Cybersecurity Risk Conference

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In the past several years, cyber-crime and cyber-breaches have exploded, due to the increase in commerce conducted on the Internet, as well as increasing quantities of sensitive information being stored in databases that can be accessed by outside parties. In addition, cyber-criminals have advanced, not only employing technical acumen but also preying on human error by using sophisticated techniques like phishing. To address these challenges, the Northeast Big Data Innovation Hub (NEBDIH) will convene two workshops to bring together experts from academia, government, and industry in the fields of insurance, cybersecurity, data science, and policy. The ultimate goal is to develop a collaborative model (e.g., a cross sector consortium) that will help to define the frequency and economic/social severity related to successful attacks, and to begin to develop baselines for measuring and managing cyber risk more effectively. NEBDIH will seek to gather leading academic, government, risk management, general industry and healthcare participants, whose mission will be to identify, quantify, and to help mitigate risk associated with cyber-related criminal activity. The workshops will serve as a forum for these experts to collaborate on: 1) better understanding and defining the interrelated cybersecurity landscape across sectors, and 2) planning for the resources necessary to develop baselines for measuring and managing cybersecurity risk. Expected outcomes from these activities include developing a framework for filling the gaps in quantifying and managing cybersecurity risk across organizations and sectors. This may take the form of an initiative that captures the best of breed technologies, vendors, and best practices; captures a substantial portion of the data that is required, in aggregate, to make a cybersecurity risk assessment at multiple levels (by industry, by region, by company); provides the tools to make the data discoverable and interoperable; and provides a basic suite of tools to allow for high level analysis of the data within the context of cybersecurity risk.