Adversarial Data Augmentation for HMM-based Anomaly Detection

In this work, we concentrate on the detection of anomalous behaviors in systems operating in the physical world and for which it is usually not possible to have a complete set of all possible anomalies in advance. We present a data augmentation and retraining approach based on adversarial learning for improving anomaly detection. In particular, we first define a method for gener- ating adversarial examples for anomaly detectors based on Hidden Markov Models (HMMs). Then, we present a data augmentation and retraining technique that uses these adversarial examples to improve anomaly detection performance. Finally, we evaluate our adversarial data augmentation and retraining approach on four datasets showing that it achieves a statistically significant perfor- mance improvement and enhances the robustness to adversarial attacks. Key differences from the state-of-the-art on adversarial data augmentation are the focus on multivariate time series (as opposed to images), the context of one-class classification (in contrast to standard multi-class classification), and the use of HMMs (in contrast to neural networks)

RF Fingerprinting Unmanned Aerial Vehicles

As unmanned aerial vehicles (UAVs) continue to become more readily available, their use in civil, military, and commercial applications is growing significantly. From aerial surveillance to search-and-rescue to package delivery the use cases of UAVs are accelerating. This accelerating popularity gives rise to numerous attack possibilities for example impersonation attacks in drone-based delivery, in a UAV swarm, etc. In order to ensure drone security, in this project we propose an authentication system based on RF fingerprinting. Specifically, we extract and use the device-specific hardware impairments embedded in the transmitted RF signal to separate the identity of each UAV. To achieve this goal, AlexNet with the data augmentation technique was employed

Securing a UAV Using Features from an EEG Signal

This thesis focuses on an approach which entails the extraction of Beta component of the EEG (Electroencephalogram) signal of a user and uses his/her EEG beta data to generate a random AES (Advanced Encryption Standard) encryption key. This Key is used to encrypt the communication between the UAVs (Unmanned aerial vehicles) and the ground control station. UAVs have attracted both commercial and military organizations in recent years. The progress in this field has reached significant popularity, and the research has incorporated different areas from the scientific domain. UAV communication became a significant concern when an attack on a Predator UAV occurred in 2009, which allowed the hijackers to get the live video stream. Since a UAVs major function depend on its onboard auto pilot, it is important to harden the system against vulnerabilities. In this thesis, we propose a biometric system to encrypt the UAV communication by generating a key which is derived from Beta component of the EEG signal of a user. We have developed a safety mechanism that gets activated in case the communication of the UAV from the ground control station gets attacked. This system was validated on a commercial UAV under malicious attack conditions during which we implement a procedure where the UAV return safely to an initially deployed "home" position

Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities

Robotics and Artificial Intelligence (AI) have been inextricably intertwined since their inception. Today, AI-Robotics systems have become an integral part of our daily lives, from robotic vacuum cleaners to semi-autonomous cars. These systems are built upon three fundamental architectural elements: perception, navigation and planning, and control. However, while the integration of AI-Robotics systems has enhanced the quality our lives, it has also presented a serious problem - these systems are vulnerable to security attacks. The physical components, algorithms, and data that make up AI-Robotics systems can be exploited by malicious actors, potentially leading to dire consequences. Motivated by the need to address the security concerns in AI-Robotics systems, this paper presents a comprehensive survey and taxonomy across three dimensions: attack surfaces, ethical and legal concerns, and Human-Robot Interaction (HRI) security. Our goal is to provide users, developers and other stakeholders with a holistic understanding of these areas to enhance the overall AI-Robotics system security. We begin by surveying potential attack surfaces and provide mitigating defensive strategies. We then delve into ethical issues, such as dependency and psychological impact, as well as the legal concerns regarding accountability for these systems. Besides, emerging trends such as HRI are discussed, considering privacy, integrity, safety, trustworthiness, and explainability concerns. Finally, we present our vision for future research directions in this dynamic and promising field

Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

Data-Driven Architecture to Increase Resilience In Multi-Agent Coordinated Missions

The rise in the use of Multi-Agent Systems (MASs) in unpredictable and changing environments has created the need for intelligent algorithms to increase their autonomy, safety and performance in the event of disturbances and threats. MASs are attractive for their flexibility, which also makes them prone to threats that may result from hardware failures (actuators, sensors, onboard computer, power source) and operational abnormal conditions (weather, GPS denied location, cyber-attacks). This dissertation presents research on a bio-inspired approach for resilience augmentation in MASs in the presence of disturbances and threats such as communication link and stealthy zero-dynamics attacks. An adaptive bio-inspired architecture is developed for distributed consensus algorithms to increase fault-tolerance in a network of multiple high-order nonlinear systems under directed fixed topologies. In similarity with the natural organisms’ ability to recognize and remember specific pathogens to generate its immunity, the immunity-based architecture consists of a Distributed Model-Reference Adaptive Control (DMRAC) with an Artificial Immune System (AIS) adaptation law integrated within a consensus protocol. Feedback linearization is used to modify the high-order nonlinear model into four decoupled linear subsystems. A stability proof of the adaptation law is conducted using Lyapunov methods and Jordan decomposition. The DMRAC is proven to be stable in the presence of external time-varying bounded disturbances and the tracking error trajectories are shown to be bounded. The effectiveness of the proposed architecture is examined through numerical simulations. The proposed controller successfully ensures that consensus is achieved among all agents while the adaptive law v simultaneously rejects the disturbances in the agent and its neighbors. The architecture also includes a health management system to detect faulty agents within the global network. Further numerical simulations successfully test and show that the Global Health Monitoring (GHM) does effectively detect faults within the network

Analysis of the Cyber Attacks against ADS-B Perspective of Aviation Experts

Käesolev töö loob põhjaliku ülevaate lennunduses valitsevatest küberjulgeoleku ohtudest. Tsiviillennunduse lennuliiklusteenindus ja õhuseire on üleminekufaasis valmistudes kasutusele võtma uue põlvkonna tehnoloogiaid, mis tulevikus asendavad praeguse radaripõhise lennukite jälgimissüsteemi uue satelliitpõhise süsteemiga. Lennunduse sideteenuste moderniseerimine loob aluse uuetele turvalisusega seotud ohtudele, mille võimalikke negatiivseid tagajärgi ei ole suudetud veel maandada. Magistritöö eesmärk on koostada kvalitatiivne süstemaatiline analüüs võimalikest küberrünnakutest uue satelliitpõhise automaatse sõltuva seire üldsaade (Automatic dependent surveillance-broadcast –ADS-B) vastu. Analüüs ühendab teadmised küberturvalisuse ja lennunduse valdkonnast, mille koos käsitlemine on oluline turvalise tagamise sesiukohalt. Töö fokusseerub ADS-B süsteemis esinevatele kitsaskohtadele, mis küberturvalise seisukohalt võivad kätkeda ohte või häirida tõsiselt lennuliiklusteeniduse tööd. Potentsiaalsed ohud ADS- S süsteemi vastu on kirjeldatud ja liigitatud sõltuvalt ohuastmest. Analüüsi põhiosa moodustab lennundus spetsialistide seas läbiviidud küsitlus, mille põhjal on hinnatud ohu tõsidust, selle mõju lennundussüsteemile ja milliseid toiminguid on vajalik rakendada ohu esinemise korral. Töö analüüs hindab mõned käsitletud ohtudest ebaoluliseks, mis ei kujuta endast märkisväärset probleemi süsteemi operaatoritele. Sellegi poolest esineb teatava keerulisuse astmega ohustsenaariumeid, mille tagajärjel on süsteem tugevalt häiritud või millega võib kaasneda ulatuslik kahju. Läbiviidud küsitluse põhjal on esitatud meetmeid, kuidas maandada võimalikke negatiivseid mõjusid ohuolukorras. Töö tulemused on olulised pööramaks tähelepanu lennunduses esinevatele küberohtudele. Töö on kirjutatud inglise keeles ja sisaldab 58 lehekülge, 5 peatükki, 17 joonist ja 15 tabelit.The present paper has a profound literature review of the relation between cyber security, aviation and the vulnerabilities prone by the increasing use of information systems in avia-tion realm. Civil aviation is in the process of evolution of the air traffic management sys-tem through the introduction of new technologies. Therefore, the modernization of aero-nautical communications are creating network security issues in aviation that have not been mitigated yet. The purpose of this thesis is to make a systematic qualitative analysis of the cyber-attacks against Automatic Dependent Surveillance Broadcast. With this analysis, the paper combines the knowledge of two fields which are meant to deal together with the security issues in aviation. The thesis focuses on the exploitation of the vulnerabilities of ADS-B and presents an analysis taking into account the perspective of cyber security and aviation experts. The threats to ADS-B are depicted, classified and evaluated by aviation experts, making use of interviews in order to determine the possible impact, and the ac-tions that would follow in case a cyber-attack occurs. The results of the interviews show that some attacks do not really represent a real problem for the operators of the system and that other attacks may create enough confusion due to their complexity. The experience is a determinant factor for the operators of ADS-B, because based on that a set of mitiga-tions was proposed by aviation experts that can help to cope in a cyber-attack situation. This analysis can be used as a reference guide to understand the impact of cyber security threats in aviation and the need of the research and aviation communities to broaden the knowledge and to increase the level of expertise in order to face the challenges posed by network security issues. The thesis is in English and contains 58 pages of text, 5 chapters, 17 figures, 15 tables

The role of space in the security and defence policy of Turkey. A change in outlook: Security in space versus security from space

Space and security domains are strongly related with each other. Nowadays, space is an indispensable part of security and defence policy, and it is increasingly becoming a critical infrastructure for strategic Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) systems. However, space is vulnerable itself to the new space threats. This study reviews the current and near future space role in Turkey's security and defence policy and aims to address the threats against space based capabilities. To provide security from space, space based systems shall themselves need to be secure in space to warrant the security. The concept of security from space starts with space security, in other words the security in space. This paper also highlights the emerging technological opportunities for these space threats to be secure in space in order to provide the security from space. According to the relevant taxonomy, a categorized opportunity proposal for more robust and resilient space/satellite projects' architecture is proposed for Turkey

Counter Unmanned Aircraft Systems Technologies and Operations

As the quarter-century mark in the 21st Century nears, new aviation-related equipment has come to the forefront, both to help us and to haunt us. (Coutu, 2020) This is particularly the case with unmanned aerial vehicles (UAVs). These vehicles have grown in popularity and accessible to everyone. Of different shapes and sizes, they are widely available for purchase at relatively low prices. They have moved from the backyard recreation status to important tools for the military, intelligence agencies, and corporate organizations. New practical applications such as military equipment and weaponry are announced on a regular basis – globally. (Coutu, 2020) Every country seems to be announcing steps forward in this bludgeoning field. In our successful 2nd edition of Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets (Nichols, et al., 2019), the authors addressed three factors influencing UAS phenomena. First, unmanned aircraft technology has seen an economic explosion in production, sales, testing, specialized designs, and friendly / hostile usages of deployed UAS / UAVs / Drones. There is a huge global growing market and entrepreneurs know it. Second, hostile use of UAS is on the forefront of DoD defense and offensive planners. They are especially concerned with SWARM behavior. Movies like “Angel has Fallen,” where drones in a SWARM use facial recognition technology to kill USSS agents protecting POTUS, have built the lore of UAS and brought the problem forefront to DHS. Third, UAS technology was exploding. UAS and Counter- UAS developments in navigation, weapons, surveillance, data transfer, fuel cells, stealth, weight distribution, tactics, GPS / GNSS elements, SCADA protections, privacy invasions, terrorist uses, specialized software, and security protocols has exploded. (Nichols, et al., 2019) Our team has followed / tracked joint ventures between military and corporate entities and specialized labs to build UAS countermeasures. As authors, we felt compelled to address at least the edge of some of the new C-UAS developments. It was clear that we would be lucky if we could cover a few of – the more interesting and priority technology updates – all in the UNCLASSIFIED and OPEN sphere. Counter Unmanned Aircraft Systems: Technologies and Operations is the companion textbook to our 2nd edition. The civilian market is interesting and entrepreneurial, but the military and intelligence markets are of concern because the US does NOT lead the pack in C-UAS technologies. China does. China continues to execute its UAS proliferation along the New Silk Road Sea / Land routes (NSRL). It has maintained a 7% growth in military spending each year to support its buildup. (Nichols, et al., 2019) [Chapter 21]. They continue to innovate and have recently improved a solution for UAS flight endurance issues with the development of advanced hydrogen fuel cell. (Nichols, et al., 2019) Reed and Trubetskoy presented a terrifying map of countries in the Middle East with armed drones and their manufacturing origin. Guess who? China. (A.B. Tabriski & Justin, 2018, December) Our C-UAS textbook has as its primary mission to educate and train resources who will enter the UAS / C-UAS field and trust it will act as a call to arms for military and DHS planners.https://newprairiepress.org/ebooks/1031/thumbnail.jp