Computer Engineering Commons^™

Concolic Execution Of Nmap Scripts For Honeyfarm Generation, Zhe Li, Bo Chen, Wu-Chang Feng, Fei Xie

Computer Science Faculty Publications and Presentations

Attackers rely upon a vast array of tools for automating attacksagainst vulnerable servers and services. It is often the case thatwhen vulnerabilities are disclosed, scripts for detecting and exploit-ing them in tools such asNmapandMetasploitare released soonafter, leading to the immediate identification and compromise ofvulnerable systems. Honeypots, honeynets, tarpits, and other decep-tive techniques can be used to slow attackers down, however, such approaches have difficulty keeping up with the sheer number of vulnerabilities being discovered and attacking scripts that are being released. To address this issue, this paper describes an approach for applying concolic execution on attacking scripts in Nmap in …

An Automated Ar-Based Annotation Tool For Indoor Navigation For Visually Impaired People, Pei Du, Nirupama Bulusu

Computer Science Faculty Publications and Presentations

Low vision people face many daily encumbrances. Traditional visual enhancements do not suffice to navigate indoor environments, or recognize objects efficiently. In this paper, we explore how Augmented Reality (AR) can be leveraged to design mobile applications to improve visual experience and unburden low vision persons. Specifically, we propose a novel automated AR-based annotation tool for detecting and labeling salient objects for assisted indoor navigation applications like NearbyExplorer. NearbyExplorer, which issues audio descriptions of nearby objects to the users, relies on a database populated by large teams of volunteers and map-a-thons to manually annotate salient objects in the environment like …

Modeling The Effect Of The Covid-19 Pandemic On Azithromycin Prescription In General Practices Across The Uk, Oluwasegun Isaac Daramola

altREU Projects

In the early months of the COVID-19 pandemic, it was reported that some antibiotics were prescribed as a remedy for viral treatment and prophylaxis based on non-randomized, uncontrolled short clinical trials. A major antibiotic consulted being Azithromycin; a broad-spectrum macrolide selected based on its immunomodulatory effects in chronic inflammatory lung diseases, with a seasonal prescription increase of 21.5% in March 2020 compared to March 2019.

To analyze the effect and possible antimicrobial resistance impact of the pandemic on Azithromycin prescription across general practices in the United Kingdom (UK), this study uses a time series decomposition modeling method to compare a …

Developing A Strategy For Creating Affordable Student Housing Solutions, Juan D. Campolargo

altREU Projects

College is becoming more and more expensive, and students are graduating with more and more debt. In 2021, we have almost 1.6 trillion dollars of student loan debt. While students are in college, they need a place to live, and this project will be about how to develop a strategy for creating affordable student housing solutions.

Housing should not be another cause of concern to students or really anyone.

The way it’s done is that people get more loans to pay for housing, or they work as much as they can when they’re not studying to pay for rent. Affordable …

Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee

REU Final Reports

The inclusion of technology on the trail can lead to better experiences for everyone involved in the hobby. Hikers can play a more prominent role in the maintenance of the trails by being able to provide better reports of obstructions while directly on the trail. This paper goes into the project of revamping the obstruction report system applied at Forest Park in Portland, Oregon. Most of my contributions to the project focus on mobile app development with some research into path planning algorithms related to the continuations of this project.

Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty

REU Final Reports

Forest Park, one of the largest public parks in the United States with over 40 trails to pick from when planning a hiking trip. One of the main problems this park has is that there are too many trails, and a lot of the trails extend over 3 miles. Due to these circumstances’ trails are not checked frequently and hikers are forced to hike trails in the area with no warnings of potential hazards they can encounter. In this paper I researched how Forest Park currently monitors its trails and then set up a goal to solve the problem. We …

Online Grocery Shopping: A Staple Of The Present -- And Maybe The Future?, Henry B. Chao

altREU Projects

This project aims to understand how the COVID-19 pandemic has affected people's food shopping tendencies, specifically focusing on the use of online grocers. It uses data collected by a team of researchers led out of Portland State University. This data consists of roughly 8000 surveys distributed starting in September of 2020. The survey asks respondents to discuss their demographics, household resources, and shopping tendencies.

In particular, this project wants to understand how inclined a respondent is to use online grocers based on their personal experience with COVID-19. To do this, the project uses a Latent Class Model (LCM) to classify …

Multi-Agent Radiation Localization, Teresa Nguyen

REU Final Reports

Advancement of radiation detection technology is an ongoing process, and adjustments are made based on pre-existing conditions of radiation presence--both natural and man made. Tools that are currently used for safely detecting radiation in urban environments exist in several forms: drones, robots, or handheld radiation detection devices. This is a harm reductive way to explore radiation-infected environments while preserving human health as best as possible. In order for these autonomous platforms to successfully detect radiation sources, an algorithm needs to be created that is capable of gathering crucial data on its own with little to no human interference. Machine learning …

Automated Statistical Structural Testing Techniques And Applications, Yang Shi

Dissertations and Theses

Statistical structural testing(SST) is an effective testing technique that produces random test inputs from probability distributions. SST shows superiority in fault-revealing power over random testing and deterministic approaches since it heritages the merits from both of them. SST ensures testing thoroughness by setting up a probability lower-bound criterion for each structural cover element and test inputs that exercise a structural cover element sampled from the probability distribution, ensuring testing randomness. Despite the advantages, SST is not a widely used approach in practice. There are two major limitations. First, to construct probability distributions, a tester must understand the underlying software's structure, …

A Method For Comparative Analysis Of Trusted Execution Environments, Stephano Cetola

Dissertations and Theses

The problem of secure remote computation has become a serious concern of hardware manufacturers and software developers alike. Trusted Execution Environments (TEEs) are a solution to the problem of secure remote computation in applications ranging from "chip and pin" financial transactions to intellectual property protection in modern gaming systems. While extensive literature has been published about many of these technologies, there exists no current model for comparing TEEs. This thesis provides hardware architects and designers with a set of tools for comparing TEEs. I do so by examining several properties of a TEE and comparing their implementations in several technologies. …

Towards Adaptive, Self-Configuring Networked Unmanned Aerial Vehicles, Nirupama Bulusu, Ehsan Aryafar, Feng Liu

Computer Science Faculty Publications and Presentations

Networked drones have the potential to transform various applications domains; yet their adoption particularly in indoor and forest environments has been stymied by the lack of accurate maps and autonomous navigation abilities in the absence of GPS, the lack of highly reliable, energy-efficient wireless communications, and the challenges of visually inferring and understanding an environment with resource-limited individual drones. We advocate a novel vision for the research community in the development of distributed, localized algorithms that enable the networked drones to dynamically coordinate to perform adaptive beam forming to achieve high capacity directional aerial communications, and collaborative machine learning to …

A Golden Age For Computing Frontiers, A Dark Age For Computing Education?, Christof Teuscher

Electrical and Computer Engineering Faculty Publications and Presentations

There is no doubt that the body of knowledge spanned by the computing disciplines has gone through an unprecedented expansion, both in depth and breadth, over the last century. In this position paper, we argue that this expansion has led to a crisis in computing education: quite literally the vast majority of the topics of interest of this conference are not taught at the undergraduate level and most graduate courses will only scratch the surface of a few selected topics. But alas, industry is increasingly expecting students to be familiar with emerging topics, such as neuromorphic, probabilistic, and quantum computing, …

Automated Test Generation For Validating Systemc Designs, Bin Lin

Dissertations and Theses

Modern system design involves integration of all components of a system on a single chip, namely System-on-a-Chip (SoC). The ever-increasing complexity of SoCs and rapidly decreasing time-to-market have pushed the design abstraction to the electronic system level (ESL), in order to increase design productivity. SystemC is a widely used ESL modeling language that plays a central role in modern SoCs design process. ESL SystemC designs usually serve as executable specifications for the subsequent SoCs design flow. Therefore, undetected bugs in ESL SystemC designs may propagate to low-level implementations or even final silicon products. In addition, modern SoCs design often involves …

On The (Im)Practicality Of Adversarial Perturbation For Image Privacy, Arezoo Rajabi, Rakesh B. Bobba, Mike Rosulek, Charles Wright, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Image hosting platforms are a popular way to store and share images with family members and friends. However, such platforms typically have full access to images raising privacy concerns. These concerns are further exacerbated with the advent of Convolutional Neural Networks (CNNs) that can be trained on available images to automatically detect and recognize faces with high accuracy.

Recently, adversarial perturbations have been proposed as a potential defense against automated recognition and classification of images by CNNs. In this paper, we explore the practicality of adversarial perturbation based approaches as a privacy defense against automated face recognition. Specifically, we first …