Automatic Dependent Surveillance-Broadcast (ADS-B) is a cornerstone of the next-generation digital sky and is now mandated in several countries. However, there have been many reports of serious security vulnerabilities in the ADS-B architecture. In this paper, we demonstrate and evaluate the impact of multiple cyberattacks on ADS-B via remote radio frequency links that affected various network, processing, and display subsystems used within the ADS-B ecosystem.Overall we implemented and tested 12 cyberattacks on ADS-B in a controlled environment, out of which 5 attacks were presented or implemented for the first time. For all these attacks, we developed a unique testbed that consisted of 13 hardware devices and 22 software that ran on Android, iOS, Linux, and Windows operating systems, which result in a total of 36 tested configurations. Each of the attacks was successful on various subsets of the tested configurations. In some attacks, we discovered wide qualitative variations and discrepancies in how particular configurations react to and treat ADS-B inputs that contain errors or contradicting flight information, with the main culprit almost always being the software implementation. In some other attacks, we managed to cause Denial of Service (DoS) by remotely crashing/impacting more than 50% of the test-set that corresponded to those attacks.Besides demonstrating successful attacks, we also implemented, investigated, and report herein some practical countermeasures to these attacks. We demonstrated that the strong relationship between the received signal strength and the distance-toemitter might help verify the aircraft's advertised ADS-B position and distance. For example, our best machine learning models achieved 90% accuracy in detecting spoofed ADS-B signals, which may be effectively used to distinguish ADS-B signals of real aircraft from spoofed signals of attackers.

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In this master's thesis on cyber security accessible methodology for over-the-air experiments using ACARS, ADS-B, and AIS telecommunication protocols is proposed, using software-defined radios, and utilising open-source and freeware software. The protocols are used as attack vectors for exploitation of Apache Log4j2 Java-library's vulnerabilities. Methods for studying CVE-2021-44228 "log4shell" remote code execution and related vulnerabilities using intentionally vulnerable software are presented. The telecommunication protocols' capabilities in transmitting CVE-2021-44228 and related cyberattack strings are evaluated by studying protocol specifications to identify probable attack vectors. Practical scenarios, in which mission critical and safety-of-life information systems could be exploitable, are experimentally demonstrated. All three studied protocols are found to be susceptible for wireless log4shell-cyberattacks, when identified preconditions are met. Moreover, novel findings concerning a high-severity Log4j2 denial of service vulnerability are presented.

To increase situational awareness of maritime vessels and other entities and to enable their exchange of various information, the International Maritime Organization mandated the use of the Automatic Identification System (AIS) in 2004. The AIS is a self-reporting system that uses the VHF radio link. However, any radio-based self-reporting system is prone to forgery, especially in situations where authentication of the message is not designed into the architecture. As AIS was designed in the 1990s when cyberattacks were in their infancy, it does not implement authentication or encryption; thus, it can be seen as fundamentally vulnerable against modern-day cyberattacks. This paper demonstrates and evaluates the impact of multiple cyberattacks on AIS via remote radio frequency (RF) links. Overall, we implemented and tested a total of 11 different tests/attacks on 18 AIS setups, using a controlled environment. The tested configurations were derived from heterogeneous platforms such as Windows, Android, generic receivers, and commercial transponders. The results showed that approximately 89% of the setups were affected by Denial-of-Service (DoS) attacks at the AIS protocol level. Besides implementing some existing attack ideas (e.g., spoofing, DoS, and flooding), we showed some novel attack concepts in the AIS context such as a coordinated attack, overwhelming alerts, and logical vulnerabilities, all of which have the potential to cause software/system crashes in the worst-case scenarios. Moreover, an implementation/specification flaw related to the AIS preamble was identified during the experiments, which may affect the interoperability of different AIS devices. The error-handling system in AIS was also investigated. Unlike the aviation sector's Automatic Dependent Surveillance-Broadcast (ADS-B), the maritime sector's AIS does not effectively support any error correction method, which may contribute to RF pollution and less effective use of the overall system. The consistency of our results for a comprehensive range of hardware-software configurations indicated the reliability of our approach, test system, and evaluation results.

Image annotation and large annotated datasets are crucial parts within the Computer Vision and Artificial Intelligence fields.At the same time, it is well-known and acknowledged by the research community that the image annotation process is challenging, time-consuming and hard to scale. Therefore, the researchers and practitioners are always seeking ways to perform the annotations easier, faster, and at higher quality. Even though several widely used tools exist and the tools' landscape evolved considerably, most of the tools still require intricate technical setups and high levels of technical savviness from its operators and crowdsource contributors.In order to address such challenges, we develop and present BRIMA -a flexible and open-source browser extension that allows BRowser-only IMage Annotation at considerably lower overheads. Once added to the browser, it instantly allows the user to annotate images easily and efficiently directly from the browser without any installation or setup on the client-side. It also features cross-browser and cross-platform functionality thus presenting itself as a neat tool for researchers within the Computer Vision, Artificial Intelligence, and privacy-related fields.

Automatic dependent surveillance-broadcast (ADS-B) is a key air surveillance technology and a critical component of next-generation air transportation systems. It significantly simplifies aircraft surveillance technology and improves airborne traffic situational awareness. Many types of mobile cockpit information systems (MCISs) are based on ADS-B technology. MCIS gives pilots the flight and trafficrelated information they need. MCIS has two parts: an ADS-B transceiver and an electronic flight bag (EFB) application. The ADS-B transceivers transmit and receive the ADS-B radio signals while the EFB applications hosted on mobile phones display the data. Because they are cheap, lightweight, and easy to install, MCISs became very popular. However, due to the lack of basic security measures, ADS-B technology is vulnerable to cyberattacks, which makes the MCIS inherently exposed to attacks. Attacks are even more likely for the MCIS, because they are power, memory, and computationally constrained. This study explores the cybersecurity posture of various MCIS setups for both types of ADS-B technology: 1090ES and UAT978. Total six portable MCIS devices and 21 EFB applications were tested against radio-link-based attacks by transmission-capable software-defined radio (SDR). Packet-level denial of service (DoS) attacks affected approximately 63% and 37% of 1090ES and UAT978 setups, respectively, while many of them experienced a system crash. Our experiments show that DoS attacks on the reception could meaningfully reduce transmission capacity. Our coordinated attack and fuzz tests also reported worrying issues on the MCIS. The consistency of our results on a very broad range of hardware and software configurations indicate the reliability of our proposed methodology as well as the effectiveness and efficiency of our platform.

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