Embedded systems are evolving in complexity, leading to the emergence of multiple threats. The co-design and execution of software on the embedded systems further exacerbate the attack surface, making them more vulnerable to sophisticated attacks. As embedded systems are used in critical areas, ensuring their security is crucial. In this special session paper, primarily four major topics regarding embedded systems’ security are discussed. Firstly, this paper initially explores timing channel analysis at a microarchitectural level in heterogeneous hardware to address the security challenges. It then delves into exploring software-based fuzzing techniques to detect vulnerabilities and enhance embedded system security. Additionally, the paper discusses strategies for improving security in IoT devices with a layered defense strategy known as Snowflake IoT. Finally, it examines approaches to securing large and complex monolithic systems. The challenges and opportunities for securing the embedded systems according to the scale and type of attacks.

In the evolving cyber-threats landscape, conventional security defenses often fall short, relying on reactive countermeasures that limit their ability to address the attack vectors that adapt over time. Proactive defense strategies, such as cyber deception and Moving Target Defense (MTD), aim to pre-emptively control the attack surface and redirect or drain the adversaries actively. Currently, their adoption is hindered by high runtime costs that further limit their scalability for real-world deployments.

Rapid rise in malware attacks has added significant costs to cyber operations. As adversaries evolve, there is a growing need for fast, targeted defenses that effectively guard computer systems against these cyber-attacks. Cyber-deception is an increasingly adopted defense strategy with its ability to continually engage with adversaries and deploy counter-measures proactively by manipulating the malware program execution flow to non-useful states for the attacker. This paper introduces Mayalok, a novel hardware-based cyber-deception framework to combat malware through runtime instruction infusion. Mayalok employs hardware deception primitives to transparently insert or skip malware program instructions during runtime and deliver the attackers a deceptive view of the system state. We evaluate and demonstrate the deception efficacy of the Mayalok framework on malware samples representing various attack vectors: Ransomware, InfoStealers, Buffer overflow, and Side-channels.

Rapid evolution of security attacks presents a perpetual challenge to computer system defenders in terms of continuously upgrading their defense capabilities and being aware of adversarial tactics. Emerging technologies like cyber-deception offer the unique advantage of intelligently surveying hostile behavior while actively safeguarding sensitive assets by manipulating the malware execution flow to non-useful states or misrepresenting critical data.