Spatially Adaptive Positioning for Molecular Geometry Inspired Aerial Networks

Rentrope, Joshua; Akbaş, Mustafa İlhan

doi:10.1145/3132340.3132348

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…Understanding the risk that a malicious UAV poses to the swarm with realistic communication conditions in a military application is essential. For this purpose, we implemented APAWSAN [6], [7] swarming algorithm, which is based on virtual forces. We simulated a cyber-attack in which a peripheral UAV is compromised.…”

Section: Project #1 -Simulated Effects Of Non-ideal Physical and Cybe...mentioning

confidence: 99%

An Undergraduate Research Experience in Unmanned Aircraft Systems (UAS) Cybersecurity – Outcomes and Lessons Learned

Verleger,

Stansbury,

Akbas

et al.

2022 ASEE Annual Conference &Amp; Exposition Proceedings

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This paper is an update of a Work-in-Progress presented at the ASEE 2021 virtual conference [1] and includes new data from after the 2021 paper was accepted for publication. An undergraduate research experience was developed in response to an Office of Naval Research program seeking to develop "innovative solutions that directly maintain, or cultivate a diverse, world-class STEM workforce in order to maintain the U.S. Navy and Marine Corps' technological superiority." During the fall 2020 semester, nine students were recruited to participate in a UAS cybersecurityfocused undergraduate research experience. Three faculty members each identified a small topic area for undergraduate students to pursue. The three areas are:1. Small UAS (sUAS) Vulnerability and Threat Assessment and Mitigation 2. Effects of Cyber Attacks on Communication in UAS Swarms with Distributed Swarm Control 3. Enhancing Security of Cloud-Connected UAS Services Students were placed onto teams based on their prior course experiences and the project requirements. Common resources were provided for all students to train them in conducting research. Teams were then tasked with developing a more comprehensive research plan for their specific project and carrying out that plan throughout the 2020-2021 academic year. A no-cost extension was granted to enable six students who had not graduated to continue into the Fall 2021 semester with the goals of completing their work and publishing the results in an academic outlet. Three students continued into the Spring 2022 semester finishing their publication work.Year 1 of the program was assessed by having students take a pre-, mid-, and post-survey and conducting a brief interview about their experiences. Students took a pre-survey at the start of the project and a mid-project survey shortly before the winter break. They completed the post survey and interview during the final week of the Spring semester in Year 1. Five students who remained with the project in Year 2 also completed a "final year" survey at the end of the Fall term in year 2. The surveys were a combination of project specific skills questions as well as relevant questions from the Undergraduate Research Student Self-Assessment (URSSA), an NSF funded assessment tool to measure student gains in research skills. This paper will describe the broader project, the individual student team projects and the outcomes of those projects, and results from the surveys and interviews. The purpose of this paper is to provide an example approach for future undergraduate research programs looking for practical approaches to implementing undergraduate research programs, particularly those in the cybersecurity area.

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Section: Project #1 -Simulated Effects Of Non-ideal Physical and Cybe...mentioning

confidence: 99%

An Undergraduate Research Experience in Unmanned Aircraft Systems (UAS) Cybersecurity – Outcomes and Lessons Learned

Verleger,

Stansbury,

Akbas

et al.

2022 ASEE Annual Conference &Amp; Exposition Proceedings

View full text Add to dashboard Cite

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Validation of decision-making in artificial intelligence-based autonomous vehicles

Medrano-Berumen

Akbaş

2020

Journal of Information and Telecommunication

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The autonomous vehicle technology is considered as a significant market disruptor for multiple industries. However, to reach this potential and to be accepted by the public, autonomous vehicles must be proven to be reliable and safe. Therefore, validation is essential for improving the public trust for autonomous vehicles and deploying them for everyday transportation activities. There have been a number of significant efforts on validation of autonomous vehicles; and real-life testing and test tracks have been the major platforms for these activities. However, simulation has also been gaining popularity due to its advantages in cost, time and safety. In this paper, we present a simulation scenario generation methodology with pseudo-random test generation to validate the decision-making system of autonomous vehicles. The methodology separates the validation concerns and focuses on generating scenarios that test the decisions taken by the vehicle. The implementation demonstrates the capabilities and the efficiency of the approach.

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Proactive Eavesdropping via Jamming for Trajectory Tracking of UAVs

Li¹,

Kanhere

et al. 2019

2019 15th International Wireless Communications &Amp; Mobile Computing Conference (IWCMC)

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Spatially Adaptive Positioning for Molecular Geometry Inspired Aerial Networks

Cited by 3 publications

References 17 publications

An Undergraduate Research Experience in Unmanned Aircraft Systems (UAS) Cybersecurity – Outcomes and Lessons Learned

An Undergraduate Research Experience in Unmanned Aircraft Systems (UAS) Cybersecurity – Outcomes and Lessons Learned

Validation of decision-making in artificial intelligence-based autonomous vehicles

Proactive Eavesdropping via Jamming for Trajectory Tracking of UAVs

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