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Conference proceeding
Data collection and generation for radio frequency signal security
Advances in Security, Networks, and Internet of Things: Proceedings from SAM'20, ICWN'20, ICOMP'20, and ESCS'20, pp.745-758
Transactions on Computational Science and Computational Intelligence (TRACOSCI
World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), 19th (Las Vegas, Nevada, USA, 07/27/2020–07/30/2020)
2021
Abstract
The current proliferation of Unmanned Aerial Systems (UAS) for a wide range of applications ranging from commercial to defense purposes demands the need for their protection. The development of security tools and techniques will need realistic Radio Frequency (RF) datasets for research and testing. This paper presents an on-going research and development effort to produce RF signal datasets that can be used for the development and testing of machine learning (ML) systems. We envision that these systems will ultimately be the precursor of future autonomous and secure UAS to benefit society for many generations.
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Details
- Title
- Data collection and generation for radio frequency signal security
- Publication Details
- Advances in Security, Networks, and Internet of Things: Proceedings from SAM'20, ICWN'20, ICOMP'20, and ESCS'20, pp.745-758
- Resource Type
- Conference proceeding
- Conference
- World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), 19th (Las Vegas, Nevada, USA, 07/27/2020–07/30/2020)
- Publisher
- Springer International Publishing AG; Cham
- Series
- Transactions on Computational Science and Computational Intelligence (TRACOSCI
- Copyright
- © Springer Nature Switzerland AG 2021
- Identifiers
- 99380090308706600
- Academic Unit
- Intelligent Systems and Robotics; Dr. Muhammad Harunur Rashid Department of Electrical and Computer Engineering; Hal Marcus College of Science and Engineering
- Language
- English