Kernel naïve Bayes classifier-based cyber-risk assessment and mitigation framework for online gaming platforms

ABSTRACT

Recently, the number and intensity of cyberattacks against massively multiplayer online (MMO) gaming platforms have increased; up to 74% of distributed denial-of-service (DDoS) attacks on MMO gaming (MMOG) firms have been launched by hackers. These malicious attacks affect gamers’ experience and MMOG firms’ revenue model. Along with financial losses, MMOG firms’ reputation also suffers from these attacks. Therefore, in this study, we devised a framework to quantify and mitigate cyber-risk for MMOG firms using a hybrid learning method, namely, a kernel naïve Bayes classifier. Our kernel naïve Bayes classifier-based cyber-risk assessment and mitigation (KB-CRAM) framework included the DDoS attack traits. Subsequently, it outputs (i) the probability of DDoS attacks; (ii) the expected financial losses; and (iii) cyber-risk mitigation strategies, such as self-protection (technology, compliance, and legal deterrence), self-insurance, or cyber-insurance. Our study contributes to field-relevant literature by providing managers with a tool to improve game performance. This framework also suggests ways in which MMOG firms can hedge losses against repeated attacks from unethical hackers.

KEYWORDS:

• Cyberattack
• hacker
• massively multiplayer online games
• gamer
• cyber-risk
• data mining
• naïve bayes
• cyber-insurance
• cyber-risk assessment
• cyber-risk mitigation

Disclosure statement

The authors declare that there is no conflict of interest

Additional information

Notes on contributors

Kalpit Sharma

Kalpit Sharma Kalpit Sharma is a Doctoral student at the Indian Institute of Management (IIM) Lucknow. He has published articles in journals and conferences of international repute, including Americas Conference on Information Systems (AMCIS), Pre-International Conference On Information Systems (ICIS) workshops, ISACA Journal. His research interests include cyber-risk issues in information systems, the economics of cybersecurity, healthcare IT, IT governance, and crowd-based digital business models.

Arunabha Mukhopadhyay

Arunabha Mukhopadhyay Dr. Arunabha Mukhopadhyay is a Professor of Information Technology & Systems Area at the Indian Institute of Management Lucknow (IIM Lucknow). He has obtained his Ph.D. and Post Graduate Diploma in Business Management (PGDBM) from the Indian Institute of Management Calcutta (IIM Calcutta) in Management Information Systems. He has published in various refereed journals and conferences, including Decision Support Systems (DSS), Information Systems Frontier (ISF), Journal of Organizational Computing and E-commerce (JOCEC), Journal of Global Information Technology Management (JGITM), JIPS, International Journal of Information Systems and Change Management (IJISCM), Decision, IIMB Review, Hawaii International Conference on System Sciences (HICSS), Americas Conference on Information Systems (AMCIS), Pre-International Conference On Information Systems (ICIS) workshops, Global Information Technology Management Association (GITMA), Conference of Information Systems and Technology Management (CISTM), International Conference on E-Governance (ICEG). He is the recipient of the Best Teacher in Information Technology Management award in 2013 and 2011, by the Star-DNA group B-School Award and the 19th Dewang Mehta Business School Award, in India, respectively. He is a Member of IEEE, AIS, ISACA, DSI, ITS, IFIP WG 11.1 and a Life Member of Computer Society of India (CSI), Telemedicine Society of India (TSI), Indian Insurance Institute (III), Actuarial Society of India (ASI), All India Management Association (AIMA), System Dynamics Society of India (SDSI) and, Operations Research Society of India (ORSI).