Understand, Manage, and Measure Cyber Risk

AbstractThe Internet-of-Things (IoT) triggers data protection questions and new types of cyber risks. Cyber risk regulations for the IoT, however, are still in their infancy. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. At present, there are no self-assessment methods for quantifying IoT cyber risk posture. It is considered that IoT represent a complex system with too many uncontrollable risk states for quantitative risk assessment. To enable quantitative risk assessment of uncontrollable risk states in complex and coupled IoT systems, a new epistemological equation is designed and tested though comparative and empirical analysis. The comparative analysis is conducted on national digital strategies, followed by an empirical analysis of cyber risk assessment approaches. The results from the analysis present the current and a target state for IoT systems, followed by a transformation roadmap, describing how IoT systems can achieve the target state with a new epistemological analysis model. The new epistemological analysis approach enables the assessment of uncontrollable risk states in complex IoT systems—which begin to resemble artificial intelligence—and can be used for a quantitative self-assessment of IoT cyber risk posture.

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Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

Safety in Extreme Environments ◽

10.1007/s42797-021-00025-1 ◽

2021 ◽

Author(s):

Petar Radanliev ◽

David De Roure ◽

Kevin Page ◽

Max Van Kleek ◽

Omar Santos ◽

...

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Real Time ◽

Cyber Security ◽

Extreme Environments ◽

Learning Technologies ◽

Cyber Attacks ◽

Edge Computing ◽

Mathematical Formulas ◽

Cyber Risk

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.

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Qualitative Risk Assessment of Cybersecurity and Development of Vulnerability Enhancement Plans in Consideration of Digitalized Ship

Journal of Marine Science and Engineering ◽

10.3390/jmse9060565 ◽

2021 ◽

Vol 9 (6) ◽

pp. 565

Author(s):

Yunja Yoo ◽

Han-Seon Park

Keyword(s):

Risk Assessment ◽

Safety Management ◽

International Standards ◽

Security Risk ◽

Analytic Hierarchy ◽

Improvement Plan ◽

Qualitative Risk Assessment ◽

Cyber Risk ◽

Hierarchy Process ◽

Ship Safety

The International Maritime Organization (IMO) published the Guidelines on Maritime Cyber Risk Management in 2017 to strengthen cybersecurity in consideration of digitalized ships. As part of these guidelines, the IMO recommends that each flag state should integrate and manage matters regarding cyber risk in the ship safety management system (SMS) according to the International Safety Management Code (ISM Code) before the first annual verification that takes place on or after 1 January 2021. The purpose of this paper is to identify cybersecurity risk components in the maritime sector that should be managed by the SMS in 2021 and to derive priorities for vulnerability improvement plans through itemized risk assessment. To this end, qualitative risk assessment (RA) was carried out for administrative, technical, and physical security risk components based on industry and international standards, which were additionally presented in the IMO guidelines. Based on the risk matrix from the RA analysis results, a survey on improving cybersecurity vulnerabilities in the maritime sector was conducted, and the analytic hierarchy process was used to analyze the results and derive improvement plan priority measures.

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Workshop on Internet Economics (WIE 2020) final report

ACM SIGCOMM Computer Communication Review ◽

10.1145/3464994.3464999 ◽

2021 ◽

Vol 51 (2) ◽

pp. 25-27

Author(s):

kc claffy ◽

David Clark

Keyword(s):

Open Source Software ◽

Economic Value ◽

Policy Research ◽

Final Report ◽

Internet Economics ◽

Research Topics ◽

Work From Home ◽

Cyber Risk ◽

Successes And Challenges ◽

Support Evidence

On 16-17 December 2020, CAIDA hosted the 11th interdisciplinary Workshop on Internet Economics (WIE) in a virtual Zoom conference. This year our goal was to gather feedback from researchers on their experiences using CAIDA’s data for economics or policy research. We invited all researchers who reported use of CAIDA data in these disciplines. We discussed their successes and challenges of using the data, and how CAIDA could help these fields via Internet measurement and data curation. To avoid Zoom fatigue, we had a conversation-focused rather than presentation-focused workshop. Research topics we discussed included: Internet data for macroeconomics; connectivity and its effect on economic interdependence; effects of the EU’s new GDPR on internet interconnection; measuring corporate cyber risk; measuring work-from-home trends; measuring the economic value of open source software; and more generally how to best support evidence-based policymaking.

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