<p dir="ltr">The Internet is a large network of globally interconnected devices p used to facilitate the exchange of information across different parties. As usage of the Internet is expected to grow in the future, the underlying infrastructure must be secure to ensure traffic reaches its intended destination without any disruptions. However, the primary routing protocol used on the Internet, the Border Gateway Protocol (BGP), while scalable and can properly route traffic between large networks, does not inherently have any security mechanisms built within the protocol. This leads to devices that use BGP over the internet to be susceptible to BGP Hijacking attacks, which involve maliciously injected routes into BGP’s Routing Information Base (RIB) to intentionally redirect traffic to another destination. Attempts to solve these issues in the past have been challenging due to the prevalence of devices that use BGP on the existing Internet infrastructure and the lack of backward compatibility for proposed solutions. The goal of this research is to categorize the different types of BGP Hijacking attacks that are possible on a network, identify indicators that an ongoing BGP Hijacking attack based on received routes from the Internet locally without access to machines from other locations or networks, and subsequently leverage these indicators to protect local networks from external BGP Hijacking attacks.</p>

<p dir="ltr">5G/4G voice calls are encrypted for the purpose of confidentiality, secrecy and privacy. Although protected by well-examined security measures we unveil several vulnerabilities previously unreported in the 5G/4G voice calls that unintentionally leak 5G/4G call state information despite encryption protection and device proof of concept attacks in this thesis. Unlike existing attacks, these new attacks are significantly more threatening because they are completely contactless without requiring any malware, access or compromise on the victim's phones, the 5G/4G network and the other call party. Instead, the attacker only needs to deploy a radio sniffer to eavesdrop on 5G/4G communication and infer confidential call information.</p><p dir="ltr">Interestingly, such confidentiality breaches are technically feasible due to recent 5G/4G call enhancement technologies standardized in the 3GPP specifications and adopted by mobile network operators. While effective in enhancing 5G/4G call quality and efficiency, they, unfortunately, expose extra call information, which can be exploited to infer call states and launch side-channel attacks precisely. Another major contributor to this attack is the IVR technology, which uses a computer-operated telephone system to help companies answer customer calls. In this thesis, we focus on snooping Pay-over-the-Phone transactions done over IVR calls and optionally inferring the company involved in the transaction. The attacks exploit technologies designed to enhance the call quality and efficiency and develop several attack modules to (1) detect voice calls over encrypted 5G/4G traffic, (2) infer the use of IVR over limited call information leaked in the air, and (3) spy on sensitive payment transactions in real-time. We have implemented this proof-of-concept attack using an SDR-based sniffer only. We have validated its effectiveness and assessed damages in various experiments with 5G operators in the US. Lastly, we have discussed the lessons learned from the attacks and the future work that can be done to improve the efficiency of the attacks and make them more threatening.</p>

<div>As wearable devices, like smartwatches and fitness monitors, gain popularity and are being touted for clinical purposes, evaluating the resilience and security of wearable operating systems (OSes) and their corresponding ecosystems becomes essential. One of the most dominant OSes for wearable devices is Wear OS, created by Google. Wear OS and Android (its counterpart OS for mobile devices) share similar features, but the unique characteristics and uses of wearable devices posses new challenges. For example, wearable applications are generally more dependent on device sensors, have complex communication patterns (both intra-device and inter-device), and are context-aware. Current research efforts on the Wear OS are more focused on the efficiency and performance of the OS itself, overlooking the resilience or security of the OS or its ecosystem.</div><div> </div><div>This dissertation introduces a systematic analysis to evaluate the Wear OS's resilience and security. The work is divided into two main parts. First, we focus our efforts on developing novel tools to evaluate the robustness of the wearable OS and uncover vulnerabilities and failures in the wearable ecosystem. We provide an assessment and propose techniques to improve the system's overall reliability. Second, we turn our attention to the security and privacy of smart devices. We assess the privacy and security of highly interconnected devices. We demonstrate the feasibility of privacy attacks under these scenarios and propose a defense mechanism to mitigate these attacks.</div><div> </div><div>For the resilience part, we evaluate the overall robustness of the Wear OS ecosystem using a fuzz testing-based tool [DSN2018]. We perform an extensive fault injection study by mutating inter-process communication messages and UI events on a set of popular wearable and mobile applications. The results of our study show similarities in the root cause of failures between Wear OS and Android; however, the distribution of exception differ in both OSes. Further, our study evidence that input validation has improved in the Android ecosystem with respect to prior studies. Then, we study the impact of the state of a wearable device on the overall reliability of the applications running in Wear OS [MobiSys2020]. We use distinguishable characteristics of wearable apps, such as sensor activation and mobile-wearable communication patterns, to derive a state model and use this model to target specific fuzz injection campaigns against a set of popular wearable apps. Our experiments revealed an abundance of improper exception handling on wearable applications and error propagation across mobile and wearable devices. Furthermore, our results unveiled a flawed design of the wearable OS, which caused the device to reboot due to excessive sensor use.</div><div><br></div><div>For the security and privacy part, we assess user awareness toward privacy risks under scenarios with multiple interconnected devices. Our results show that a significant majority of the users have no reservation while granting permission to their devices. Furthermore, users tend to be more conservative while granting permission on their wearables. Based on the results of our study, we demonstrate the practicability of leaking sensitive information inferred from the user by orchestrating an attack using multiple devices. Finally, we introduce a tool based on NLP (Natural Language Processing) techniques that can aid the user in detecting this type of attack.</div>

<p dir="ltr">The world is increasingly dependent on cyber-physical systems (CPSs), e.g., robotic vehicles (RVs) and industrial control systems (ICSs). CPSs operate autonomously by processing data coming from both “cyberspace”—such as user commands—and “physical space”—such as sensors that measure the physical environment in which they operate. However, even after decades of research, CPSs remain susceptible to threats from attackers, primarily due to the increased complexity created by interaction with cyber and physical space (e.g., the cascading effects that changes in one space can impact on the other). In particular, the complexity causes two primary threats that increase the risk of causing physical damage to RVs: (1) logic bugs causing undesired physical behavior from the developers expectations; and (2) physical sensor attacks—such as GPS or acoustic noise spoofing—that disturb an RV’s sensor readings. Dealing with these threats requires addressing the interplay between cyber and physical space. In this dissertation, we systematically analyze the interplay between cyber and physical space, thereby tackling security problems created by such complexity. We present novel algorithms to detect logic bugs (PGFuzz in Chapter 2), help developers fix them (PGPatch in Chapter 3), and test the correctness of the patches attempting to address them (PatchVerif in Chapter 4). Further, we explain algorithms to discover the root causes and formulate countermeasures against physical sensor attacks that target RVs in Chapter 5.</p>

<p dir="ltr">Dynamic analysis of embedded firmware is a necessary capability for many security tasks, e.g., vulnerability detection. Rehosting is a technique that enables dynamic analysis by facilitating the execution of firmware in a host environment decoupled from the actual hardware. Current rehosting techniques focus on high-fidelity execution of the entire firmware. Consequently, these techniques try to execute firmware in an emulated environment, with precise models of hardware (i.e., peripheral) interactions. However, these techniques are hard to scale and have various drawbacks. </p><p dir="ltr">Therefore, a novel take on rehosting is proposed by focusing on the application components and their interactions with the firmware without the need to model hardware dependencies. This is achieved by rehosting the embedded application as a Linux application. In addition to avoiding precise peripheral modeling, such a rehosting technique enables the use of existing dynamic analysis techniques on these embedded applications. The feasibility of this approach is demonstrated first by manually performing the rehosting on real-world embedded applications. The challenges in each of the phases – retargeting to x86-64, peripheral handling, and fuzzing the rehosted applications are elaborated. Furthermore, automated steps for retargeting to the x86-64 and peripheral handling are developed. The peripheral handling achieves 89% accuracy if reserved regions are also considered. The testing of these rehosted applications found 2 previously unknown defects in driver components.</p>

<p dir="ltr">VANET is formed by vehicles, road units, infrastructure components, and various con- nected objects.It aims mainly to ensure public safety and traffic control. New emerging applications include value-added and user-oriented services. While this technological ad- vancement promises ubiquitous deployment of the VANET, security and privacy challenges must be addressed. Thence, vehicle authentication is a vital process to detect malicious users and prevent them from harming legitimate communications. Hover, the authentication pro- cess uses sensitive information to check the vehicle’s identity. Sharing this information will harm vehicle privacy. In this thesis, we aim to deal with this issues:</p><ul><li>How can we ensure vehicle authentication and avoid sensitive and identity information leaks simultaneously?</li><li>When nodes are asked to provide identity proof, how can we ensure that the shared information is only used by an authorized entity?</li><li>Can we define an effective scheme to distinguish between legitimate and malicious network nodes?This dissertation aims to address the preservation of vehicle private information used within the authentication mechanism in VANET communications.The VANET characteristics are thoroughly presented and analyzed. Security require- ments and challenges are identified. Additionally, we review the proposed authentication techniques and the most well-known security attacks while focusing on the privacy preser- vation need and its challenges.To fulfill, the privacy preservation requirements, we proposed a new solution called Active Bundle AUthentication Solution based on SDN for Vehicular Networks (ABAUS). We intro- duce the Software Defined Networks (SDN) as an authentication infrastructure to guarantee the authenticity of each participant. Furthermore, we enhance the preservation of sensitive data by the use of an active data Bundle (ADB) as a self-protecting security mechanism. It ensures data protection throughout the whole data life cycle. ABAUS defines a dedicated registration protocol to verify and validate the different members of the network.</li></ul><p dir="ltr">first solution focused on legitimate vehicle identification and sensitive data pro- tection. A second scheme is designed to recognize and eliminate malicious users called BEhaviour-based REPutation scheme for privacy preservation in VANET using blockchain technology (BEREP). Dedicated public blockchains are used by a central trust authority to register vehicles and store their behavior evaluation and a trust scoring system allows nodes to evaluate the behavior of their communicators and detect malicious infiltrated users.</p><p dir="ltr">By enhancing sensitive data preservation during the authentication process and detect- ing malicious attempts, our proposed work helps to tackle serious challenges in VANET communications.</p>

<p>Dockerizing web servers has gained significant popularity due to its lightweight containerization approach, enabling rapid and efficient deployment of web services. However, the security of web server containers remains a critical concern. This study proposes a novel approach to enhance the security of Docker-based web servers using bpftrace to trace Nginx and Apache containers under attack, identifying abnormal syscalls, connections, shared library calls, and file accesses from normal ones. The gathered metrics are used to generate tailored AppArmor profiles for improved mandatory access control policies and enhanced container security. BPFtrace is a high-level tracing language allowing for real-time analysis of system events. This research introduces an innovative method for generating AppArmor profiles by utilizing BPFtrace to monitor system alerts, creating customized security policies tailored to the specific needs of Docker-based web servers. Once the profiles are generated, the web server container is redeployed with enhanced security measures in place. This approach increases security by providing granular control and adaptability to address potential threats. The evaluation of the proposed method is conducted using CVE’s found in the open source literature affecting nginx and apache web servers that correspond to the classification system that was created. The Apache and Nginx containers was attacked with Metasploit, and benchmark tests including ltrace evaluation in accordance with existing literature were conducted. The results demonstrate the effectiveness of the proposed approach in mitigating security risks and strengthening the overall security posture of Docker-based web servers. This is achieved by limiting memcpy and memset shared library calls identified using bpftrace and applying rlimits in 9 AppArmor to limit their rate to normal levels (as gauged during testing) and deny other harmful file accesses and syscalls. The study’s findings contribute to the growing body of knowledge on container security and offer valuable insights for practitioners aiming to develop more secure web server deployments using Docker. </p>

<p>The progressive integration of microcontrollers into various domains has transformed traditional mechanical systems into modern cyber-physical systems. However, the beginning of this transformation predated the era of hyper-interconnectedness that characterizes our contemporary world. As such, the principles and visions guiding the design choices of this transformation had not accounted for many of today's security challenges. Many designers had envisioned their systems to operate in an air-gapped-like fashion where few security threats loom. However, with the hyper-connectivity of today's world, many CPS find themselves in uncharted territory for which they are unprepared.</p> <p><br></p> <p>An example of this evolution is the Controller Area Network (CAN). CAN emerged during the transformation of many mechanical systems into cyber-physical systems as a pivotal communication standard, reducing vehicle wiring and enabling efficient data exchange. CAN's features, including noise resistance, decentralization, error handling, and fault confinement mechanisms, made it a widely adopted communication medium not only in transportation but also in diverse applications such as factories, elevators, medical equipment, avionic systems, and naval applications.</p> <p><br></p> <p>The increasing connectivity of modern vehicles through CD players, USB sticks, Bluetooth, and WiFi access has exposed CAN systems to unprecedented security challenges and highlighted the need to bolster their security posture. This dissertation addresses the urgent need to enhance the security of modern cyber-physical systems in the face of emerging threats by proposing a proactive vulnerability identification and defense construction approach and applying it to CAN as a lucid case study. By adopting this proactive approach, vulnerabilities can be systematically identified, and robust defense mechanisms can be constructed to safeguard the resilience of CAN systems.</p> <p><br></p> <p>We focus on developing vulnerability scanning techniques and innovative defense system designs tailored for CAN systems. By systematically identifying vulnerabilities before they are discovered and exploited by external actors, we minimize the risks associated with cyber-attacks, ensuring the longevity and reliability of CAN systems. Furthermore, the defense mechanisms proposed in this research overcome the limitations of existing solutions, providing holistic protection against CAN threats while considering its performance requirements and operational conditions.</p> <p><br></p> <p>It is important to emphasize that while this dissertation focuses on CAN, the techniques and rationale used here could be replicated to secure other cyber-physical systems. Specifically, due to CAN's presence in many cyber-physical systems, it shares many performance and security challenges with those systems, which makes most of the techniques and approaches used here easily transferrable to them. By accentuating the importance of proactive security, this research endeavors to establish a foundational approach to cyber-physical systems security and resiliency. It recognizes the evolving nature of cyber-physical systems and the specific security challenges facing each system in today's hyper-connected world and hence focuses on a single case study. </p>

<p dir="ltr">In the contemporary digital era, Advanced Persistent Threat (APT) attacks are evolving, becoming increasingly sophisticated, and now perilously targeting critical cyber-physical systems, notably Industrial Control Systems (ICS). The intersection of digital and physical realms in these systems enables APT attacks on ICSs to potentially inflict physical damage, disrupt critical infrastructure, and jeopardize human safety, thereby posing severe consequences for our interconnected world. Provenance tracing techniques are essential for investigating these attacks, yet existing APT attack forensics approaches grapple with scalability and maintainability issues. These approaches often hinge on system- or application-level logging, incurring high space and run-time overheads and potentially encountering difficulties in accessing source code. Their dependency on heuristics and manual rules necessitates perpetual updates by domain-knowledge experts to counteract newly developed attacks. Additionally, while there have been efforts to verify the safety of Programming Logic Controller (PLC) code as adversaries increasingly target industrial environments, these works either exclusively consider PLC program code without connecting to the underlying physical process or only address time-related physical safety issues neglecting other vital physical features.</p><p dir="ltr">This dissertation introduces two novel frameworks, ATLAS and ARCHPLC, to address the aforementioned challenges, offering a synergistic approach to fortifying cybersecurity in the face of evolving APT and ICS threats. ATLAS, an effective and efficient multi-host attack investigation framework, constructs end-to-end APT attack stories from audit logs by combining causality analysis, Natural Language Processing (NLP), and machine learning. Identifying key attack patterns, ATLAS proficiently analyzes and pinpoints attack events, minimizing alert fatigue for cyber analysts. During evaluations involving ten real-world APT attacks executed in a realistic virtual environment, ATLAS demonstrated an ability to recover attack steps and construct attack stories with an average precision of 91.06%, a recall of 97.29%, and an F1-score of 93.76%, providing a robust framework for understanding and mitigating cyber threats.</p><p dir="ltr">Concurrently, ARCHPLC, an advanced approach for enhancing ICS security, combines static analysis of PLC code and data mining from ICS data traces to derive accurate invariants, providing a comprehensive understanding of ICS behavior. ARCHPLC employs physical causality graph analysis techniques to identify cause-effect relationships among plant components (e.g., sensors and actuators), enabling efficient and quantitative discovery of physical causality invariants. Supporting patching and run-time monitoring modes, ARCHPLC inserts derived invariants into PLC code using program synthesis in patching mode and inserts invariants into a dedicated monitoring program for continuous safety checks in run-time monitoring mode. ARCHPLC adeptly detects and mitigates run-time anomalies, providing exceptional protection against cyber-physical attacks with minimal overhead. In evaluations against 11 cyber-physical attacks on a Fischertechnik manufacturing plant and a chemical plant simulator, ARCHPLC protected the plants without any false positives or negatives, with an average run-time overhead of 14.31% in patching mode and 0.4% in run-time monitoring mode.</p><p dir="ltr">In summary, this dissertation provides invaluable solutions that equip cybersecurity professionals to enhance APT attack investigation, enabling them to identify and comprehend complex attacks with heightened accuracy. Moreover, these solutions significantly bolster the safety and security of ICS infrastructure, effectively protecting critical systems and strengthening defenses against cyber-physical attacks, thereby contributing substantially to the field of cybersecurity.</p>

<p dir="ltr">This thesis focuses on securing different attack surfaces of embedded systems while meeting the stringent requirements imposed by these systems. Due to the specialized architecture of embedded systems, the security measures should be customized to match the unique requirements of each specific domain. To this end, this thesis identified novel security architectures using techniques such as anomaly detection, program analysis, compartmentalization, etc. This thesis synergizes work at the intersection of programming languages, compilers, computer architecture, operating systems, and embedded systems. </p>