Attack-Resilient TLS Certificate Transparency

Khan, Salabat; Zhu, Liehuang; Zhang, Zijian; Rahim, Mussadiq Abdul; Khan, Khalid; Li, Meng

doi:10.1109/access.2020.2996997

Cited by 7 publications

(2 citation statements)

References 47 publications

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“…To calculate the clustering coefficient of these networks, scientists apply the query to nodes other than the sampled nodes. In fact, in social networks and large scale networks, the estimation of network-based features is difficult because the sizes of these networks are extremely large [28,29]. Also, they contain large datasets that are occasionally unavailable because of privacy concerns [30].…”

Section: Introductionmentioning

confidence: 99%

Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

Amin¹,

Choi²

2022

Computers, Materials &Amp; Continua

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The Internet of Things (IoT) has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses. Social network analysis (SNA) is a good example that has recently gained a lot of scientific attention. It has its roots in social and economic research, as well as the evaluation of network science, such as graph theory. Scientists in this area have subverted predefined theories, offering revolutionary ones regarding interconnected networks, and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon. The motivation of this study is to understand and capture the clustering properties of large networks and social networks. We present a network growth model in this paper and build a scale-free artificial social network with controllable clustering coefficients. The random walk technique is paired with a triangle generating scheme in our proposed model. As a result, the clustering control mechanism and preferential attachment (PA) have been realized. This research builds on the present random walk model. We took numerous measurements for validation, including degree behavior and the measure of clustering decay in terms of node degree, among other things. Finally, we conclude that our suggested random walk model is more efficient and accurate than previous state-of-the-art methods, and hence it could be a viable alternative for societal evolution.

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Section: Introductionmentioning

confidence: 99%

Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

Amin¹,

Choi²

2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…The proposed method achieves transparency, provides a framework for service-level agreement (SLA) enforcement, and relaxes availability requirements. The recent work of S. Khan, et al on attack-resilient TLS certificate transparency has motivated further research [ 15 ]. A secure transmission on the cost of computation and routing overhead is a problem for 5G/6G.…”

Section: Introductionmentioning

confidence: 99%