Pricing and Investments in Internet Security: A Cyber-Insurance Perspective

Internet users such as individuals and organizations are subject to different types of epidemic risks such as worms, viruses, spams, and botnets. To reduce the probability of risk, an Internet user generally invests in traditional security mechanisms like anti-virus and anti-spam software, sometimes also known as self-defense mechanisms. However, such software does not completely eliminate risk. Recent works have considered the problem of residual risk elimination by proposing the idea of cyber-insurance. In this regard, an important research problem is the analysis of optimal user self-defense investments and cyber-insurance contracts under the Internet environment. In this paper, we investigate two problems and their relationship: 1) analyzing optimal self-defense investments in the Internet, under optimal cyber-insurance coverage, where optimality is an insurer objective and 2) designing optimal cyber-insurance contracts for Internet users, where a contract is a (premium, coverage) pair

Computing on Masked Data to improve the Security of Big Data

Organizations that make use of large quantities of information require the ability to store and process data from central locations so that the product can be shared or distributed across a heterogeneous group of users. However, recent events underscore the need for improving the security of data stored in such untrusted servers or databases. Advances in cryptographic techniques and database technologies provide the necessary security functionality but rely on a computational model in which the cloud is used solely for storage and retrieval. Much of big data computation and analytics make use of signal processing fundamentals for computation. As the trend of moving data storage and computation to the cloud increases, homeland security missions should understand the impact of security on key signal processing kernels such as correlation or thresholding. In this article, we propose a tool called Computing on Masked Data (CMD), which combines advances in database technologies and cryptographic tools to provide a low overhead mechanism to offload certain mathematical operations securely to the cloud. This article describes the design and development of the CMD tool.Comment: 6 pages, Accepted to IEEE HST Conferenc

Cyber risk in health facilities: A systematic literature review

The current world challenges include issues such as infectious disease pandemics, environmental health risks, food safety, and crime prevention. Through this article, a special emphasis is given to one of the main challenges in the healthcare sector during the COVID-19 pandemic, the cyber risk. Since the beginning of the Covid-19 pandemic, the World Health Organization has detected a dramatic increase in the number of cyber-attacks. For instance, in Italy the COVID-19 emergency has heavily affected cybersecurity; from January to April 2020, the total of attacks, accidents, and violations of privacy to the detriment of companies and individuals has doubled. Using a systematic and rigorous approach, this paper aims to analyze the literature on the cyber risk in the healthcare sector to understand the real knowledge on this topic. The findings highlight the poor attention of the scientific community on this topic, except in the United States. The literature lacks research contributions to support cyber risk management in subject areas such as Business, Management and Accounting; Social Science; and Mathematics. This research outlines the need to empirically investigate the cyber risk, giving a practical solution to health facilities. Keywords: cyber risk; cyber-attack; cybersecurity; computer security; COVID-19; coronavirus;information technology risk; risk management; risk assessment; health facilities; healthcare sector;systematic literature review; insuranc

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems, cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture