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Digital Communications and Networking Commons™
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Full-Text Articles in Digital Communications and Networking
Enhancing Cyberspace Monitoring In The United States Aviation Industry: A Multi-Layered Approach For Addressing Emerging Threats, Matthew Janson
Enhancing Cyberspace Monitoring In The United States Aviation Industry: A Multi-Layered Approach For Addressing Emerging Threats, Matthew Janson
Doctoral Dissertations and Master's Theses
This research project examined the cyberspace domain in the United States (U.S.) aviation industry from many different angles. The research involved learning about the U.S. aviation cyberspace environment, the landscape of cyber threats, new technologies like 5G and smart airports, cybersecurity frameworks and best practices, and the use of aviation cyberspace monitoring capabilities. The research looked at how vulnerable the aviation industry is from cyber-attacks, analyzed the possible effects of cyber-attacks on the industry, and suggests ways to improve the industry's cybersecurity posture. The project's main goal was to protect against possible cyber-attacks and make sure that the aviation industry …
Machine Learning And Artificial Intelligence Methods For Cybersecurity Data Within The Aviation Ecosystem, Anna Baron Garcia
Machine Learning And Artificial Intelligence Methods For Cybersecurity Data Within The Aviation Ecosystem, Anna Baron Garcia
Doctoral Dissertations and Master's Theses
Aviation cybersecurity research has proven to be a complex topic due to the intricate nature of the aviation ecosystem. Over the last two decades, research has been centered on isolated modules of the entire aviation systems, and it has lacked the state-of-the-art tools (e.g. ML/AI methods) that other cybersecurity disciplines have leveraged in their fields. Security research in aviation in the last two decades has mainly focused on: (i) reverse engineering avionics and software certification; (ii) communications due to the rising new technologies of Software Defined Radios (SDRs); (iii) networking cybersecurity concerns such as the inter and intra connections of …
Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming
Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming
Publications
The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to the existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ cryptographic signatures to verify the trustworthiness of received information. In prevalent IoT, secret keys for cryptography can potentially be disclosed and disable the verification mechanism. Noncryptographic device verification is needed to ensure trustworthy IoT. In this article, we propose an enhanced deep learning framework …
Guest Editorial Special Issue On Toward Securing Internet Of Connected Vehicles (Iov) From Virtual Vehicle Hijacking, Yue Cao, Houbing Song, Omprakash Kaiwartya, Sinem Coleri Ergen, Jaime Lloret, Naveed Ahmad
Guest Editorial Special Issue On Toward Securing Internet Of Connected Vehicles (Iov) From Virtual Vehicle Hijacking, Yue Cao, Houbing Song, Omprakash Kaiwartya, Sinem Coleri Ergen, Jaime Lloret, Naveed Ahmad
Publications
Today’s vehicles are no longer stand-alone transportation means, due to the advancements on vehicle-tovehicle (V2V) and vehicle-to-infrastructure (V2I) communications enabled to access the Internet via recent technologies in mobile communications, including WiFi, Bluetooth, 4G, and even 5G networks. The Internet of vehicles was aimed toward sustainable developments in transportation by enhancing safety and efficiency. The sensor-enabled intelligent automation of vehicles’ mechanical operations enhances safety in on-road traveling, and cooperative traffic information sharing in vehicular networks improves traveling efficiency.