Analysis and Intellectual Structure of the Multi-Factor Authentication in Information Security

Saqib, Rashad Mahmood; Khan, Adnan Shahid; Javed, Yasir; Ahmad, Shakil; Nisar, Kashif; Abbasi, Irshad Ahmed; Haque, Muhammad Reazul; Julaihi, Azlina Ahmadi

doi:10.32604/iasc.2022.021786

Cited by 16 publications

(7 citation statements)

References 57 publications

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“…In [37], a bibliometric survey was performed based on Web of Science data for research publications on the topic of MFA. Furthermore, we summarize the use of MFA through a different number of factors for cloud computing environments in Table 1.…”

Section: Literature Reviewmentioning

confidence: 99%

Strengthening Cloud Security: An Innovative Multi-Factor Multi-Layer Authentication Framework for Cloud User Authentication

Mostafa,

Ezz,

Elbashir

et al. 2023

Applied Sciences

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Cloud multi-factor authentication is a critical security measure that helps strengthen cloud security from unauthorized access and data breaches. Multi-factor authentication verifies that authentic cloud users are only authorized to access cloud apps, data, services, and resources, making it more secure for enterprises and less inconvenient for users. The number of authentication factors varies based on the security framework’s architecture and the required security level. Therefore, implementing a secured multi-factor authentication framework in a cloud platform is a challenging process. In this paper, we developed an adaptive multi-factor multi-layer authentication framework that embeds an access control and intrusion detection mechanisms with an automated selection of authentication methods. The core objective is to enhance a secured cloud platform with low false positive alarms that makes it more difficult for intruders to access the cloud system. To enhance the authentication mechanism and reduce false alarms, multiple authentication factors that include the length, validity, and value of the user factor is implemented with a user’s geolocation and user’s browser confirmation method that increase the identity verification of cloud users. An additional AES-based encryption component is applied to data, which are protected from being disclosed. The AES encryption mechanism is implemented to conceal the login information on the directory provider of the cloud. The proposed framework demonstrated excellent performance in identifying potentially malicious users and intruders, thereby effectively preventing any intentional attacks on the cloud services and data.

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Section: Literature Reviewmentioning

confidence: 99%

Strengthening Cloud Security: An Innovative Multi-Factor Multi-Layer Authentication Framework for Cloud User Authentication

Mostafa,

Ezz,

Elbashir

et al. 2023

Applied Sciences

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“…Also,

m

is the reference time indicating the location in the time domain signal, while

\omega

is the angular frequency. The

w\left[n\right]

is the analysis window function that is only non‐zero during the interval

\left[0,N-1\right]

and is used to divide

x\left[n\right]

into small chunks, The spectrogram is then calculated as,

\mathrm{Spectrogram}\ \left(m,\omega \right)={\left| STFT\left\{x\left[n\right]\right\}\right|}^2={\left|X\Big(m,\omega \Big)\right|}^2

where the energy is distributed and visualized in the form of heatmaps in the two‐dimensional time‐frequency plane 36 …”

Section: Preliminary Conceptsmentioning

confidence: 99%

MS‐ADS: Multistage Spectrogram image‐based Anomaly Detection System for IoT security

Ahmad

Khan

Zen

et al. 2023

Trans Emerging Tel Tech

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The innovative computing idea of Internet‐of‐Things (IoT) architecture has gained tremendous popularity over the last decade, resulting in an exponential increase in the connected devices and the data processed in the IoT networks. Since IoT devices collect a massive amount of sensitive information exchanged over the traditional internet, security has become a prime concern due to the more frequent generation of network anomalies. A network‐based anomaly detection system can provide the much‐needed efficient security solution to the IoT network by detecting anomalies at the network entry points through constant traffic monitoring. Despite enormous efforts by researchers, these detection systems still suffer from lower detection accuracy in detecting anomalies and generate a high false alarm rate and false‐negative rate in classifying network traffic. To this end, this paper proposes an efficient Multistage Spectrogram image‐based network Anomaly Detection System (MS‐ADS) using a deep convolution neural network that utilizes a short‐time Fourier Transform to transform flow features into spectrogram images. The results demonstrate that the proposed method achieves high detection accuracy of 99.98% with a reduction in the false alarm rate to 0.006% in classifying network traffic. Also, the proposed scheme improves predicting the anomaly instances by 0.75% to 4.82%, comparing the benchmark methodologies to exhibit its efficiency for the IoT network. To minimize the computational and training cost for the model re‐training phase, the proposed solution demonstrates that only 40500 network flows from the dataset suffice to achieve a detection accuracy of 99.5%.

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“…Simple use of MFA mitigates phishing [12] and spear phishing [13] attacks those attacks provide a possibility to steal login and password but MFA/2FA tokens prevent this risk.…”

Section: Figure 2 Architecture Diagram Generation Hotpmentioning

confidence: 99%

Comparison of information security methods of information-communication infrastructure: Multi-Factor Authentication

Safin,

Abdiraman,

Nurusheva

et al. 2022

bultechenukz

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Sensitive information was always one of the big trade-offs we always exchange big secrets for small ones. On one hand, memorization of small secrets on the other hand tons of services requires a dedicated secret for each one. And when one of the services will be compromised it affects all services with the same password and credential. The main purpose of this article is to discuss multiple factors and increase security trade-offs differently. We will try to compare MFA (Multi-Factor Authentication), 2FA (Two Factor Authentication), 2SV (Two-Step Verification), and 1FA (One Factor Authentication) and investigate the password-free future.

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Analysis and Intellectual Structure of the Multi-Factor Authentication in Information Security

Cited by 16 publications

References 57 publications

Strengthening Cloud Security: An Innovative Multi-Factor Multi-Layer Authentication Framework for Cloud User Authentication

Strengthening Cloud Security: An Innovative Multi-Factor Multi-Layer Authentication Framework for Cloud User Authentication

MS‐ADS: Multistage Spectrogram image‐based Anomaly Detection System for IoT security

Comparison of information security methods of information-communication infrastructure: Multi-Factor Authentication

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