The globalization of today's supply chains (e.g., information and communication technologies, military systems, etc.) has created an emerging security threat that could degrade the integrity and availability of sensitive and critical government data, control systems, and infrastructures. Commercial-off-theshelf (COTS) and even government-off-the-self (GOTS) products often are designed, developed, and manufactured overseas. Counterfeit items, from individual chips to entire systems, have been found in commercial and government sectors. Supply chain attacks can be initiated at any point during the product or system lifecycle, and can have detrimental effects to mission success. To date, there is a lack of analytics and decision support tools used to analyze supply chain security holistically, and to perform tradeoff analyses to determine how to invest in or deploy possible mitigation options for supply chain security such that the return on investment is optimal with respect to cost, efficiency, and security. This paper discusses the development of a supply chain decision analytics framework that will assist decision makers and stakeholders in performing risk-based cost-benefit prioritization of security investments to manage supply chain risk. Key aspects of our framework include the hierarchical supply chain representation, vulnerability and mitigation modeling, risk assessment and optimization. This work is a part of a long term research effort on supply chain decision analytics for trusted systems and communications research challenge.