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Machine translation
1. (WO2007001390) SYSTEM AND METHOD FOR CLASSIFYING REGIONS OF KEYSTROKE DENSITY WITH A NEURAL NETWORK
Latest bibliographic data on file with the International Bureau   

Pub. No.:    WO/2007/001390    International Application No.:    PCT/US2005/035219
Publication Date: 04.01.2007 International Filing Date: 30.09.2005
IPC:
H04L 9/00 (2006.01), H04K 1/00 (2006.01)
Applicants: THE PENN STATE RESEARCH FOUNDATION [US/US]; 113 Technology Center, University Park, PA 16802 (US) (For All Designated States Except US).
PHOHA, Vir, V. [US/US]; (US) (For US Only).
BABU, Sunil [US/US]; (US) (For US Only).
RAY, Asok [US/US]; (US) (For US Only).
PHOABA, Shashi, P. [US/US]; (US) (For US Only)
Inventors: PHOHA, Vir, V.; (US).
BABU, Sunil; (US).
RAY, Asok; (US).
PHOABA, Shashi, P.; (US)
Agent: BABBITT, William, Thomas; BLAKELY, SOKOLOFF, TAYLOR & ZAFMAN, 12400 Wilshire Blvd., 7th Floor, Los Angeles, CA 90025-1026 (US)
Priority Data:
60/615,735 04.10.2004 US
11/241,103 29.09.2005 US
Title (EN) SYSTEM AND METHOD FOR CLASSIFYING REGIONS OF KEYSTROKE DENSITY WITH A NEURAL NETWORK
(FR) SYSTEME ET PROCEDE DE CLASSIFICATION DE REGIONS DE DENSITE DE FRAPPES DE TOUCHE AVEC RESEAU NEURONAL
Abstract: front page image
(EN)We develop a system consisting of a neutral architecture resulting in classifying regions corresponding to users’keystroke patterns. We extend the adaptation properties to classification phase resulting in learning of changes over time. Classification results on login attempts of 43 users (216 valid, 657 impersonation samples) show considerable improvements over existing methods)
(FR)La présente invention concerne un système constitué d'une architecture neuronale qui consiste à classifier des régions correspondant à des structures de frappes de touche d'un utilisateur. Ces propriétés d'adaptation ont été étendues à une phase de classification qui consiste à apprendre des changements dans le temps. Cette classification consiste en des tentatives d'enregistrement de 43 utilisateurs ( 216 valables, 657 échantillons d'imitation) et présente des améliorations considérables sur les procédés existants.
Designated States: AE, AG, AL, AM, AT, AU, AZ, BA, BB, BG, BR, BW, BY, BZ, CA, CH, CN, CO, CR, CU, CZ, DE, DK, DM, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KP, KR, KZ, LC, LK, LR, LS, LT, LU, LV, LY, MA, MD, MG, MK, MN, MW, MX, MZ, NA, NG, NI, NO, NZ, OM, PG, PH, PL, PT, RO, RU, SC, SD, SE, SG, SK, SL, SM, SY, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, YU, ZA, ZM, ZW.
African Regional Intellectual Property Organization (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (AM, AZ, BY, KG, KZ, MD, RU, TJ, TM)
European Patent Office (AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HU, IE, IS, IT, LT, LU, LV, MC, NL, PL, PT, RO, SE, SI, SK, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, ML, MR, NE, SN, TD, TG).
Publication Language: English (EN)
Filing Language: English (EN)