Defense Notices

Software Defined Networking (SDN) decouples the control or logical plane of a network from its physical/data plane thus enabling features such as centralized control, network programmability, virtualization, network application development, automation and more. However, SDN is still vulnerable to attacks and failures just like any other non-SDN network. The failure in SDN can be either a link or device failure. Controller is the central device, acting like the brain of a network, and its failure can propagate rapidly rendering the underlying data plane dysfunctional. The concept of Multi-Controller SDN uses redundancy as an effective method to ensure resilience and fault-tolerance in a Software-Defined Network. Multiple Controllers are connected in a cluster to form a physically distributed but logically centralized network. The backup controllers ensure resilience against failure, attack, disaster and other network disruptions. In this project, we implement multi-controller SDN and measure performance metrics such as high availability, reliability, latency, datastore persistency and failure recovery time in a clustered environment.

Three-dimensional (3D) integrated circuits (ICs) offer a promising near-term solution for pushing beyond Moore’s Law because of their compatibility with current technology. Through silicon vias (TSVs) provide electrical connections that pass vertically through wafers or dies to generate high-performance interconnects, which allows for higher design densities through shortened connection lengths. In recent years, we have seen tremendous technological and economic progress in adoption of 3D ICs with TSVs for mainstream commercial use. 
Along with the need for low-cost and high-yield process technology, the successful application of TSV technology requires further optimization of the TSV electrical modeling and design. In the millimeter wave (mmW) frequency range, the root mean square (rms) height of the through silicon via (TSV) sidewall roughness is comparable to the skin depth and hence becomes a critical factor for TSV modeling and analysis. The impact of TSV sidewall roughness on electrical performance, such as the loss and impedance alteration in the mmW frequency range, is examined and analyzed. The second order small analytical perturbation method is applied to obtain a simple closed-form expression for the power absorption enhancement factor of the TSV. In this study, we propose an accurate and efficient electrical model for TSVs which considers the TSV sidewall roughness effect, the skin effect, and the metal oxide semiconductor (MOS) effect. The accuracy of the model is validated through a comparison of circuit model behavior for full wave electromagnetic field simulations up to 100 GHz. 
Another advanced neurophysiological computing system that can incorporate 3D integration could provide massive parallelism with fast and energy efficient links. While the 3D neuro-inspired system offers a fantastic level of integration, it becomes inordinately arduous for the designer to model, merely because of the innumerable interconnected elements. When a TSV array is utilized in a 3D neuromorphic system, crosstalk has a malefic effect upon the system’s signal to noise ratio; the result is an overall deterioration of system performance. To countervail the crosstalk, we propose a novel optimized TSV array pattern by applying the force directed optimization algorithm. 

As our world becomes more connected, the average person must place more trust in cloud systems for everyday transactions. We rely on banks and credit card services to protect our money, hospitals to conceal and selectively disclose sensitive health information, and government agencies to protect our identity and uphold national security interests. However, establishing trust in remote systems is not a trivial task, especially in the diverse, distributed ecosystem of todays networked computers. Remote Attestation is a mechanism for establishing trust in a remotely running system where an appraiser requests information from a target that can be used to evaluate its operational state. The target responds with evidence providing configuration information, run-time measurements, and authenticity meta-evidence used by the appraiser to determine if it trusts the target system. For Remote Attestation to be applied broadly, we must have attestation protocols that perform operations on a collection of applications, each of which must be measured differently. Verifying that these protocols behave as expected and accomplish their diverse attestation goals is a unique challenge. An important first step is to understand the structural properties and execution patterns they share. In this thesis I present a semantic framework for attestation protocol execution within the Coq verification environment including a protocol representation based on Session Types, a dependently typed model of perfect cryptography, and an operational execution semantics. The expressive power of dependent types constrains the structure of protocols and supports precise claims about their behavior. If we view attestation protocols as programming language expressions, we can borrow from standard language semantics techniques to model their execution. The proof framework ensures desirable properties of protocol execution, such as progress and termination, that hold for all protocols. It also ensures properties of authenticity and secrecy for individual protocols.

The Internet of Things (IoT) is expected to revolutionize the world through its myriad applications in health-care, public safety, environmental management, vehicular networks, industrial automation, etc. Some of the concepts related to IoT include Machine Type Communications (MTC), Low power Wireless Personal Area Networks (LoWPAN), wireless sensor networks (WSN) and Radio-Frequency Identification (RFID). Characterized by large amount of traffic with smart decision making with little or no human interaction, these different networks pose a set of challenges, among which security, energy, reliability and latency are the most important ones. First, the open wireless medium and the distributed nature of the system introduce eavesdropping, data fabrication and privacy violation threats. Second, the large number of IoT devices are expected to operate in a self-sustainable and self-sufficient manner without degrading system performance. That means energy efficiency is critical to prolong devices' lifetime. Third, many IoT applications require the information to be successfully transmitted in a reliable and timely manner, such as emergency response and health-care scenarios. To address these challenges, we propose low-complexity approaches by exploiting the physical layer and using stochastic geometry as a powerful tool to accurately model the spatial locations of ''things''. This helps provide a tractable analytical framework to provide solutions for the mentioned challenges of IoT.

Event Studies in finance have focused on traditional news headlines to assess the impact an event has on a traded company. The increased proliferation of news and information produced by social media content has disrupted this trend. Although researchers have begun to identify trading opportunities from social media platforms, such as Twitter, almost all techniques use a general sentiment from large collections of tweets. Though useful, general sentiment does not provide an opportunity to indicate specific events worthy of affecting stock prices.

The surface-elevation of ice sheets and sea ice is currently measured using both satellite and airborne radar altimeters. These measurements are used for generating mass balance estimates of ice sheets and thickness estimates of sea ice. However, due to the penetration of the altimeter signal into the snow there is ambiguity between the surface tracking point and the actual surface location which produces errors in the surface elevation measurement. In order to address how the penetration of the signal affects the shape of the return waveform, it is important to study the effect sub-surface scattering and seasonal variations in properties of snow have on the return waveform to correctly interpret the satellite radar altimeter data. To address this problem, an ultra-wide bandwidth Ku-band radar altimeter was developed at the Center for Remote Sensing of Ice Sheets (CReSIS). The Ku-band altimeter operates over the frequency range of 12 to 18 GHz providing very fine resolution to measure ice surface and resolve the sub-surface features of the snow. It is designed to encompass the frequency band of satellite radar altimeters. The data from Ku-band altimeter can be used to simulate satellite radar altimeter data, and these simulated waveforms can help us understand the effect of signal penetration and sub-surface scattering on low bandwidth satellite altimeter returns. The extensive dataset collected as a part of the Operation Ice Bridge (OIB) campaign can be used to interpret satellite radar altimeter data over surfaces with varying snow conditions. The goal of this research is to use waveform modeling and data inter-comparisons of full and reduced bandwidth data products from Ku-band radar altimeter to investigate the effect of signal penetration and snow conditions on surface tracking using threshold and waveform fitting retracking algorithms to improve the retrieval of surface elevation from satellite radar altimeters.

High rate data transmission is very common in cellular and wireless local area networks. It is achievable because of its wired backbone where only the first or the last hop is wireless, commonly known as wireless “last-mile” link. With this type of infrastructure network, it is not surprising to achieve the desired performance of wirelessly-transmitted video. However, the current challenge is to transmit an enunciated and a high quality real time video over multiple wireless hops in an ad hoc network. The performance of multiple wireless hops to transmit a high quality video is limited by data rate, bandwidth of wireless channel and interference from adjacent channels. These factors constrain the applications for a wireless multihop network but are fundamental to military tactical network solutions. The project addresses and studies the effect of packet sensitivity, latency, bitrate and bandwidth on the quality of video for line of sight and non-line of sight test scenarios. It aims to achieve the best visual user experience at the receiver end on transmission over multiple wireless hops. Further, the project provides an algorithm for placement of drones in sub-terrain environment to stream real time videos for border surveillance to monitor and detect unauthorized activity.

The Treatise on Invertebrate Paleontology (TIP) is a definitive work completed by more than 300 authors in the field of Paleontology, covering all categories of invertebrate animals. The digital version for TIP is consisted of multiple PDF files, however, these files are just a clone of paper version and are not well formatted, which makes it hard to extract structured data using only straightforward methods. In order to make fossil and extant records in TIP organized and searchable from a web interface, a digital library which is called Invertebrate Paleontology Knowledgebase (IPKB) was built for information sharing and querying in TIP. It is consisted of a database which stores records of all fossils and extant invertebrate animals, and a web interface which provides an online access. 
The existing IPKB system provides a general framework for TIP information showing and searching, however, it has very limited search functions, only allowing users querying by pure text. Details of structural properties in the fossil descriptions are not carefully taken into consideration. Moreover, sometimes users cannot provide correct and rich enough query terms. Although authors of TIP are all paleontologists, the expected users of IPKB may not be that professional. 
In order to overcome this limitation and bring more powerful search features into the IPKB system, in this thesis, we present a content-based search function, which allow users to search using textual ontology descriptions and images of fossils. First, this thesis describes the work done by previous research on IPKB system. Except for the original text and image processing approaches, we also present our new efforts on improving these original methods. Second, this thesis presents the algorithm and approach adopted in the construction of content-based search system for IPKB. The search functions in the old IPKB system did not consider the differences among morphological details of certain regions of fossils. Three major parts are discussed in detail: (1) Textual ontology based search. (2) Image based search. (3) Text-image based search. 

Participation in social networking sites has dramatically increased in recent years. Services such as Linkedin, Facebook, or Twitter allow millions of individuals to create online profiles and share personal information with vast networks of friends - and, often, unknown numbers of strangers. The relation between privacy and a person’s social network is multi-faced. At certain occasions we want information about ourselves to be know only to a limited set of people, and not to strangers. Privacy implications associated with online social networking depend on the level of identifiability of the information provided, its possible recipients, and its possible uses. Even social networking websites that do not openly expose their users’ identities may provide enough information to identify profile’s owner. 

With the advent of general-purpose programming tools and newer GPUs, programmers now have access to a more flexible general-purpose approach to using GPUs for something other than graphics. With single instruction stream, multiple data streams (SIMD), the same instruction is executed by multiple processors using different data streams. GPUs are SIMD computers that exploit data-level parallelism by applying the same operations to multiple items of data in parallel. There are many areas where GPUs can be used for general-purpose computing. We have chosen to focus on a project in the astrophysics area of scientific computing called N-body simulation which computes the evolution of a system of bodies that interact with each other. Each body represents an object such as a planet or a star, and each exerts a gravitational force on all the others. It is performed by using a numerical integration method to compute the interactions among the system of bodies, and begins with the initial conditions of the system which are the masses and starting position and velocity of every body. These data are repeatedly used to compute the gravitational force between all bodies of the system to show updates on screen. We investigate alternative implementation approaches to the problem in an attempt to determine the factors that maximize its performance, including speed and accuracy. Specifically, we compare an OpenCL approach to one based on using OpenGL Compute Shaders. We select these two for comparison to generate real-time interactive displays with OpenGL. Ultimately, we anticipate our results will be generalizable to other APIs (e.g., CUDA) as well as to applications other than the N-Body problem. A comparison of various numerical integration and memory optimization techniques is also included in our analysis in an attempt to understand how they work in the SIMD GPGPU environment and how they contribute to our performance metrics. We conclude that, for our particular implementation of the problem, taking advantage of efficiently using local memory considerably increases performance.