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DC Field | Value | Language |
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dc.contributor.author | Pal, Ranjan | |
dc.contributor.author | Psounis, Konstantinos | |
dc.contributor.author | Crowcroft, Jon A. | |
dc.contributor.author | Kelly, Frank | |
dc.contributor.author | Hui, Pan | |
dc.contributor.author | Tarkoma, Sasu | |
dc.contributor.author | Kumar, Abhishek | |
dc.contributor.author | Kelly, John | |
dc.contributor.author | Chatterjee, Aritra | |
dc.contributor.author | Golubchik, Leana | |
dc.contributor.author | Sastry, Nishanth R. | |
dc.contributor.author | Nag, Bodhibrata | |
dc.date.accessioned | 2021-08-26T06:05:25Z | - |
dc.date.available | 2021-08-26T06:05:25Z | - |
dc.date.issued | 2020 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090469868&doi=10.1145%2f3386159&partnerID=40&md5=b3f9c710ee2e4f415bcb1d77e3cbe11a | |
dc.identifier.uri | https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1320 | - |
dc.description | Ranjan Pal, Computer Laboratory, University of Cambridge, Cambridge, CB3 OFD, United Kingdom; Konstantinos Psounis, Department of Computer Science and Electrical Engineering, University of Southern California, Los Angeles, CA 90089, United States; Jon A. Crowcroft, Computer Laboratory, University of Cambridge, Cambridge, CB3 OFD, United Kingdom; Frank Kelly, University of Cambridge, Cambridge, CB3 OFD, United Kingdom; Pan Hui, Department of Computer Science, University of Helsinki, Yliopistonkatu 4, Helsinki, 00100, Finland; Sasu Tarkoma, Department of Computer Science, University of Helsinki, Yliopistonkatu 4, Helsinki, 00100, Finland; Abhishek Kumar, Department of Computer Science, University of Helsinki, Yliopistonkatu 4, Helsinki, 00100, Finland; John Kelly, Envelop Risk, Washington, D.C., United States; Aritra Chatterjee, Envelop Risk, Bermuda, Bermuda; Leana Golubchik, Department of Computer Science and Electrical Engineering, University of Southern California, Los Angeles, CA 90089, United States, Envelop Risk, Washington, D.C., United States; Nishanth R. Sastry, King's College London, London, WC2R 2LS, United Kingdom; Bodhibrata Nag, Indian Institute of Management Calcutta, Calcutta, 700104, India | |
dc.description | ISSN/ISBN - 2158656X | |
dc.description | DOI - 10.1145/3386159 | |
dc.description.abstract | Service liability interconnections among globally networked IT- and IoT-driven service organizations create potential channels for cascading service disruptions worth billions of dollars, due to modern cyber-crimes such as DDoS, APT, and ransomware attacks. A natural question that arises in this context is: What is the likelihood of a cyber-blackout?, where the latter term is defined as the probability that all (or a major subset of) organizations in a service chain become dysfunctional in a certain manner due to a cyber-attack at some or all points in the chain. The answer to this question has major implications to risk management businesses such as cyber-insurance when it comes to designing policies by risk-averse insurers for providing coverage to clients in the aftermath of such catastrophic network events. In this article, we investigate this question in general as a function of service chain networks and different cyber-loss distribution types. We show somewhat surprisingly (and discuss the potential practical implications) that, following a cyber-attack, the effect of (a) a network interconnection topology and (b) a wide range of loss distributions on the probability of a cyber-blackout and the increase in total service-related monetary losses across all organizations are mostly very small. The primary rationale behind these results are attributed to degrees of heterogeneity in the revenue base among organizations and the Increasing Failure Rate property of popular (i.i.d/non-i.i.d) loss distributions, i.e., log-concave cyber-loss distributions. The result will enable risk-averse cyber-risk managers to safely infer the impact of cyber-attacks in a worst-case network and distribution oblivious setting. | |
dc.publisher | SCOPUS | |
dc.publisher | ACM Transactions on Management Information Systems | |
dc.publisher | Association for Computing Machinery | |
dc.relation.ispartofseries | 11(2) | |
dc.subject | Cyber-blackout | |
dc.subject | Service network | |
dc.subject | Systemic risk | |
dc.title | When Are Cyber Blackouts in Modern Service Networks Likely? | |
dc.type | Article | |
Appears in Collections: | Operations Management |
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