An enhanced classifier for authentication in keystroke dynamics using experimental data

العناوين الأخرى

مصنف مطور للتحقق من الهوية في ديناميكية الكتابة على لوحة المفاتيح باستخدام البيانات التجريبية

مقدم أطروحة جامعية

al-Rahmani, Abd Allah Usamah

مشرف أطروحة جامعية

al-Jarrah, Muzaffar Munir

أعضاء اللجنة

Viktorov, Oleg
al-Dawud, Ali Asad Ahmad

الجامعة

جامعة الشرق الأوسط

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

قسم علم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2014

الملخص الإنجليزي

The problem of cyber-attacks on information systems and networks, for various illegal purposes, has become a major threat to society and individuals.

Computer hackers are using all possible means to get access to private data, or to destroy such data.

It has become necessary to improve computer security through more advanced access control mechanisms.

Recently the use of biometrics has been employed to strengthen access control through user authentication that is based on users‟ measureable features.

The work in this thesis examines the keystroke dynamics approach, as a biometric authentication scheme that does not require extra hardware.

The study is focused on enhancing an anomaly detector that is based on a statistical model of classifying the typing rhythm of a person who is trying to access a computer system, whether it is a genuine user or an imposter.

An anomaly detector model is proposed, which uses the median for each typing feature element of as the point of center to measure acceptance against, and a Distance-to-Median threshold value which gives the upper and lower limits for an acceptable feature element.

The proposed model is evaluated using a public benchmark dataset of 20,400 records of password typing time measurement, collected by the Biometrics Lab of Carnagei Melon University.

The proposed model achieves lowest error rates of False Acceptance and False Rejection, compared to previous results of using other models on the same dataset.

A prototype keystroke dynamics authentication tool is developed, based on the proposed model.

The tool has two parts: training, to collect typing data of a user and from that data generates a user identity template, and testing module, to be used as an authentication tool that uses the data collected during training.

A discussion of the results of analyzing the benchmark data, and the data collected using the proposed models are discussed, and conclusions and suggestion for future work are presented.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

عدد الصفحات

80

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-694056