Next-generation cybersecurity via data fusion, AI, and big data

Be it the global financial institution or the critical infrastructure that runs essential services in our lives, at the center is trust. Trust is a differentiator for the modern customer, and in a hyperconnected world, customers demand that their most sensitive personal information (i.e., identity, address, salary, mortgage, credit card spending, pension, travel, and shopping habits) and their essential services are kept safe. We share outcomes and lessons learned from building and deploying a global data fusion, incident analysis/visualization, and effective cybersecurity defense based on big data and AI at a large bank, in collaboration with several financial services institutions. We also cover some case studies in critical infrastructure cybersecurity.

The new “fusion cell” concept that is able to utilize big data, AI, and machine learning enables a truly strategic view for the bank’s operations and has already led to new and enhanced functions, including cyberintelligence, insider threats, red teaming, threat hunting, cyberinnovation, and outreach. At the heart of the system is a context cloud, as the change from big data is powered by the context and focus. Context, generated by analytical judgements, reference data and historical understanding is pushed into the stream enriching new data automatically. This means a human-led, machine-driven SOC with highly trained and skilled analysts at its heart. It is also supported by next-generation technology and expanded insight. Analysis and response requires the ability to create inference based on machine learning, statistics, and other matching techniques. We will use some case studies in banking and in protection of critical infrastructure to illustrate these concepts. Absolute security does not exist in the physical world; neither does it exist in the virtual world. If we invest in next-generation security and cooperate, we will, at least, be able to provide the same - and hopefully acceptable - level of security in both worlds.

This talk tries to capture contributions of AI/ML/Data Science to the area of cybersecurity in general. We start with a historical summary that summarizes the hype and tries to separate it from the reality of what actually works in the enterprise. We include concrete lessons for making AI/ML work pragmatically in the enterprise and in meaningful applications. We conclude with case studies in financial services and in critical infrastructure cyber protection.

Speaker: Usama Fayyad, Open Insights and OODA Health