Institut Teknologi Bandung Reports Findings in Life Science Research (Pricing of cyber insurance premiums using a Markov-based dynamic model with clustering structure): Life Science Research

2021 NOV 04 (NewsRx) -- By a News Reporter-Staff News Editor at Engineering Daily News -- New research on Life Science Research is the subject of a report. According to news reporting originating from Bandung, Indonesia, by NewsRx correspondents, research stated, “Cyber insurance is a risk management option to cover financial losses caused by cyberattacks. Researchers have focused their attention on cyber insurance during the last decade.”

Our news editors obtained a quote from the research from Institut Teknologi Bandung, “One of the primary issues related to cyber insurance is estimating the premium. The effect of network topology has been heavily explored in the previous three years in cyber risk modeling. However, none of the approaches has assessed the influence of clustering structures. Numerous earlier investigations have indicated that internal links within a cluster reduce transmission speed or efficacy. As a result, the clustering coefficient metric becomes crucial in understanding the effectiveness of viral transmission. We provide a modified Markov-based dynamic model in this paper that incorporates the influence of the clustering structure on calculating cyber insurance premiums. The objective is to create less expensive and less homogenous premiums by combining criteria other than degrees. This research proposes a novel method for calculating premiums that gives a competitive market price. We integrated the epidemic inhibition function into the Markov-based model by considering three functions: quadratic, linear, and exponential. Theoretical and numerical evaluations of regular networks suggested that premiums were more realistic than premiums without clustering. Validation on a real network showed a significant improvement in premiums compared to premiums without the clustering structure component despite some variations. Furthermore, the three functions demonstrated very high correlations between the premium, the total inhibition function of neighbors, and the speed of the inhibition function.”

According to the news editors, the research concluded: “Thus, the proposed method can provide application flexibility by adapting to specific company requirements and network configurations.”

For more information on this research see: Pricing of cyber insurance premiums using a Markov-based dynamic model with clustering structure. PLOS ONE, 2021;16(10). PLOS ONE can be contacted at: Public Library Science, 1160 Battery Street, Ste 100, San Francisco, CA 94111, USA. (Public Library of Science - www.plos.org; PLOS ONE - www.plosone.org)

The news editors report that additional information may be obtained by contacting Sapto Wahyu Indratno, Statistics Research Division, Institut Teknologi Bandung, Bandung, West Java, Indonesia. Additional authors for this research include Yeftanus Antonio and Suhadi Wido Saputro.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1371/journal.pone.0258867. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Publisher contact information for the journal PLOS ONE is: Public Library Science, 1160 Battery Street, Ste 100, San Francisco, CA 94111, USA.

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