The objective of this project is a statistical decision-making framework to optimize the privacy-utility trade-off for routing in wireless networks against a global and informed adversary using the Bayesian maximum-a-posteriori (MAP) estimation strategy. We then formulate linear programs to efficiently compute the optimal privacy-preserving paths under the lossless and loss adversarial models, given a privacy budget.
In the optimal privacy-preserving probabilistic routing for wireless networks project, Privacy-preserving routing protocols in wireless networks frequently utilize additional artificial traffic to hide the source-destination identities of the communicating pair. Usually, the addition of artificial traffic is done heuristically with no guarantees that the transmission cost, latency, etc., are optimized in every network topology.
In this project, we explicitly examine the privacy-utility trade-off problem for wireless networks and develop a novel privacy-preserving routing algorithm called Optimal Privacy Enhancing Routing Algorithm (OPERA). OPERA uses a statistical decision-making framework to optimize the privacy of the routing protocol given a utility (or cost) constraint. We consider global adversaries with both lossless and loss observations that use the Bayesian maximum-a-posteriori (MAP) estimation strategy. We formulate the privacy-utility trade-off problem as a linear program which can be efficiently solved.
Keywords: Location Privacy, Privacy-Utility Trade-Off, Probabilistic Routing, Bayesian Traffic Analysis, Wireless Routing.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
HARDWARE SPECIFICATIONS:
System: Pentium IV 2.4 GHz.
Hard Disk: 40 GB.
Floppy Drive: 1.44 Mb.
Monitor: 15 VGA Colour.
Mouse : Logitech.
Ram: 512 Mb.
SOFTWARE SPECIFICATIONS:
Operating system: Windows XP/7/LINUX.
Implementation: NS2
NS2 Version: NS2.2.34
Front End: OTCL (Object Oriented Tool Command Language)
Tool: Fedora (To simulate in Linux OS)