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The password used to authenticate users is vulnerable to shoulder-surfing assaults, in which attackers directly observe users and steal their passwords without using any other technical upkeep. The graphical password system is regarded as a likely backup plan to the alphanumeric password system. Additionally, for system privacy and security, a number of programs make considerable use of the graphical password-based authentication method. The user chooses the image for the authentication procedure when using a graphical password. Furthermore, graphical password approaches are more secure than text-based password methods. In this paper, the effective graphical password authentication model, named as Deep Residual Network based Graphical Password is introduced. Generally, the graphical password authentication process includes three phases, namely registration, login, and authentication. The secret pass image selection and challenge set generation process is employed in the two-step registration process. The challenge set generation is mainly carried out based on the generation of decoy and pass images by performing an edge detection process. In addition, edge detection is performed using the Deep Residual Network classifier. The developed Deep Residual Network based Graphical Password algorithm outperformance than other existing graphical password authentication methods in terms of Information Retention Rate and Password Diversity Score of 0.1716 and 0.1643, respectively. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the traditional PIN entry method is vulnerable to shoulder-surfing attack,a secure PIN entry method against shoulder-surfing attack was proposed.The method changes the traditional input interface on the mobile device and uses the vibration channel of the device as the auxiliary channel to transmit the hidden information to the user.The user simply selects items to input PIN.The analysis shows that the proposed method can effectively resist shoulder-surfing attack.

Aiming at the problem that the traditional PIN entry method is vulnerable to shoulder-surfing attack, a secure PIN entry method against shoulder-surfing attack was proposed. The method changes the traditional input interface on the mobile device and uses the vibration channel of the device as the auxiliary channel to transmit the hidden information to the user. The user simply selects items to input PIN. The analysis shows that the proposed method can effectively resist shoulder-surfing attack.

Password systems should be secure and easy to use. However, text-based systems require passwords that can be difficult to remember, while graphical systems require passwords with lengthy input times. In addition, shoulder-surfing attacks are a difficulty common to both. This paper discusses a multi-modal password system called GTPass. GTPass uses both graphics and text to capitalize on the advantages and eliminate the drawbacks of both systems. GTPass introduces a new password input scheme called TIS (Transformed Input Scheme) to solve existing problems in graphical password systems and text-based password systems. GTPass users can memorize the password easily and the passwords require very little time to enter. TIS can potentially be used to generate large password spaces. Accordingly, GTPass will be easy to use and highly resistant to a variety of attacks. [ABSTRACT FROM AUTHOR]

Access management of IoT devices is extremely important, and a secure login authentication scheme can effectively protect users’ privacy. However, traditional authentication schemes are threatened by shoulder-surfing attacks, and biometric-based schemes, such as fingerprint recognition and face recognition, that are commonly used today can also be cracked. Researchers have proposed some schemes for current attacks, but they are limited by usability. For example, the login authentication process requires additional device support. This method solves the problem of attacks, but it is unusable, which limits its application. At present, most authentication schemes for the Internet of Things and mobile platforms either focus on security, thus ignoring availability, or have excellent convenience but insufficient security. This is a symmetry problem worth exploring. Therefore, users need a new type of login authentication scheme that can balance security and usability to protect users’ private data or maintain device security. In this paper, we propose a login authentication scheme named PinWheel, which combines a textual password, a graphical password, and biometrics to prevent both shoulder-surfing attacks and smudge attacks and solves the current schemes’ lack of usability. We implemented PinWheel and evaluated it from the perspective of security and usability. The experiments required 262 days, and 573 subjects participated in our investigation. The evaluation results show that PinWheel can at least effectively resist both mainstream attacks and is superior to most existing schemes in terms of usability.

The graphical password authentication scheme uses icons instead of text-based passwords to authenticate users. Icons might be somehow more familiar to human beings than text-based passwords, since it is hard to remember the latter with sufficient security strength. No matter what kind of password is used, there are always shoulder-surfing problems. An attacker can easily get text-based password or graphical password by observation, capturing a video or recording the login process. In this paper, we propose a shoulder-surfing-proof graphical password authentication scheme using the convex-hull graphical algorithm. We give evaluation and comparisons to demonstrate the security strength and the functionality advantages of our scheme. [ABSTRACT FROM AUTHOR]

User authentication such as password setting has become increasingly important for the secure management of the information stored in mobile devices. However, in the password authentication schemes used in mobile devices, enhancing security reduces their usability, and passwords become hard to memorize. In addition, enhancing their usability makes them vulnerable to shoulder-surfing or recording attacks involving stealing a glance at the authentication process through the system interface. In this paper, we propose a password authentication scheme that uses a virtual scroll wheel, called WheelLock, to ensure appropriate usability and prevent brute force, shoulder-surfing, and recording attacks. [ABSTRACT FROM AUTHOR]

Access management of IoT devices is extremely important, and a secure login authentication scheme can effectively protect users' privacy. However, traditional authentication schemes are threatened by shoulder-surfing attacks, and biometric-based schemes, such as fingerprint recognition and face recognition, that are commonly used today can also be cracked. Researchers have proposed some schemes for current attacks, but they are limited by usability. For example, the login authentication process requires additional device support. This method solves the problem of attacks, but it is unusable, which limits its application. At present, most authentication schemes for the Internet of Things and mobile platforms either focus on security, thus ignoring availability, or have excellent convenience but insufficient security. This is a symmetry problem worth exploring. Therefore, users need a new type of login authentication scheme that can balance security and usability to protect users' private data or maintain device security. In this paper, we propose a login authentication scheme named PinWheel, which combines a textual password, a graphical password, and biometrics to prevent both shoulder-surfing attacks and smudge attacks and solves the current schemes' lack of usability. We implemented PinWheel and evaluated it from the perspective of security and usability. The experiments required 262 days, and 573 subjects participated in our investigation. The evaluation results show that PinWheel can at least effectively resist both mainstream attacks and is superior to most existing schemes in terms of usability. [ABSTRACT FROM AUTHOR]