Sponsored by:
NSF logo
Latest news:
Important Dates:
Contact Information:
Oakland University

2013 Projects

Advisor: Dr. Zohdy
Bio-inspired algorithms are a class of algorithms that translate complex behaviors from nature, such as the movement of ants, into code and then modify them to solve computational problems. One in particular, the Firefly algorithm, mimics the flashing of fireflies for sexual selection, and then solves optimization problems by representing solutions as mobile fireflies. In this project, a new version of the firefly algorithm will be developed by examining the limiting assumptions on the existing version. For example, all fireflies are currently considered unisexual, which could be changed to male and female variants. To optimize the algorithm, extensive coding and testing using Matlab will be performed to determine and quantify performance issues as well as areas of improvement. Applications of the improved algorithm include evolving areas such as Cyber Physical systems, particularly the robotic Dragonfly aerial vehicle.
Advisor: Dr. Shu
Currently, location based services rely upon trusted infrastructure, but Crowdsourced localization, or CL, requires devices requesting their location to cooperate with whichever devices are convenient. Therefore it is necessary that a device be able to hide its location from each untrusted device from which it requests its location. It is also necessary for those devices to hide their location from each other, as well as from the device requesting its location. In this project we developed three protocols that each demonstrate a different level of privacy preservation, the most complex of which will protect both the target and the anchors.
Advisor: Dr. Fu
Our goal is to analyze the effects using different mobility models in VANET simulations on privacy metrics. Vehicle ad hoc networks (VANETs) are an emerging technology planned to be implemented in new vehicles around the world - VANETs allow for increased security and safety while driving, and allows for greater access for information about entertainment and other interesting locations in the area. Despite this, privacy, security, and efficiency concerns are still prevalent, making VANETs a topic of interest in the research community. We do this through simulation and analysis of several mobility models that could potentially be used for vehicular ad hoc network testing. Our testing process begins with the comparison of 3 realistic trace mobility models from the Generic Mobility Simulation Framework (GMSF) project. We created a simulator to test the data from the three scenarios: the urban, rural, and city models provided with the GMSF simulation, which obtains privacy metric data for each time step as the vehicles move across our simulation. We take the metric data from tests of each of these scenarios and compare it to note any trends as mobility models change.
Advisor: Dr. Fu
Vehicular Ad Hoc Networks (VANETs) are the pinnacle of 21st Century technology. While vehicular communication via this network offers a variety of positive services, it may be susceptible to malicious attacks and threats. Due to the complexity of this system, it is a high target for cyber terrorism and hacking. To better understand these attacks, we will present threats posed to VANETs. These threats will include vehicle tracking, manipulation of GPS coordinates, impersonation of law enforcement safety devices, and petty crime such as robbery or theft. In addition, we will discuss research and statistics pertaining to General Motors OnStar and the Federal Bureau of Investigation’s (FBI) Stingray Phone Interceptor. These two systems have helped with the development of possible VANET threats because both systems have been manipulated by various personnel resulting in the intrusion of privacy. By exploring OnStar and the Stingray, a more clear roadmap of the possibilities of attacks will be presented. We will conclude by summarizing possible defense methods that OnStar and the Stingray provide for VANETs.
Advisor: Dr. Fu
We propose a self-organizing trust model that uses a message based approach to formulate opinions about an event. Our model uses role, experienced based trust, split message trust, and the reliability of previous messages. Our model uses a threshold value and a confidence value to evaluate messages. Furthermore, our model takes into account the ever changing nature of roads by not relying on RSUs, which a fair amount of other models assume are always present. Our model evaluates what percentages of malicious nodes have an impact on messages, or go undetected. We also evaluate the performance of our model based ontime efficiency (the time it takes to perform a trust opinion and aggregation); and route avoidance (the ability of a node to avoid a particular route based on trust messages). Additionally we propose a solution to the storage and recollection of experience based trust in a decentralized environment that uses rapidly expiring keys. For added confidence in message transmission a threshold value for consideration ensures that only reliable nodes will contribute into the synthesis of a message.