov chain in states S = {s1 , . . , zt ∈ S. An observation value, ot , is generated by a state, sn , with probability bsn (ot ).

2. Reduce the dimensionality of the power spectrum obtained in Step 1 using a Melscale filter bank [12]. 3. Map the Mel powers obtained in Step 2 onto the logarithmic scale. 4. Calculate the discrete cosine transform of Mel log powers obtained in Step 3. See [11] for details. The first and second derivative of MFCC are called a delta MFCC and a delta-delta MFCC, both of which are also effective temporal representations [13]. Thus, a feature vector is composed of a combination of MFCC, Delta MFCC, and Delta-Delta MFCC in most ASR methods.

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Advances in Information and Computer Security: 8th International Workshop on Security, IWSEC 2013, Okinawa, Japan, November 18-20, 2013, Proceedings by Masaya Sato, Toshihiro Yamauchi (auth.), Kazuo Sakiyama, Masayuki Terada (eds.)


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