Human Aspects of Information Security, Privacy, and Trust: by Sourav Bhuyan, Joel S. Greenstein, Kevin A. Juang (auth.), PDF

By Sourav Bhuyan, Joel S. Greenstein, Kevin A. Juang (auth.), Louis Marinos, Ioannis Askoxylakis (eds.)

ISBN-10: 3642393446

ISBN-13: 9783642393440

ISBN-10: 3642393454

ISBN-13: 9783642393457

This ebook constitutes the refereed court cases of the 1st foreign convention on Human facets of knowledge safeguard, privateness and belief, HAS 2013, held as a part of the fifteenth foreign convention on Human-Computer interplay, HCII 2013, held in Las Vegas, united states in July 2013, together with 12 different thematically comparable meetings. the complete of 1666 papers and 303 posters awarded on the HCII 2013 meetings used to be conscientiously reviewed and chosen from 5210 submissions. those papers tackle the most recent study and improvement efforts and spotlight the human features of layout and use of computing platforms. The papers authorised for presentation completely disguise the whole box of human-computer interplay, addressing significant advances in wisdom and potent use of desktops in a number of program parts. the entire of 39 contributions was once conscientiously reviewed and chosen for inclusion within the HAS lawsuits. The papers are geared up within the following topical sections: novel authentication structures; human elements in protection; protection and privateness regulations; and consumer centric defense and privacy.

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Extra resources for Human Aspects of Information Security, Privacy, and Trust: First International Conference, HAS 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013. Proceedings

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This property also allows ANNs to learn from experience, which make them strong candidates for keeping pace with evolving intrusion techniques in the paramount task of guarding the brain. As such, ANNs are an ideal technology for working with brain waves [16]. After brain waves have been converted into a digital format using a DWT, they will be used in conjunction with a predetermined classification enumerating the danger of each input to train an ANN. The ANN then learns the patterns between the input and the classification, and after enough training, will develop signatures similar to those used by antivirus programs.

Fuzzy numbers help to deal with the imprecise and uncertain values of each criterion [4]. Each fuzzy number is associated to a linguistic variable as shown in fig 1 [5]. Fig. 1. Fuzzy numbers with linguistic variables defining them Multicriteria optimization is the process of determining the most feasible alternative of all taking in to account each of the established criteria. An approach to determine a final solution as a compromise was introduced in [6]. In this context, the VIKOR method [7, 8, 9] is a multicriteria ranking approach developed to help solve the decision problems with conflicting and noncommensurable criteria.

Intermediate performance matrix with performance scores as triangular fuzzy numbers Step 5: Defuzzification: First, the interval performance matrix ( ) as in Fig 8 is obtained using the alpha cut method on the intermediate performance matrix (F). Each score is worked upon using eq. 2 and 3 to form an interval [ , ]. The value of α (0-1) denotes the experimenter’s degree of confidence while evaluating the scores and criteria weights in the process. A larger value expresses stronger degree of confidence.

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Human Aspects of Information Security, Privacy, and Trust: First International Conference, HAS 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013. Proceedings by Sourav Bhuyan, Joel S. Greenstein, Kevin A. Juang (auth.), Louis Marinos, Ioannis Askoxylakis (eds.)


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