Security Revisited: Honeytokens meet Google Authenticator

Papaspirou, Vassilis; Papathanasaki, Maria; Μαγλαράς, Λέανδρος; Kantzavelou, Ioanna; Douligeris, Christos; Ferrag, Mohamed Amine; Janicke, Helge

doi:10.1109/seeda-cecnsm57760.2022.9932907

Cited by 4 publications

(3 citation statements)

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“…However, they still remain vulnerable to various threats that are typical of 2FA systems. In contrast, our recent two-factor honeytoken authentication solution [10] has demonstrated robustness against many common attacks. By incorporating blockchain technology, our solution is further strengthened, particularly against tampering attacks.…”

Section: Introductionmentioning

confidence: 87%

A novel Two-Factor HoneyToken Authentication Mechanism

Papaspirou

Μαγλαράς

Ferrag

et al. 2021

2021 International Conference on Computer Communications and Networks (ICCCN)

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Section: Introductionmentioning

confidence: 87%

A novel Two-Factor HoneyToken Authentication Mechanism

Papaspirou

Μαγλαράς

Ferrag

et al. 2021

2021 International Conference on Computer Communications and Networks (ICCCN)

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“…We also conducted a comparison between the most well-known authenticators to reveal how their features affect the needs of a user. Each authentication mechanism has its own authenticator, and we examined their characteristics and operational features to find out how they work and justify the selection of one [10].…”

Section: Related Workmentioning

confidence: 99%

A Novel Authentication Method That Combines Honeytokens and Google Authenticator

et al. 2023

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Despite the rapid development of technology, computer systems still rely heavily on passwords for security, which can be problematic. Although multi-factor authentication has been introduced, it is not completely effective against more advanced attacks. To address this, this study proposes a new two-factor authentication method that uses honeytokens. Honeytokens and Google Authenticator are combined to create a stronger authentication process. The proposed approach aims to provide additional layers of security and protection to computer systems, increasing their overall security beyond what is currently provided by single-password or standard two-factor authentication methods. The key difference is that the proposed system resembles a two-factor authentication but, in reality, works like a multi-factor authentication system. Multi-factor authentication (MFA) is a security technique that verifies a user’s identity by requiring multiple credentials from distinct categories. These typically include knowledge factors (something the user knows, such as a password or PIN), possession factors (something the user has, such as a mobile phone or security token), and inherence factors (something the user is, such as a biometric characteristic like a fingerprint). This multi-tiered approach significantly enhances protection against potential attacks. We examined and evaluated our system’s robustness against various types of attacks. From the user’s side, the system is as friendly as a two-factor authentication method with an authenticator and is more secure.

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“…An app system that improves identity-based encryption and generates safe credentials with an identity bit string component reduces identity leakage (Gupta et al, 2022). This technique is more secure than single-password or two-factor authentication since it uses many layers (Papaspirou et al, 2022). This project attempts to provide a complex authentication system that improves website security and user experience.…”

Section: Introductionmentioning

confidence: 99%

Enhancing User Authentication with Facial Recognition and Feature-Based Credentials

Mohialden,

Hussien,

Ali

2023

JLMA

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This research proposes a novel and trustworthy user authentication method that creates individualized and trusted credentials based on distinctive facial traits using facial recognition technology. The ability to easily validate user identification across various login methods is provided by this feature. The fundamental elements of this system are face recognition, feature extraction, and the hashing of characteristics to produce usernames and passwords. This method makes use of the OpenCV library, which is free software for computer vision. Additionally, it employs Hashlib for secure hashing and Image-based Deep Learning for Identification (IDLI) technology to extract facial tags. For increased security and dependability, the system mandates a maximum of ten characters for users and passwords. By imposing this restriction, the system increases its resilience by reducing any possible weaknesses in its defense. The policy also generates certificates that are neatly arranged in an Excel file for easy access and management. To improve user data and provide reliable biometric authentication, this study intends to create and implement a recognition system that incorporates cutting-edge approaches such as face feature extraction, feature hashing, and password creation. Additionally, the system has robust security features using face recognition.

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Security Revisited: Honeytokens meet Google Authenticator

Cited by 4 publications

References 0 publications

A novel Two-Factor HoneyToken Authentication Mechanism

A novel Two-Factor HoneyToken Authentication Mechanism

A Novel Authentication Method That Combines Honeytokens and Google Authenticator

Enhancing User Authentication with Facial Recognition and Feature-Based Credentials

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