By Olivier Camp, Steven Furnell, Paolo Mori
This e-book constitutes the revised chosen papers of the second one foreign convention on details structures protection and privateness, ICISSP 2016, held in Rome, Italy, in February 2016.
The nine complete papers awarded including invited papers have been conscientiously reviewed and chosen from a complete of ninety one submissions. they're facing subject matters comparable to information and software program protection; privateness and confidentiality; cellular structures defense; biometric authentication; privateness in social media.
Read Online or Download Information Systems Security and Privacy: Second International Conference, ICISSP 2016, Rome, Italy, February 19-21, 2016, Revised Selected Papers PDF
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Additional resources for Information Systems Security and Privacy: Second International Conference, ICISSP 2016, Rome, Italy, February 19-21, 2016, Revised Selected Papers
3. Fig. 3. Evaluation scheme. Finally, our approach was designed taking into consideration two diﬀerent schemes: the ﬁrst based on the sole use of SVM; while the second scheme implemented an additional layer that included clustering techniques. , the SVM-based, and the combined scheme (SVM and clustering) consisted of two phases; the learning phase and guessing phase. 3 SVM-based Scheme The learning and guessing phases performed by the SVM-based scheme are explained next. [Learning Phase] – We select n questions where 1 ≤ n ≤ M ax.
To overcome this limitation, one needs techniques capable of verifying handwritten signatures acquired by smartphones and tablets in mobile scenarios with very high accuracy. Online HSV systems (such as [1,8,16–18]) are able to address only partially these issues: they are supported by mobile devices, but they are not inherently designed for common low-end mobile devices such as mobile phones; several approaches make use of pen pads (special purpose hardware for handwriting), signature tablets (special purpose desktop and mobile hardware for signing), interactive pen displays (complete instruments for working in digital applications), Kiosk systems and PC Tablets.
The threshold reported in Table 1. That shows the results related to precision, recall, f-measure, FAR, and FRR for values which maximize the f-measure. The best results for average were achieved using a 35% tolerance factor. Claimed identities are accepted whenever the score is above the threshold, rejected otherwise. The higher the threshold, the higher the precision, but the lower the recall. Online Handwritten Signature Veriﬁcation for Low-End Devices 41 Fig. 14. Computational time for diﬀerent mobile devices.