Performance Evaluation of a new one-time password (OTP) scheme using stochastic petri net (SPN)

Khan, Razib Hayat; Miah, Jonayet

doi:10.1109/aiiot54504.2022.9817203

Cited by 8 publications

(6 citation statements)

References 3 publications

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“…Replay attacks are a type of MiTM attack where an attacker captures a legitimate authentication request and resends it later. This can be done to gain unauthorized access to an online banking account [114]- [116].…”

Section: ) Replay Attackmentioning

confidence: 99%

Online Banking User Authentication Methods: A Systematic Literature Review

Karim,

Khashan,

Kanaker

et al. 2024

IEEE Access

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Online banking has become increasingly popular in recent years, making it a target for cyberattacks. Banks have implemented various user authentication methods to protect their customers' online accounts. This paper reviews the state-of-the-art user authentication methods used in online banking and potential cyber threats. This paper starts by exploring different user authentication methods, such as knowledge-based authentication (KBA), biometrics-based authentication (BBA), possession-based authentication (PBA), and other methods. The advantages and disadvantages of each user authentication method are then discussed. Furthermore, the paper discusses the various cyber threats that can compromise user authentication for online banking systems, such as malware attacks, social engineering, phishing attacks, man-in-the-middle (MiTM) attacks, denial of service (DoS) attacks, session hijacking, weak passwords, keyloggers, SQL injection, and replay attacks. Also, the paper explores the user authentication methods used by popular banks, which can provide insights into best practices for safeguarding online banking accounts and future user authentication methods in online banking and cyber threats. It states that the increasing use of BBA, two-factor authentication (2FA), and multi-factor authentication (MFA) will help improve the security of online banking systems. However, the paper also warns that new cyber challenges will emerge, and banks need to be vigilant in protecting their customers' online banking accounts.

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Section: ) Replay Attackmentioning

confidence: 99%

Online Banking User Authentication Methods: A Systematic Literature Review

Karim,

Khashan,

Kanaker

et al. 2024

IEEE Access

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“…By leveraging alert messages for transaction verification and OTPs for authentication, this approach mitigates the risk of fraudulent activities. In addressing the limitations of existing OTP systems, [2] introduces a novel method that incorporates an intermediate mathematical calculation step to enhance security. Using stochastic Petri net (SPN) models for performance evaluation, the proposed scheme demonstrates improvements in processing and verification, thus ensuring a more secure authentication process.…”

Section: Literature Reviewmentioning

confidence: 99%

Alpha Identification Based Otp System

Prof. Sonali Patil,

Parth Tagadpallewar,

Nayan Pagare

et al. 2024

Int Res J Adv Engg Hub

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In the realm of contemporary digital security, this study focuses on enhancing Secure OTP Management. The Alphabetical ID system is a pivotal solution to bolster security and streamline user authentication. It strategically displays three alphabetic characters in both the generated OTP sent to the user and the interface for OTP input. This design empowers users to identify the latest OTP among received codes, addressing the dilemma of consecutive OTPs causing confusion and potential access denial. The Alphabetical ID system revolutionizes identification protocols, significantly reducing the likelihood of unauthorized access. This heightened identification capability serves as a robust safeguard for sensitive data and reinforces the integrity of digital transactions. The synergy between the Alphabetical ID system and the conventional OTP process marks a paradigm shifts in user authentication, achieving an optimal balance between user experience and identification precision. As businesses transition towards digitization and online interactions, the Alphabetical ID system emerges as a pioneering leap, offering a reliable shield against unauthorized access and catalyzing fortified digital security. This inventive solution stands as a pragmatic answer to the challenge of identification in OTP management, culminating in an elegant fusion of simplicity and efficacy. The proposed Alphabetical ID system is poised to redefine the landscape of Secure OTP Management by placing a heightened emphasis on user-friendly identification mechanisms within the broader context of digital security.

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“…The breast cancer dataset utilized in this research, known as Breast Histopathology Images, is sourced from the publicly accessible platform Kaggle [16]. The initial dataset comprises 162 whole-mount slide photos of breast cancer samples scanned at 40x, as reported by the dataset source [17]. These images were subsequently extracted and categorized into two groups: Invasive Ductal Carcinoma (IDC) positive and IDC negative.…”

Section: Dataset Collection and Preprocessingmentioning

confidence: 99%

Transforming Breast Cancer Identification: An In-Depth Examination of Advanced Machine Learning Models Applied to Histopathological Images

Rejon Kumar Ray,

Ahmed Ali Linkon,

Mohammad Shafiquzzaman Bhuiyan

et al. 2024

JCSTS

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Breast cancer stands as one of the most prevalent and perilous forms of cancer affecting both women and men. The detection and treatment of breast cancer benefit significantly from histopathological images, which carry crucial phenotypic information. To enhance accuracy in breast cancer detection, Deep Neural Networks (DNNs) are commonly utilized. Our research delves into the analysis of pre-trained deep transfer learning models, including ResNet50, ResNet101, VGG16, and VGG19, for identifying breast cancer using a dataset comprising 2453 histopathology images. The dataset categorizes images into two groups: those featuring invasive ductal carcinoma (IDC) and those without IDC. Through our analysis of transfer learning models, we observed that ResNet50 outperformed the other models, achieving impressive metrics such as accuracy rates of 92.2%, Area under Curve (AUC) rates of 91.0%, recall rates of 95.7%, and a minimal loss of 3.5%.

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Performance Evaluation of a new one-time password (OTP) scheme using stochastic petri net (SPN)

Cited by 8 publications

References 3 publications

Online Banking User Authentication Methods: A Systematic Literature Review

Online Banking User Authentication Methods: A Systematic Literature Review

Alpha Identification Based Otp System

Transforming Breast Cancer Identification: An In-Depth Examination of Advanced Machine Learning Models Applied to Histopathological Images

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