International Journal of Advances in Intelligent Informatics ISSN 2442-6571 Vol. 7, No. 3, November 2021, pp. 237-248 237 https://doi.org/10.26555/ijain.v7i3.698 http://ijain.org ijain@uad.ac.id Adjusting cyber insurance premiums based on frequency in a communication network Sapto Wahyu Indratno a,b,1,* , Yeftanus Antonio a,2 , Suhadi Wido Saputro c,3 a Statistics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung 40132, West Java, Indonesia b University Center of Excellence on Artificial Intelligence for Vision, Institut Teknologi Bandung, Bandung 40132, West Java, Indonesia c Combinatorial Mathematics Research Division, Institut Teknologi Bandung, Bandung 40132, West Java, Indonesia 1 sapto@math.itb.ac.id; 2 yeftanus@students.itb.ac.id; 3 suhadi@math.itb.ac.id * corresponding author 1. Introduction Cyber insurance is a risk management tool to transfer financial losses due to communication and information technology operations [1]–[3]. Economic damage caused by cyberattacks shows an increasing trend in the range of 1.1% to more than 30% of the global gross domestic product [4]. The annual cost of cybercrime is estimated to reach USD 6 trillion by 2021, which is more than twice that of 2015 [5]. This condition can improve cyber insurance sales and the market in the coming years. Cyber insurance still has some technical challenges [6]. One of the main issues associated with cyber insurance is how to estimate premiums or rates [7], [8]. Today, there is no established pricing method for cyber insurance products. Some of the available products are offered at high prices because of the long and complicated identification and selection of risks (underwriting) [9]. Several existing risk models consider the demand and supply of the product. Other factors to consider are assumptions regarding network structure, computer information, and attack’s timing. Information and communication technology ARTICLE INFO ABSTRACT Article history Selected paper from The 2020 3rd International Symposium on Advanced Intelligent Informatics (SAIN’20), Virtual, 25-26 November 2020, http://sain.ijain.org/2020/. Peer-reviewed by SAIN’20 Scientific Committee and Editorial Team of IJAIN journal. Received November 23, 2020 Revised August 9, 2021 Accepted August 9, 2021 Available online November 30, 2021 This study compares cyber insurance premiums with and without a communication network effect frequency. As a cybersecurity factor, the frequency in a communication network influences the speed of cyberattack transmission. It means that a network or a high activity node is more vulnerable than a network with low activity. Traditionally, cyber insurance pricing considers historical data to set premiums or rates. Conversely, the network security level can evaluate using the Monte Carlo simulation based on the epidemic model. This simulation requires spreading parameters, such as infection rate, recovery rate, and self-infection rate. Our idea is to modify the infection rate as a function of the frequency in a communication network. The node-based model uses probability distributions for the communication mechanism to generate the data. It adopts the co-purchase network formation in market basket analysis for building weighted edges and nodes. Simulations are used to compare the initial and modified infection rates. This paper considered prism and Petersen graph topology as case studies. The relative difference is a metric to compare the significance of premium adjustment. The results show that the premium for a node with a low level in a communication network can reach 28.28% lower than the initial premium. The premium can reach 20.99% lower than the initial network premium for a network. Based on these results, insurance companies can adjust cyber insurance premiums based on computer usage to offer a more appropriate price. This is an open access article under the CC–BY-SA license. Keywords Communication network Cyber insurance Frequency Node-based model Premium adjustment