General Nathan F. Twining distinguished himself in leading the American Fifteenth Air Force during the last full year of World War II in the European Theatre. Drawing on the leadership qualities he had already shown in combat in the Pacific Theatre, he was the only USAAF leader who commanded three separate air forces during World War II. His command of the Fifteenth Air Force gave him his biggest, longest lasting, and most challenging experience of the war, which would be the foundation for the reputation that eventually would win him appointment to the nation's highest military post as Chairman of the Joint Chiefs of Staff during the Cold War.

Classification and scheduling are key functionalities of a network processor. Network processors are equipped with application specific integrated circuits (ASIC), so that as IP (Internet Protocol) packets arrive, they can be processed directly without using the central processing unit. A new network processor is proposed called the video network processor (VNP) for real time broadcasting of video streams for IP television (IPTV). This thesis explores the challenge in designing a combined classification and scheduling module for a VNP. I propose and design the classifier-scheduler module which will classify and schedule data for VNP. The proposed module discriminates between IP packets and video packets. The video packets are further processed for digital rights management (DRM). IP packets which carry regular traffic will traverse without any modification. Basic architecture of VNP and architecture of classifier-scheduler module based on content addressable memory (CAM) and random access memory (RAM) has been proposed. The module has been designed and simulated in Xilinx 9.1i; is built in ISE simulator with a throughput of 1.79 Mbps and a maximum working frequency of 111.89 MHz at a power dissipation of 33.6mW. The code has been translated and mapped for Spartan and Virtex family of devices.

Trusted platform modules (TPMs) are hardware modules that are bound to a computer's motherboard, that are being included in many desktops and laptops. Augmenting computers with these hardware modules adds powerful functionality in distributed settings, allowing us to reason about the security of these systems in new ways. In this dissertation, I study the functionality of TPMs from a theoretical as well as an experimental perspective. On the theoretical front, I leverage various features of TPMs to construct applications like random oracles that are impossible to implement in a standard model of computation. Apart from random oracles, I construct a new cryptographic primitive which is basically a non-interactive form of the standard cryptographic primitive of oblivious transfer. I apply this new primitive to secure mobile agent computations, where interaction between various entities is typically required to ensure security. I prove these constructions are secure using standard cryptographic techniques and assumptions. To test the practicability of these constructions and their applications, I performed an experimental study, both on an actual TPM and a software TPM simulator which has been enhanced to make it reflect timings from a real TPM. This allowed me to benchmark the performance of the applications and test …

I start with a brief introduction to the graphics processing unit (GPU) as well as general-purpose computation on modern graphics hardware (GPGPU). Next, I explore the motivations for GPGPU programming, and the capabilities of modern GPUs (including advantages and disadvantages). Also, I give the background required for further exploring GPU programming, including the terminology used and the resources available. Finally, I include a comprehensive survey of previous and current GPGPU work, and end with a look at the future of GPU programming.

With the amount of email spam received these days it is hard to imagine that spammers act individually. Nowadays, most of the spam emails have been sent from a collection of compromised machines controlled by some spammers. These compromised computers are often called bots, using which the spammers can send massive volume of spam within a short period of time. The motivation of this work is to understand and analyze the behavior of spammers through a large collection of spam mails. My research examined a the data set collected over a 2.5-year period and developed an algorithm which would give the botnet features and then classify them into various groups. Principal component analysis was used to study the association patterns of group of spammers and the individual behavior of a spammer in a given domain. This is based on the features which capture maximum variance of information we have clustered. Presence information is a growing tool towards more efficient communication and providing new services and features within a business setting and much more. The main contribution in my thesis is to propose the willingness estimator that can estimate the callee's willingness without his/her involvement, the model estimates willingness level based …

This research addresses the problem of automatic keyphrase extraction from large documents and back of the book indexing. The potential benefits of automating this process are far reaching, from improving information retrieval in digital libraries, to saving countless man-hours by helping professional indexers creating back of the book indexes. The dissertation introduces a new methodology to evaluate automated systems, which allows for a detailed, comparative analysis of several techniques for keyphrase extraction. We introduce and evaluate both supervised and unsupervised techniques, designed to balance the resource requirements of an automated system and the best achievable performance. Additionally, a number of novel features are proposed, including a statistical informativeness measure based on chi statistics; an encyclopedic feature that taps into the vast knowledge base of Wikipedia to establish the likelihood of a phrase referring to an informative concept; and a linguistic feature based on sophisticated semantic analysis of the text using current theories of discourse comprehension. The resulting keyphrase extraction system is shown to outperform the current state of the art in supervised keyphrase extraction by a large margin. Moreover, a fully automated back of the book indexing system based on the keyphrase extraction system was shown to lead to back …