A pattern-based password authentication scheme for minimizing shoulder surfing attack
The user usually uses a password to avoid the attacks like a dictionary attack, brute force attack and shoulder surfing attack which is the famous attack nowadays. The shoulder surfing attack is a direct observation technique by watching over the user's shoulder when they enter their password t...
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my.uniten.dspace-60072018-02-20T03:05:08Z A pattern-based password authentication scheme for minimizing shoulder surfing attack Awang, M.I. Mohamed, M.A. Mohamed, R.R. Ahmad, A. Rawi, N.A. The user usually uses a password to avoid the attacks like a dictionary attack, brute force attack and shoulder surfing attack which is the famous attack nowadays. The shoulder surfing attack is a direct observation technique by watching over the user's shoulder when they enter their password to get information. The most common authentication method used by the user is textual password. But, the textual password has many disadvantages because it is vulnerable to attack as it tends to shoulder surfing attack. In this project, a pattern-based password authentication will develop to overcome this problem. Using this scheme, the user needs to select the type of pattern that they like during registration. To log in to their account, the user needs to enter the password in the form of the textual password in ordering manner based on a pattern that they choose during registration. The text password grid presented with a different style as it filled with random objects whether characters, numbers or images. This method is suitable to minimizing shoulder surfing attack as it can improve the security of user's password and they can efficiently login to the system. 2017-12-08T08:00:49Z 2017-12-08T08:00:49Z 2017 Article 10.18517/ijaseit.7.3.1517 en_US International Journal on Advanced Science, Engineering and Information Technology, 7(3), 1049-1055 |
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The user usually uses a password to avoid the attacks like a dictionary attack, brute force attack and shoulder surfing attack which is the famous attack nowadays. The shoulder surfing attack is a direct observation technique by watching over the user's shoulder when they enter their password to get information. The most common authentication method used by the user is textual password. But, the textual password has many disadvantages because it is vulnerable to attack as it tends to shoulder surfing attack. In this project, a pattern-based password authentication will develop to overcome this problem. Using this scheme, the user needs to select the type of pattern that they like during registration. To log in to their account, the user needs to enter the password in the form of the textual password in ordering manner based on a pattern that they choose during registration. The text password grid presented with a different style as it filled with random objects whether characters, numbers or images. This method is suitable to minimizing shoulder surfing attack as it can improve the security of user's password and they can efficiently login to the system. |
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Article |
author |
Awang, M.I. Mohamed, M.A. Mohamed, R.R. Ahmad, A. Rawi, N.A. |
spellingShingle |
Awang, M.I. Mohamed, M.A. Mohamed, R.R. Ahmad, A. Rawi, N.A. A pattern-based password authentication scheme for minimizing shoulder surfing attack |
author_facet |
Awang, M.I. Mohamed, M.A. Mohamed, R.R. Ahmad, A. Rawi, N.A. |
author_sort |
Awang, M.I. |
title |
A pattern-based password authentication scheme for minimizing shoulder surfing attack |
title_short |
A pattern-based password authentication scheme for minimizing shoulder surfing attack |
title_full |
A pattern-based password authentication scheme for minimizing shoulder surfing attack |
title_fullStr |
A pattern-based password authentication scheme for minimizing shoulder surfing attack |
title_full_unstemmed |
A pattern-based password authentication scheme for minimizing shoulder surfing attack |
title_sort |
pattern-based password authentication scheme for minimizing shoulder surfing attack |
publishDate |
2017 |
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1644493821252206592 |
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