Implementation of a Graphical Password Authentication System 'PassPositions'

Yang, Gi-Chul; Oh, Haengun

doi:10.18178/joig.6.2.117-121

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Certain websites use dynamic codes through e-mails or phone messages to provide authentication. It is one of the most successful two-factor authentication schemes, but the identified problem is that it mainly relies on other devices [3,4]. Some of the earlier studies found that the users can better recall images than text passwords.…”

Section: Introductionmentioning

confidence: 99%

An Advanced Knowledge Based Graphical Authentication Framework with Guaranteed Confidentiality and Integrity

Golar,

Sharma

2023

IJRITCC

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The information and security systems largely rely on passwords,which remain the fundamental part of any authentication process. The conventional authentication method based on alphanumerical username and password suffer from significant disadvantages. The graphical password-based authentication system has recently been introduced as an effective alternative. Although the graphical schemes effectively generate the passwords with better flexibility and enhanced security, the most common problem with this is the shoulder surfing attack. This paper proposes an effective 3D graphical password authentication system to overcome such drawbacks. The system is based on the selection of click points for generating passwords. The proposed work involved a training phase for evaluating the model in terms of the success rate. The overall evaluations of the model in terms of password entropy, password space, login success rates, and prediction probability in the shoulder surfing and guessing attacks proved that the model is more confidential and maintains a higher range of integrity than the other existing models.

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Section: Introductionmentioning

confidence: 99%

An Advanced Knowledge Based Graphical Authentication Framework with Guaranteed Confidentiality and Integrity

Golar,

Sharma

2023

IJRITCC

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“…Graphical password systems can be classified as either recognition-based or recall-based approach; the latter of which is further divided into cued recall-based and pure recall-based approach [2,7,18]. In the recognition-based approach, the user selects a set of images from the available images in the registration phase which are recognized and reselected in the same sequence in the login phase.…”

Section: Introductionmentioning

confidence: 99%

A New Shoulder Surfing and Mobile Key-Logging Resistant Graphical Password Scheme for Smart-Held Devices

Hanif¹,

Sohail²,

Shehrbano³

et al. 2019

IJACSA

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In globalization of information, internet has played a vital role by providing an easy and fast access of information and systems to remote users. However, with ease for authentic users, it has made information resources accessible to unauthorized users too. To authorize legitimate user for the access of information and systems, authentication mechanisms are applied. Many users use their credentials or private information at public places to access their accounts that are protected by passwords. These passwords are usually text-based passwords and their security and effectiveness can be compromised. An attacker can steal text-based passwords using different techniques like shoulder surfing and various key logger software, that are freely available over internet. To improve the security, numerous sophisticated and secure authentication systems have been proposed that employ various biometric authentication systems, token-based authentication system etc. But these solutions providing such high-level security, require special modification in the design and hence, imply additional cost. Textual passwords that are easy to use but vulnerable to attacks like shoulder surfing, various image based, and textual graphical password schemes are proposed. However, none of the existing textual graphical passwords are resistant to shoulder surfing and more importantly to mobile key-logging. In this paper, an improved and robust textual graphical password scheme is proposed that uses sectors and colors and introducing randomization as the primary function for the character display and selection. This property makes the proposed scheme resistant to shoulder surfing and more importantly to mobile key-logging. It can be useful for authentication process of any smart held device application.

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Intelligent Security Model for Password Generation and Estimation Using Hand Gesture Features

Mahdi

Hadi

Abbas

2022

BDCC

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Computer security depends mainly on passwords to protect human users from attackers. Therefore, manual and alphanumerical passwords are the most frequent type of computer authentication. However, creating these passwords has significant drawbacks. For example, users often tend to choose passwords based on personal information so that they can be memorable and therefore weak and guessable. In contrast, it is often difficult to remember if the password is difficult to guess. We propose an intelligent security model for password generation and estimation to address these problems using the ensemble learning approach and hand gesture features. This paper proposes two intelligent stages: the first is the password generation stage based on the ensemble learning approach and the proposed S-Box. The second is the password strength estimation stage, also based on the ensemble learning approach. Four well-known classifiers are used: Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), Random Forest Tree (RFT), and AdaBoost applied on two datasets: MNIST images dataset and password strength dataset. The experimental results showed that the hand gesture and password strength classification processes accurately performed at 99% in AUC, Accuracy, F1-measures, Precision, and Recall. As a result, the extracted features of hand gestures will directly impact the complexity of generated passwords, which are very strong, hard to guess, and memorable.

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Implementation of a Graphical Password Authentication System 'PassPositions'

Cited by 3 publications

References 7 publications

An Advanced Knowledge Based Graphical Authentication Framework with Guaranteed Confidentiality and Integrity

An Advanced Knowledge Based Graphical Authentication Framework with Guaranteed Confidentiality and Integrity

A New Shoulder Surfing and Mobile Key-Logging Resistant Graphical Password Scheme for Smart-Held Devices

Intelligent Security Model for Password Generation and Estimation Using Hand Gesture Features

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