Keystroke Identifier Using Fuzzy Logic to Increase Password Security
| Title | Keystroke Identifier Using Fuzzy Logic to Increase Password Security |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Shaout, A., Schmidt, N. |
| Conference Name | 2020 21st International Arab Conference on Information Technology (ACIT) |
| Date Published | Nov. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-8855-3 |
| Keywords | authorisation, Companies, Computer crime, computer security, correct password, Cyber physical system, Cybercrime, cybercriminal, cybersecurity, Delay effects, delays, entity behavior analytics, Fuzzy logic, fuzzy system, fuzzy systems, keystroke identifier, machine learning, message authentication, Metrics, normal password entry session, password, password security, pubcrawl, resilience, Resiliency, secure log-in, security, typing speed |
| Abstract | Cybersecurity is a major issue today. It is predicted that cybercrime will cost the world \$6 trillion annually by 2021. It is important to make logins secure as well as to make advances in security in order to catch cybercriminals. This paper will design and create a device that will use Fuzzy logic to identify a person by the rhythm and frequency of their typing. The device will take data from a user from a normal password entry session. This data will be used to make a Fuzzy system that will be able to identify the user by their typing speed. An application of this project could be used to make a more secure log-in system for a user. The log-in system would not only check that the correct password was entered but also that the rhythm of how the password was typed matched the user. Another application of this system could be used to help catch cybercriminals. A cybercriminal may have a certain rhythm at which they type at and this could be used like a fingerprint to help officials locate cybercriminals. |
| URL | https://ieeexplore.ieee.org/document/9300107 |
| DOI | 10.1109/ACIT50332.2020.9300107 |
| Citation Key | shaout_keystroke_2020 |
- fuzzy systems
- typing speed
- security
- secure log-in
- Resiliency
- resilience
- pubcrawl
- password security
- password
- normal password entry session
- Metrics
- message authentication
- machine learning
- keystroke identifier
- authorisation
- fuzzy system
- Fuzzy logic
- entity behavior analytics
- delays
- Delay effects
- Cybersecurity
- cybercriminal
- Cybercrime
- Cyber Physical System
- correct password
- computer security
- Computer crime
- Companies