Sökning: "Keystroke Biometrics"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden Keystroke Biometrics.

1. 1. User authentication through behavioral biometrics using multi-class classification algorithms : A comprehensive study of machine learning algorithms for keystroke and mouse dynamics

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Emil Lantz; [2023]
   Nyckelord :Behavioral biometrics; keystroke dynamics; mouse dynamics; machine learning; neural networks; decision trees.; Beteendemässig biometri; maskininlärning; neurala nätverk; beslutsträd.;

   Sammanfattning : User authentication is vital in a secure system. Authentication is achieved through something a genuine user knows, has, or is. The latter is called biometrics, commonly attributed with fingerprint and face modalities. It is also possible to identify a user based on their behavior, called behavioral biometrics. LÄS MER

3. 2. Keystroke dynamics for student authentication in online examinations

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Rebecka Mattsson; [2020]
   Nyckelord :;

   Sammanfattning : Biometrics are distinctive for each person, and can not be given away or hacked like a password. Keystroke dynamics is a behavioral biometric characteristic that can be used as a complementary authentication step [1]. In online examinations it is difficult to make sure that each student write their own work. LÄS MER

4. 3. Feature learning with deep neural networks for keystroke biometrics : A study of supervised pre-training and autoencoders

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Datavetenskap

   Författare :Erik Hellström; [2018]
   Nyckelord :Machine Learning; Feature Learning; Neural Networks; Keystroke Biometrics; Behaviosec; Behaviometrics;

   Sammanfattning : Computer security is becoming an increasingly important topic in today’s society, withever increasing connectivity between devices and services. Stolen passwords have thepotential to cause severe damage to companies and individuals alike, leading to therequirement that the security system must be able to detect and prevent fraudulentlogin. LÄS MER

5. 4. Using XGBoost to classify theBeihang Keystroke Dynamics Database

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datalogi

   Författare :Johanna Blomqvist; [2018]
   Nyckelord :Keystroke; XGBoost; machine learning; biometrics; keyboard;

   Sammanfattning : Keystroke Dynamics enable biometric security systems by collecting and analyzing computer keyboard usage data. There are different approaches to classifying keystroke data and a method that has been gaining a lot of attention in the machine learning industry lately is the decision tree framework of XGBoost. LÄS MER

7. 5. Biometrics Technology : Attitudes & influencing factors when trying to adopt this technology in Blekinge healthcare

   Master-uppsats, Blekinge Tekniska Högskola/Sektionen för datavetenskap och kommunikation

   Författare :Irfan Iqbal; Bilal Qadir; [2012]
   Nyckelord :Biometrics Technology; Attitudes influencing factors; Blekinge healthcare;

   Sammanfattning : Context. Biometric technology is a secure and convenient identification method and it does not need to remember complex passwords, nor smart cards, keys, and the like. Biometrics is the measurable characteristics of individuals based on their behavioral patterns or physiological features that can be used to verify or recognize their identity. LÄS MER