Embedded systems are found in many safety- and security-critical applications, and bring aspects of the physical world to the digital one and vice versa. However, imperfections in this hardware bridge can break the integrity of sensor inputs into an embedded device, causing it to act upon the wrong data. For instance, malicious electromagnetic transmissions can trick systems into inducing defibrillation shocks and raising the temperature of infant incubators, both with potentially severe health consequences.
Unfortunately, such attacks which alter sensor outputs without changing the property being measured itself have so far only been studied in an ad-hoc manner. In my thesis, I address this shortcoming in two ways. First, I create a taxonomy of these “out-of-band” signal injection attacks and defenses. Second, I propose a framework that quantifies security in their context through a system model, mathematical definitions, and an algorithm that can compare the “security level” of off-the-shelf systems.
In my thesis, I also investigate Field-Programmable Gate Arrays (FPGAs), which are available on public cloud infrastructures, and are also integrated in many consumer end-products, such as smartphones and laptops. As FPGAs are often used in sensitive applications, including genome processing, cryptography, and financial modeling, it is necessary to ensure that they can maintain the secrecy of the data that they process.
However, the confidentiality of FPGA data can be broken, as I demonstrate through three new sources of information leakage due to hardware imperfections. The first source exists between “long wires” within seven families of Xilinx FPGAs. I explain how to exploit long-wire leakage for covert- and side-channel attacks, both locally, and on two commercial FPGA clouds through novel ring oscillators structures that bypass currently-deployed countermeasures.
The second source of leakage operates even when different FPGA users are isolated to distinct dies of the same chip. These unintended interactions demonstrate that current FPGA architectures are not well-suited for multi-tenancy, despite the physical isolation of user logic. Finally, I show that assigning dedicated FPGAs to different users is still not enough to prevent cross-FPGA communication: shared Power Supply Units (PSUs) leak information between physically distinct FPGA, CPU, and GPU boards, which can be detected via means of a novel receiver design and classification metric.
Overall, in my thesis, I highlight that the underlying electrical properties of embedded devices often fall short of protecting the integrity and the confidentiality of the data that they process, and allow remote attackers to spoof sensor measurements or infer cryptographic keys and other types of data.</p
