Biblio

In the 21st century, each country must make decisions on how to utilize modern technologies to maximize benefits and minimize repercussions. For example, the United States Department of Defense (DoD) needs to be able to share information efficiently with its allies while simultaneously preventing unwarranted access or attacks. These attacks pose a threat to the national security of the United States, but proper use of the cyberspace provides countless benefits. The aim of this paper is to explore Identity and Access Management (IdAM) technologies that the Department of Defense can use in joint operations with allies that will allow efficient information-sharing and enhance security. To this end, we have created a methodology and a model for evaluating Identity and Access Management technologies that the Department of Defense can use in joint operations with other nations, with a specific focus on Japan and Australia. To evaluate these systems, we employed an approach that incorporates Political, Operational, Economic and Technical (POET) factors. Governance protocols, technological solutions, and political factors were first thoroughly reviewed and then used to construct an evaluation model to formally assess Identity and Access Management alternatives. This model provides systematic guidance on how the Department of Defense can improve their use of Identity and Access Management systems in the future.

The interaction between information technology and phys ical world makes Cyber-Physical Systems (CPS) vulnerable to malicious attacks beyond the standard cyber attacks. This has motivated the need for attack-resilient state estimation. Yet, the existing state-estimators are based on the non-realistic assumption that the exact system model is known. Consequently, in this work we present a method for state estimation in presence of attacks, for systems with noise and modeling errors. When the the estimated states are used by a state-based feedback controller, we show that the attacker cannot destabilize the system by exploiting the difference between the model used for the state estimation and the real physical dynamics of the system. Furthermore, we describe how implementation issues such as jitter, latency and synchronization errors can be mapped into parameters of the state estimation procedure that describe modeling errors, and provide a bound on the state-estimation error caused by modeling errors. This enables mapping control performance requirements into real-time (i.e., timing related) specifications imposed on the underlying platform. Finally, we illustrate and experimentally evaluate this approach on an unmanned ground vehicle case-study.