This paper describes the experience of our institution in creating a comprehensive undergraduate information assurance (IA) program. An interdisciplinary approach was undertaken in order to include a larger portion of the student body and faculty and thus influence a broader audience. The program includes a wide variety of mutually supporting information assurance activities including a research center, coursework, an information warfare laboratory, a cyber defense exercise, an outreach program, conferences, trips, summer internships, a guest speaker program, a National Security Agency Liaison program, summer student internships, faculty sabbaticals and a student information warfare club. This paper organizes discussion of these activities into the student experience, building faculty expertise, and organizational support. The catalyst for these activities has been the formation of the Military Academy's dedicated information assurance research center, the Information Technology and Operations Center (ITOC), and the continuing support from and interaction with the National Security Agency. The primary goal of this paper is to provide a descriptive resource to educators who wish to implement an undergraduate or graduate level information assurance program. It is our sincere hope to inspire and aid others in starting similar programs.

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It is not uncommon to teach Artificial Intelligence (AI) by asking students to implement agents that embody intelligent behavior. This helps students gain a fuller understanding of the many concepts taught in the course. There are two issues with this approach that deserve attention. First, students come into an AI course knowing how to program in different languages and having different levels of programming ability. Second, it's useful for the students to have a single task environment for all of the agents they program. A solution to both issues lies in a distributed system where the agents are clients communicating with a server that handles a configurable task environment. This allows the students to program their agents in any language and on any platform they desire, so long as they can communicate with the task environment server. If the task environment can be configured to provide additional levels of complexity and difficulty, this allows students to program at a level they are comfortable with. They can then challenge themselves by incorporating more advanced capabilities into their agents. This paper presents just such a distributed and configurable task environment that was developed for an undergraduate AI course.