Browsing by Subject "Theoretical framework"

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Open Access
GenoGuard: protecting genomic data against brute-force attacks
(IEEE, 2015-05) Huang, Z.; Ayday, Erman; Fellay, Jacques; Hubaux, J-P.; Juels, A.
Secure storage of genomic data is of great and increasing importance. The scientific community's improving ability to interpret individuals' genetic materials and the growing size of genetic database populations have been aggravating the potential consequences of data breaches. The prevalent use of passwords to generate encryption keys thus poses an especially serious problem when applied to genetic data. Weak passwords can jeopardize genetic data in the short term, but given the multi-decade lifespan of genetic data, even the use of strong passwords with conventional encryption can lead to compromise. We present a tool, called Geno Guard, for providing strong protection for genomic data both today and in the long term. Geno Guard incorporates a new theoretical framework for encryption called honey encryption (HE): it can provide information-theoretic confidentiality guarantees for encrypted data. Previously proposed HE schemes, however, can be applied to messages from, unfortunately, a very restricted set of probability distributions. Therefore, Geno Guard addresses the open problem of applying HE techniques to the highly non-uniform probability distributions that characterize sequences of genetic data. In Geno Guard, a potential adversary can attempt exhaustively to guess keys or passwords and decrypt via a brute-force attack. We prove that decryption under any key will yield a plausible genome sequence, and that Geno Guard offers an information-theoretic security guarantee against message-recovery attacks. We also explore attacks that use side information. Finally, we present an efficient and parallelized software implementation of Geno Guard. © 2015 IEEE.
Open Access
Perceived auditory environment in historic spaces of anatolian culture : a case study on Hacı Bayram mosque
(International Institute of Acoustics and Vibrations, 2016) Acun V.; Yilmazer, Semiha; Taherzadeh, P.
This article reports the initial finds of a research that is concerned with the perceived auditory environment within an historical mosque and its surroundings. Haci Bayram Mosque and its surrounding area of Hamamönü has been selected as the research site due to being the historical center of Ankara. Although there are studies concerned with the acoustical characteristics of mosques, there isn't enough research focusing on users' expectation and interpretation of the perceived auditory environment within a mosque. This study adopts the user focused of Grounded Theory to capture individuals' auditory sensation and interpretation of the perceived auditory environment within a historical mosque and its surroundings. In depth interviews are held with the congregation of the mosque and with the individuals sitting around the surrounding area. Based on their subjective responses, a theoretical framework is generated to gain an insight on the factors that affect individuals understanding and expectation from mosques. Acoustical characteristics of the mosque are analyzed by computer simulation and in-situ measurements of sound pressure levels. Objective room-acoustic indicators consist of reverberation time (RT) and speech transmission index (STI). The conceptual framework generated through Grounded Theory shows how perceived auditory environment may influence individuals' response to the physical environment of the mosque by showing the associations between the soundscape elements, spatial function and sense of place.
Open Access
A theoretical framework on the ideal number of classifiers for online ensembles in data streams
(ACM, 2016-10) Bonab, Hamed R.; Can, Fazlı
A priori determining the ideal number of component classifiers of an ensemble is an important problem. The volume and velocity of big data streams make this even more crucial in terms of prediction accuracies and resource requirements. There is a limited number of studies addressing this problem for batch mode and none for online environments. Our theoretical framework shows that using the same number of independent component classifiers as class labels gives the highest accuracy. We prove the existence of an ideal number of classifiers for an ensemble, using the weighted majority voting aggregation rule. In our experiments, we use two state-of-the-art online ensemble classifiers with six synthetic and six real-world data streams. The violation of providing independent component classifiers for our theoretical framework makes determining the exact ideal number of classifiers nearly impossible. We suggest upper bounds for the number of classifiers that gives the highest accuracy. An important implication of our study is that comparing online ensemble classifiers should be done based on these ideal values, since comparing based on a fixed number of classifiers can be misleading. © 2016 ACM.