Tag: Computer Science

Burn Notice: Using Changepoint Detection Algorithms to Improve Wildfire Tracking

Presenter: Sabrina Reis – Mathematics and Computer Science

Faculty Mentor(s): Weng-Keen Wong

Session: (In-Person) Oral Panel—Fuel, Fire, Grass and Compost

The ability to detect anomalous data is a critical component of any useful statistical analysis, but the process for identifying anomalies can prove time-consuming and arduous. To address these challenges, researchers often delegate data processing to an algorithm, which analyzes data with more speed, efficiency, and accuracy than manual calculations, enabling earlier detection of anomalies. The property of early detection is especially critical when monitoring spatio-temporal events such as wildfires. The critical impact of these events necessitate data sources that provide current and complete information. This need is often met by networks of sensors–for instance, air quality sensors–that collect real-time, localized data. When processed with an anomaly detection algorithm, the comprehensive data collected by sensor networks can reveal aberrations indicative of a spatio- temporal event. To explore how anomaly detection algorithms can facilitate early detection of events of interest using sensor data, we gathered historical data from open-source Purple Air sensors to build case studies of past wildfires. We then applied various types of changepoint detection algorithms to the data in hopes of identifying changes in the distribution of data that indicated a wildfire had broken out. The toolkit of detection methods produced by the project offer a cost-effective and portable way of enhancing our ability to monitor the formation and spread of wildfires.

Creating an Educational Graphic Novel about Psychedelics

Presenter: Audra McNamee – Mathematics and Computer Science

Faculty Mentor(s): Luca Mazzucato

Session: (In-Person) Poster Presentation

Scientific communication through the use of comics is an emerging trend across scientific disciplines. Comics are a promising medium for outreach because they appeal to non-scientifically trained audiences, hold the reader’s attention, and the storytelling approach lends itself to explaining complex scientific information. Psychedelics are a promising subject for a scientific comic: psychedelics have recently been designated by the FDA as breakthrough treatment for PTSD, depression, and addiction. While the press on psychedelics is unceasing, most publications about psychedelics are focused on venture capital, psychedelic retreats, and clinical trials. Missing is an explanation of the neuroscience of psychedelics, and reflection on how the history of psychedelics intersect with racial justice and cultural appropriation of indigenous traditions and practices. We are creating a comic addressing these gaps in the science and history of psychedelics by explaining scientific material accurately and accessibly.

The comic is structured around the conversation between two friends, one of whom is very pro-psychedelics, the other being staunchly anti-psychedelics. Having the comic take the form of a dialogue will offer space for argument and nuance: putting psychedelics into historical context, explaining and disproving common myths about psychedelics, explaining how social justice and psychedelics interact, and providing an introductory understanding of the science of psychedelics.

Welcome to Computer Science: Designing a Comic Tour of Computers and Computing

Presenter: Audra McNamee – Mathematics and Computer Science

Faculty Mentor(s): Kathleen Freeman

Session: (In-Person) Oral Panel—Comics, Classics and Analysis

While the number of high-quality educational comics is growing, there are no modern long-form comics discussing computer science at an undergraduate level. The computer science comics that do exist, along with being for a younger audience, are generally focused on teaching the reader programming concepts without exploring other aspects of computer science. For this thesis I scripted and drew the 54-page comic Welcome to Computer Science, which introduces the reader to computer science concepts including computer architecture, programming languages, and the internet. As a narrative comic written for an undergraduate audience, it can draw in readers who otherwise might not choose to engage with the material. As a breadth-first introduction, the comic provides the reader with a foundational understanding of computers and computer science; this work may provide even more experienced students with a better understanding of how their computer science classes relate to the rest of the field.

Simulating Dead-End State Distributions for Microbial Metabolism

Presenter: Nathan Malamud − Mathematics and Computer Science

Faculty Mentor(s): Stilianos Louca

Session: (In-Person) Poster Presentation

In this project, I simulate the influence of microbial metabolism on ocean geochemistry using the Cariaco Basin, Venezuela as a model system. In my investigation, I used bifurcation diagrams to visualize the distribution of possible dead-end states: geochemical configurations at which all metabolic reactions become energetically unfavorable and microbial metabolism slows to a halt. In a radically novel approach, I used an Ornstein-Uhlenbeck process to stochastically model kinetic rates.

My rationale for doing this was to show how stoichiometry and energetics alone could potentially determine long-term biogeochemical states. By running N=9,336 simulations written in Python, I found that the dead-end state of an isolated system with aerobic sulfide-oxidizing microbes could be determined fairly consistently based on varying oxygen levels. At high oxygen concentrations (>100 micromolars), oxygen was utilized to the fullest metabolic extent (until the Gibbs free energy yield reached 0 kJ / mol) by the simulated microbes in order to convert all available sulfide to sulfate.

At lower oxygen levels, nitrate was utilized instead due to its biochemical role as an alternative electron acceptor. At higher oxygen levels, final nitrate concentrations were far less predictable, and significant variation in nitrate consumption can be seen in the associated bifurcation plot. This theoretical exercise may aid in the development of biogeochemical models of climate-influenced ocean processes.

Ducks Quacking – UO Network Characterization with NetFlows

Presenter : Ricky Kerndt

Major : Computer Science

Poster 35

“Intra/Inter-network traffic has become an important part of our daily lives. Its become a primary means of communication through email, messaging, and social networks (e.g. Facebook, Twitter). The University of Oregon represents a small community environment encompassing student housing and the daily activity of classes, staff and professors carrying out research, administration and services to keep the campus functioning. The University’s network backbone thus provides a potential data source for studying how society uses internet applications in their daily activities. This project evaluates the potential of using anonymized netflows obtained from the UO Network and Telecom Services (NTS) to characterize network activity. Netflow records are provided with local addresses anonymized from UO border routers to preserve confidentiality. The records are aggreagated and stored in a database for later characterization of network activity. The characterization includes packet rate!

s, bandwith utilization, applications (unique ports), and distribution of destination IP address. We can then look at how this charac- terization differs with different areas of campus (dorms, offices, wifi) and temporal patterns. The results show that netflow records will provide a valuable data source for studying how a community setting uses internet applications in carrying out their daily activities.

Analyzing the Deployment of Secure Routing Protocols at Internet Scale

Presenter: Braden Hollembaek

Mentor: Kevin Butler

Poster: 18

Major: Computer Science 

With large-scale attacks occurring at alarming frequency, the current state of Internet routing security has proven to be inadequate. Various security modifications to the current protocols have been proposed to help mitigate this problem, but none have seen widespread support or adoption due, in part, to the lack of investigative research on the high demands of bandwidth and cryptographic processing power required by these protocols. The purpose of this study is to provide the critical and independent analysis necessary to determine the feasibility and effect of deploying secure routing protocols across the highest levels of the Internet. By creating software capable of simulating all of the world’s routing traffic, we are able to analyze the additional bandwidth consumed by multiple secure protocols as well as increased load placed on the CPUs. As the research progresses, we will be comparing various secure protocol specifications to determine which security features are the best candidates for adoption and which are not well-suited for use at Internet scale. Based on their efficiency for real-world deployment while not compromising their security, we will be able to make strong recommendations on which protocol suite will be the most practical for implementation going forward.

Verifying the Implementation of Secure Multi-Party Computation Systems

Presenter: Jonathan Eskeldson

Mentor: Kevin Butler

Poster: 14

Major: Computer Science/Mathematics 

As technology has advanced, applications have arisen which rely on sensitive data. In the past, users had to trust these application’s creators with private data. However, breaches of private data and abuses of power, such as
the Snowden NSA revelations, have eroded users’ trust. A recent development in cryptography, called multi-party computation (MPC), allows multiple parties to compute a function over sensitive inputs, in such a way that the
inputs themselves are not revealed, bypassing the issue of trust. This is usually done by performing Yao’s Garbled Circuit protocol. This was mostly theoretical work until a few years ago, when systems capable of performing these operations were created. While there is confidence in the theory driving such systems, little attention has been paid to their implementations, which are prone to error due to their large size and complexity. These errors could create discrepancies between what a system claims to do and what that system actually does, which could weaken its security. The purpose of this study is to rigorously evaluate the security of leading MPC implementations, and expose bugs that weaken the system’s security. This research will help inspire confidence in the implementation of these systems, making them suitable for use in areas where security is a high priority, including electronic elections and private auctions.

Investigation of the Effectiveness of Offensive Computer Security Techniques through Group Self-Study

Presenter: Adam Pond

Mentors: Jun Li and Kathleen Freeman, Computer Science

Poster: 52

Major: Computer Science 

Computer security, otherwise known as cyber security, is a broad and dynamic subfield of computer science. It
is concerned with protecting computing systems, embedded devices, networks, and data from unintended or unauthorized access. While computer security was not one of the fundamental ideas at the beginning of computing, it’s now one of the most interesting fields of computer science, especially the arms race between computer security defense personnel and hackers. One of the most important ways we can learn to defend against adversaries such
as hackers is by learning how to think like them. An effective way of thinking like your adversary is by performing penetration tests against the computing system you’re trying to protect. These penetration tests require a unique skill set that is best acquired through trials and tribulations (commonly called capture the flag events). During a capture- the-flag event, you simulate an adversary trying to gain access, or change data on a computing system that you should not be able to. Since this type of studying was not an option through standard academic courses, I set out to create a group environment in which to study and apply offensive security techniques. I will present the curriculum that I created and used during our weekly meetings of UO Security Club and the results and suggested changes from this experience.

Machine Learning of Motifs and Motif Patterns in Probabilistic Jazz Grammars

Presenter(s): Joseph Yaconelli − Math And Computer Science

Faculty Mentor(s): Robert Keller

Oral Session 3C

Research Area: Computer Science

Funding: National Science Foundation (NSF) Research Experience for Undergraduates (REU)

Building on previous work by Keller et al. in computer generated jazz solos using probabilistic grammars, this paper describes research extending the capabilities of the current learning process and grammar representation used in the Impro-Visor software with the concepts of motifs and motif patterns. An approach has been developed using clustering, best match search techniques, and probabilistic grammar rules to identify motifs and incorporate them into computer generated solos. The abilities of this technique are further expanded through the use of motif patterns. Motif patterns enable the learning of multiple lengths of motifs at once and induce coherence in generated solos by learning the patterns in which motifs
were used in a given set of solos. This approach is implemented as a feature of the Impro-Visor educational music software. Research has been done in other forms of pattern recognition and motif detection. However, this application of musical motif learning is a special case that requires vastly different techniques to accomplish due to music’s temporal nature, the variability of motifs both in length and melody, and the relatively short lifetime of motifs.

New Capabilities for Self-Driving Networks

Presenter(s): Nolan Rudolph—Computer Science

Faculty Mentor(s): Ramakrishnan Durairajan

Session: Prerecorded Poster Presentation

Granted the annual trends in increasing internet usage, the University of Oregon Networking Research Group preemptively researches the concept of Self-Driving Networks (S-DNs) to create a self-remediating, high-performance network . In efforts of accomplishing this project, the lack of S-DN compatible software compels new research to be conducted on new capabilities for a self-driving network . In this project, we accomplish a light-weight visualization framework for flow level data accompanied by a scalable flow to packet generator usable by S-DNs .