Defense Notices


All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.

Upcoming Defense Notices

Logan Schmalz

A Framework for Controlled Key Release

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Perry Alexander, Chair
Drew Davidson
Sankha Guria


Abstract

Modern security relies heavily on public key cryptography, and private keys and secrets in general must be protected from attackers. Against a highly-capable adversary it is ideal to store secrets outside of main memory, which is easy on general purpose systems with the now widely-available Trusted Platform Module (TPM) 2.0. However, the lack of integration between the TPM and the OS makes protecting secrets with automated availability needs difficult. We develop a strategy to authenticate OS entities and protect TPM-stored secrets without restricting access to the TPM, using standard features available on Linux---SELinux, Integrity Measurement Architecture (IMA), Extended Verification Module (EVM), and Linux Unified Key Setup (LUKS).


Pranav Sudhakar Raju

Information Theoretic Waveform Design and Receive Processing for Pulse Agile Radar

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

James Stiles, Chair
Shannon Blunt
Patrick McCormick
Charles Mohr
Zsolt Talata

Abstract

Modern radar systems are increasingly required to operate in complex, dynamic environments where traditional waveform design and signal processing techniques reach fundamental limitations. To address this, waveform diversity has been utilized to increase design degrees of freedom and improve detection performance in challenging scattering scenarios. This dissertation leverages an information-theoretic framework to implement waveform design and receive processing techniques in pulse-agile radars.

First, a modification of Fishers Information known as Marginal Fishers Information is adapted specifically for application to pulse-agile radars, where the ensuing waveform sets are optimally designed to minimize the error covariance of the scene estimate, improving target detection. This methodology is applied to range-Doppler estimation, where some knowledge of the scattering scene is known a priori. By incorporating the a priori knowledge of the scene into the waveform design, the waveforms are able to inherently suppress the self-interference introduced by pulse-agility.

Second, the information theoretic framework is used to create pulse-agile receive processing techniques for range-only and range-Doppler estimation. The range-only implementation is an iterative minimum mean square error (MMSE) estimator similar to a Kalman filter, where the innovation-based update suited to pulse-agility, mirrors the Kalman filter’s correction step. The range-Doppler implementation leverages the same principles as the range-Doppler waveform design technique, where some knowledge of the scattering scenario a priori is used to suppress self-interference and improve the range-Doppler estimate in a desired region.

Both the waveform design and advanced receive processing techniques are first developed in the fast-time slow-time parameterization space, and then translated to a frequency-domain implementation to reduce computation complexity and improve tractability. Finally, future work is proposed to round out the content of the dissertation.


Sirisha Thippabhotla

From Fragments to Function: Computational Approaches for Reconstructing Biological Context in Metagenomic and Exosomal Discovery

When & Where:


Eaton Hall, Room 2001B

Committee Members:

Cuncong Zhong, Chair
Prasad Kulkarni
Fengjun Li
Zijun Yao
Liang Xu

Abstract

Advances in high-throughput Next Generation Sequencing (NGS) technologies have transformed our ability to study biological systems. However, a fundamental gap remains between generating data and interpreting it. Sequencing produces genomes, transcriptomes, and cell-derived signals as millions of short, fragmented sequences, resulting in the loss of biological context, specifically the long-range relationships that determine genes, structured RNAs, or regulatory signals. This work investigates computational and experimental approaches to improve functional discovery by reconstructing or preserving biological context. The concept is developed across three interconnected dimensions: sensitivity, scalability, and biological fidelity, demonstrating that context is lost and must be recovered at two distinct stages of the discovery process.

The first contribution handles the loss of context that occurs after sequencing. By representing metagenomic sequencing reads as connected paths in an assembly graph and guiding graph traversal with biological models, this work recovers both protein-coding and non-coding signals that conventional fragment-level analyses fail to detect, thereby revealing functional pathways that would otherwise be missed. The second contribution makes this recovery practical at scale by introducing a significantly faster framework that preserves the sensitivity of graph-based methods while reducing computational costs by over an order of magnitude, thus enabling the analysis of large present-day datasets.

The third contribution studies the loss of context prior to sequencing. Using extracellular vesicles as a model system, the findings show that cells cultured in conventional two-dimensional environments generate signals that differ from their physiological state. In contrast, cells cultured in three-dimensional models produce signals that closely resemble those observed in patients. This shows that an accurate biological model is essential for reliable discovery, since computational methods cannot recover signals that are fundamentally distorted at their origin.

Taken together, these contributions establish a set of methods and principles for extracting meaningful biological information from fragmented, high-throughput genomic data, thereby enabling more accurate functional discovery.


Harlan Williams

State-replicated key directories: Decoupling key distribution from the messaging service to prevent person-in-the-middle attacks

When & Where:


Zoom defense, please email jgrisafe@ku.edu for defense information.

Committee Members:

Hossein Saiedian, Chair
Arvin Agah
Perry Alexander


Abstract

End-to-end encrypted (E2EE) messaging services rely on the service operator to distribute authentic public keys. This arrangement protects users from external attackers, but fails catastrophically when the service itself acts maliciously. A service that distributes a spoofed key can silently decrypt, read, and re-encrypt its users' communications—undetectably, if users simply assume the service is trustworthy.

This thesis proposes and evaluates a state-replicated key directory, a model that decouples key distribution from the messaging service entirely. Instead of a single service controlling the directory, the directory is built and maintained across multiple decentralized nodes that follow a consensus and validation protocol. This design substantially raises the cost of key substitution attacks and, under well-defined assumptions, can prevent them outright.

We make three core contributions. First, we present End2, a fully functional browser-based E2EE messaging application that integrates a state-replicated key directory without modifying the underlying cryptographic session protocol. Second, we implement and compare three distinct key directory backends—centralized, permissionless blockchain (Ethereum), and permissioned blockchain (CometBFT)—and analyze their respective security and performance trade-offs. Third, we provide an empirical evaluation under realistic workloads, including upload and query latency, long-term performance degradation, validator failure resilience, and detection of malicious key insertions.

Our results show that a permissioned, Byzantine fault-tolerant key directory achieves query performance comparable to a centralized directory while providing substantially stronger security guarantees against service-side attacks. State-replicated key directories offer a practical and deployable path toward reducing the excessive trust placed in modern E2EE messaging providers.


Past Defense Notices

Dates

MEENAKSHI MISHRA

Task Relationship Modeling in Multitask Learning with Applications to Computational Toxicity

When & Where:


246 Nichols Hall

Committee Members:

Luke Huan, Chair
Arvin Agah
Swapan Chakrabarti
Ron Hui
Zhou Wang

Abstract

Multitask Learning is a learning framework which explores the concept of sharing training information among multiple related tasks to improve the generalization error of each task. The benefits of multitask learning have been shown both empirically and theoretically. There are a number of fields that benefit from multitask learning, including toxicology. However, the current multitask learning algorithms make a very important key assumption that all the tasks are related to each other in a similar fashion in multitask learning. The users often do not have the knowledge of which tasks are related and train all tasks together. This results in sharing of training information even among the unrelated tasks. Training unrelated tasks together can cause a negative transfer and deteriorate the performance of multitask learning. For example, consider the case of predicting in vivo toxicity of chemicals at various endpoints from the chemical structure. Toxicity at all the endpoints are not related. Since, biological networks are highly complex, it is also not possible to predetermine which endpoints are related. Thus, training all the endpoints together may cause a negative effect on the overall performance. This proposal aims at developing algorithms which make use of task relationship models to further improve the generalization error and prevent transfer of information among the unrelated tasks. The algorithms proposed here either learn the task relationships or utilize the known task relationships in the learning framework. Further, these algorithms will be utilized to predict toxicity of chemicals at various endpoints using the chemical structures and the results of multiple in vitro assays performed on these chemicals.


YINGYING MA

A Comparison of Two Discretization Options of the MLEM2 Algorithm

When & Where:


2001B Eaton Hall

Committee Members:

Jerzy Grzymala-Busse, Chair
Luke Huan
Prasad Kulkarni


Abstract

A rule set is a popular symbolic representation of knowledge derived from 
data. A rule induction is an important technique of data mining or machine 
learning. Many rule induction algorithms are widely used, such as LEM1, LEM2 and MLEM2. Some of these algorithms perform better on special data, e. g., on inconsistent data set or data sets with missing attribute values. This work discusses basic ideas of the MLEM2 algorithm, especially, how it handles data sets with numeric attribute values. Additionally, a comparison of the performance of different discretization options of the MLEM2 algorithm is also included.


FRANK MOLEY

Maintaining Privacy and Security of Personally Identifiable Information Data in a Connected System

When & Where:


280 Best

Committee Members:

Hossein Saiedian, Chair
Fengjun Li
Bo Luo


Abstract

The large data stores of Personally Identifiable Information (PII) in todays connected systems, coupled with the increased potential damages of Identity Theft bring the need for architectures that provide secure collection, storage, and transmission of this data. The need has not yet been standardized in the industry in a way similar to the Payment Card Industry (PCI) has done so. At the same time, however, municipalities, states, and even countries are instituting legislature that requires business entities that store PII data to maintain adequate security of the data. The need has become clear for a set of processes, procedures, and systems that provide a framework for securely storing PII data. This project defines the lower level datastore system and associated services for that PII data. It also outlines a network architecture prototype for providing segmented security zones used to provide more layers of security in a connected system.


KALYANI HARIDASYAM

AskMyNetwork: Finding Reliable Feedback and Reviews

When & Where:


280 Best

Committee Members:

Hossein Saiedian, Chair
Fengjun Li
Bo Luo


Abstract

We all consult online reviews before obtaining a product or service. However, not all the reviews can be trusted. For example, in 2013, "Operation Clean Turf” a yearlong sting operation in New York State, caught 19different companies that were writing fake reviews in online forums like Yelp for businesses that paid them. For my project, I've developed an application called AskMyNetwork. AskMyNetwork interfaces with Facebook to obtain feedback or input from a user's Facebook friends.The rationale for my project is that the feedback or inputs are from "friends" (personal friends, family members,or colleagues in a user's Facebook friends' list) and can be trusted. 

AskMyNetwork has four major components namely, Login,Search My Network, Ask My Network and Notifications. Using the Login component, the user can login to the application with Facebook credentials. Using Search My Network component, the user can define search criteria (e.g.,search for restaurant in Kansas City) and search his or her Facebook data for relevant results. Using Ask My Network component, the user can ask a group of friends question about a product or service they would like an opinion on. The group of friends can either be chosen by name or by the current location of the friends. Using the Notifications component, the user can view the responses given to questions asked from AskMyNetwork. 

I validated AskMyNetwork via a number of inquiries on topics such as restaurants, places to visit in a city and arts. The results of the validation were satisfactory.


MUHARREM ALI TUNC

LPTV-Aware Bit Loading and Channel Estimation in Broadband PLC for Smart Grid

When & Where:


246 Nichols Hall

Committee Members:

Erik Perrins, Chair
Shannon Blunt
Lingjia Liu
James Sterbenz
Atanas Stefanov

Abstract

Power line communication (PLC) has received steady interest over recent decades because of its economic use of existing power lines, and is one of the communication technologies envisaged for Smart Grid infrastructure. However, power lines are not designed for data communication, and this brings unique challenges for data communication over power lines. In particular for broadband (BB) PLC, the channel exhibits linear periodically time varying (LPTV) behavior synchronous to the AC mains cycle due to time varying impedances, impulsive noise due to switching events in the power line network is present in addition to background noise. In this work, we focus on two major aspects of an orthogonal frequency division multiplexing (OFDM) system for BB PLC LPTV channels; bit and power allocation, and channel estimation (CE). 

For the problem of optimal bit and power allocation, we present that the application of a power constraint that is averaged over many microslots can be exploited for further performance improvements through bit loading. Due to the matroid structure of the optimization problem, greedy-type algorithms are proven to be optimal for the new LPTV-aware bit and power loading. Next, two mechanisms are utilized to reduce the complexity of the optimal LPTV-aware bit loading and peak microslot power levels: employing representative values from microslot transfer functions, and power clipping. 

Next, we introduce a robust CE scheme with low overhead that addresses the drawbacks of block-type pilot arrangement and decision directed CE schemes such as large estimation overhead, and difficulty in channel tracking in the case of sudden changes in the channel, respectively. A transform domain (TD) analysis approach is developed to determine the cause of changes in the channel estimates. The result of TD analysis is then exploited in the proposed scheme to mitigate the effects of LPTV channel and impulsive noise. 

Our results indicate that the proposed reduced complexity LPTV-aware bit loading with power clipping algorithm performs close to the optimal scheme, and the proposed CE scheme based on TD analysis has low estimation overhead and is robust to changes in the channel and noise, making them good alternatives for BB PLC LPTV channels.


BRIAN CORDILL

Radar System Enhancement through High Fidelity Electromagnetic Modeling

When & Where:


129 Nichols

Committee Members:

Sarah Seguin, Chair
Shannon Blunt
Chris Allen
Jim Stiles
Mark Ewing

Abstract

Many of the innovative algorithms that permeate the field of array processing are based on a very simple signal model of an array. This simple, although powerful, model is at times a pale reflection of the complexities inherent in the physical world, and this model mismatch opens the door to the performance degradation of any solution for which the model underpins. This dissertation seeks to explore the impact of model mismatch upon common array processing algorithms. Model mismatch is examined in two ways: First, by developing a blind array calibration routine that estimates model mismatch and incorporates that knowledge into the RISR direction of arrival estimation algorithm. Second, by examining model mismatch between a transmitting and receiving antenna array, and assessing the impact of this mismatch on prolific direction of arrival estimation algorithms. In both of these studies it is shown that engineers have traded algorithm performance of model simplicity, and that if we are willing to deal with the added complexity we can recapture that lost performance.


JOSHUA DAVIS

A Covert Channel Using Named Resources

When & Where:


246 Nichols Hall

Committee Members:

Victor Frost, Chair
Fengjun Li
Bo Luo


Abstract

A method of transmitting information clandestinely over a variety of network protocols is designed and discussed. A demonstrative implementation is created that utilizes the ubiquitous Hypertext Transfer Protocol (HTTP) and the world wide web. Key contributions include the use of access ordering to convey information, and the modulation of transaction level timing to emulate user behavior.


NAHAL NIAKAN

Mutual Coupling Reduction Between Closely Spaced U-slot Patch Antennas by Optimizing Array Configuration and Its Applications in MIMO

When & Where:


2001B Eaton Hall

Committee Members:

Sarah Seguin, Chair
Chris Allen
Jim Stiles


Abstract

Multiple-input, multiple-output (MIMO) systems have received considerable attention over the last decade due to their ability to provide high throughputs and mitigate multipath fading effects. There are some limitations to get the most from MIMO, such as mutual coupling between 
antenna elements in an array. Mutual coupling and therefore inter element spacing have important effect on the channel capacity of MIMO communication system, its error rate and ambiguity of MIMO radar system. There are huge numbers of researches that focus on reducing the mutual coupling in antenna arrays and improve MIMO performance. Antenna design affects the performance of Multiple-Input–Multiple-output (MIMO) systems. Two aspects of antenna role in MIMO performance have been investigated in this thesis. Employing suitable antenna can have significant impact on performance of MIMO system. In addition to antenna design another antenna related issue that helps to optimize the system performance is to reduce mutual coupling between antenna elements in an array.Effect of antenna configuration in array on mutual coupling has been studied in this research. Main purpose is to find the array configuration which provides minimum mutual coupling between elements. U-slot patch antenna which because of its features like wide bandwidth ,multi band resonance and ease to achieve different polarizations has attracted lots of researchers has been used in this study.


ZAID HAYYEH

Exploiting Wireless Networks for Covert Communications

When & Where:


246 Nichols Hall

Committee Members:

Victor Frost, Chair
Shannon Blunt
Erik Perrins
David Petr
Jeffrey Lang

Abstract

The desire to hide communications has existed since antiquity. This includes hiding the existence of the transmission and the location of the sender. Wireless networks offer an opportunity for hiding a transmission by placing a signal in the radio frequency (RF) occupied by a target network which also has the added benefit of lowering its probability of detection. 

This research hides a signal within the RF environment of a packet based wireless (infrastructure) network. Specifically, in this research the interfering (covert) signal is placed in the guard band of the target network’s orthogonal frequency division multiplexed (OFDM) signal. We show that the existence of adaptive protocols allow the target network to adjust to the existence of the covert signal. In other words, the wireless network views the covert network as a minor change in the RF environment; this work shows that the covert signal can be indistinguishable from other wireless impairments such as fading. 

The impact of the covert signal on the target system performance is discovered through analysis and simulation; the analysis and simulation begin at the physical layer where the interaction between the target and covert systems occurs. After that, analysis is performed on the impact of the covert link on the target system at data-link layer. Finally, we analyze the performance of the target system at the transmission control protocol (TCP) layer which characterizes the end-to-end performance. The results of this research demonstrate the potential of this new method for hiding the transmission of information. The results of this research could encourage the creation of new protocols to protect these networks from exploitation of this manner.


RAMESH KUMAR DUGAR

Pulsed Doppler Lidar for Velocity Measurement using Coherent Detection

When & Where:


250 Nichols Hall

Committee Members:

Ron Hui, Chair
Glenn Prescott
Jim Stiles


Abstract

Measurement of wind velocity is of essential to enhance the wind energy utilization which is very important considering the fact that it one of most important renewable source of energy and LIDAR (Light Detection and Ranging) has become a very popular technology for such measurements. In this study, a pulsed Doppler Lidar operating at 1.5µm is demonstrated with coherent detection technique for measurement of velocity of spinning disc which is a hard target used in this project. This Lidar uses the principle of Doppler shift to measure the velocity and an Acousto-optic modulator is used for frequency shifting in the transmitter to produce an intermediate frequency. A data acquisition board (DAQ) was used to generate the pulses and also to process the data once it was collected by the receiver using mat lab. A graphical user interface was used to interface the DAQ with the system and changing parameters like PRF, pulse width, record directory etc. could be changed directly from the computer. A thorough study of literature has been done and same has been presented. The architecture of the Lidar, velocity results, future work and an analysis of SNR’s dependence on range and pulse energy under predefined atmospheric conditions will be discussed.