6/24/2016Financial Services Sector Coordinating Council For Critical Infrastructure Protection R&D Committee 1 Financial Cybersecurity in Complex, Heterogeneous Data Environments Martha Grabowski Le Moyne College Rensselaer Polytechnic Institute 7 May 2010

6/24/20162 Banking and Financial Systems Secure, resilient and reliable systems Seamless operations Public confidence in monetary systems Public-private partnerships for information sharing Industry-academia-government project

6/24/20163 Financial Services Sector Coordinating Council R&D Committee (FSSCC) Priorities Enrollment and identity credential management --identify, authenticate and authorize customers --provide controls to reduce vulnerabilities --improve identity management processes --reduce social engineering attacks Understanding the human insider threat

6/24/20164 Financial Services Sector Coordinating Council R&D Committee (FSSCC) Priorities Understanding the human insider threat --identify trustworthy candidates --couple historical record and identity confirmation analyses to develop holistic methods --develop data frame to predict likelihood of insider attacks --develop continuous, unobtrusive monitoring systems to reduce insider risks

6/24/20165 Leading Indicators Conditions, events, patterns or measures that precede an undesirable event Predict arrival of an event Identify activities to minimize and manage risk Traditionally developed using quantitative data sets Financial, medical, mining, aviation, transportation systems

6/24/20166 Telecommunications data Human Profile, Behavioral data Social network, Web 2.0/3.0 data Multimedia communications data Funds transfer, movement data Transaction data Organizational Culture data Heterogeneous, Complex Data

6/24/20167 Fusion Real-time Monitoring Decision Historical Data Other Information or Data Other Information or Data Prediction (distribution of abnormal events) Indication (early detection) Correlation (symptoms of flaws, signs of suspicious activities, associations with other events) Time-series Models, Statistical Estimations Geometric Brownian Motion & Leading Indicators Probabilistic Methods Approach Fuse results and simulate cyber systems using software agents Detect structural risks, load-related weaknesses and behaviorally-based disruptions Develop population and behaviorally-based models Model and capture interactions between humans and technology, and between design and operations Data cleansing, data mining and integration

6/24/20168 Goals Identify correlations and associations with flaws or suspicious activities Detect anomalies early in analysis/monitoring Predict occurrence of future events

6/24/20169 Results Measure, monitor, mitigate operational risk Requirements for capital Data security Vendor management Benchmarking and generalization Resiliency Maturity Model (CMU, 2008) Implications for other mission- and safety-critical large-scale systems

6/24/ Schedule 2 years September September 2012

6/24/ Project Team Financial Cybersecurity In Complex, Heterogeneous Data Environments Le Moyne College Prof Martha Grabowski Research Assistants Rensselaer Polytechnic Institute Prof W.K. Victor Chan Prof Cheng Hsu Doctoral students

6/24/ Contacts Martha Grabowski Chair, Business Administration Dept Director, Information Systems Program Le Moyne College Syracuse, NY Research Professor Rensselaer Polytechnic Institute Troy, NY