Ad hoc networks are very helpful in situations when no fixed network infrastructure is available, such as natural disasters and military conflicts. In such a network, all wireless nodes are equal peers simultaneously serving as both senders and routers for other nodes. Therefore, how to route packets through reliable paths becomes a fundamental problems when behaviors of certain nodes deviate from wireless ad hoc routing protocols. We proposed a novel Dirichlet reputation model based on Bayesian inference theory which evaluates reliability of each node in terms of packet delivery. Our system offers a way to predict and select a reliable path through combination of first-hand observation and second-hand reputation reports. We also proposed moving window mechanism which helps to adjust ours responsiveness of our system to changes of node behaviors. We integrated the Dirichlet reputation into routing protocol of wireless ad hoc networks. Our extensive simulation indicates that our proposed reputation system can improve good throughput of the network and reduce negative impacts caused by misbehaving nodes.

With new technology such as cloud computing emerging, parties communicate directly with each other to exchange files or execute transaction in a peer-to-peer fashion. Therefore, peers have to manage the risks involved in the collaboration when prior experience and knowledge about each other are imcomplete. The behaviors of a party are undertain and attributes of a party, requested objects, and context information are mutable. To address above changllenges, we integrate Dirichlet reputation into usage control to manage authentication and authorization in a collaborative enviornment. We added moving window mechanism to the Dirichlet reputation evaluation. Moving windows not only help to adjust our responsiveness of our system to changes in peers' behaviors, but also allow us to use different strategies to react to different group of peers. Our system offers a way to handle uncertainty and mutability by dynamically revoke granted privileges from a party due to low reputation or changed attributes and context information.

To graduate students accustomed to working with the numerical solution of partial differential equations using finite difference, finite elements, spectral methods, etc. where time generally progresses in evenlyspaced small intervals, switching paradigms to a discrete-event simulation environment is not only counterintuitive but is also difficult. The SimCenter at the University of Tennessee Chattanooga recently introduced a class in discrete event simulation with the goal of providing sufficient coverage of the topic to enable any of thH 6LP&HQWHU ¶V VWXGHQWV FRPSOHWLQJ the course to work effectively in a typical industry-or government-supported simulation modeling group. The course is structured around a diverse set of engineering problems rather than traditional industrial engineering-type simulations in order to present the material in a more palatable fashion for students who come primarily from other disciplines. This paper discusses the organization of the class and serves as a good outline for another professor attempting a similar introduction.

Application features such as port numbers are used by Network-based Intrusion Detection Systems (NIDSs) to detect attacks coming from networks. System calls and the operating system related information are used by Host-based Intrusion Detection Systems (HIDSs) to detect intrusions towards a host. However, the relationship between hardware architecture events and Denial-of-Service (DoS) attacks has not been well revealed. When increasingly sophisticated intrusions emerge, some attacks are able to bypass both the application and the operating system level feature monitors. Therefore, a more effective solution is required to enhance existing HIDSs. In this paper, we identify the following hardware architecture features: Instruction Count, Cache Miss, Bus Traffic and integrate them into a novel HIDS framework based on a modern statistical Gradient Boosting Trees model. Through the integration of application, operating system and architecture level features, our proposed HIDS demonstrates a significant improvement of the detection rate in terms of sophisticated DoS intrusions.