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Full-Text Articles in Computer Engineering

Concolic Execution Of Nmap Scripts For Honeyfarm Generation, Zhe Li, Bo Chen, Wu-Chang Feng, Fei Xie Nov 2021

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 …


Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee Aug 2021

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 Aug 2021

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 …


Multi-Agent Radiation Localization, Teresa Nguyen Aug 2021

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 …


On The (Im)Practicality Of Adversarial Perturbation For Image Privacy, Arezoo Rajabi, Rakesh B. Bobba, Mike Rosulek, Charles Wright, Wu-Chi Feng Jan 2021

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 …