Topics in Secure Embedded System Design
Pervasive networks have led to widespread use of embedded systems, like cell phones, PDAs, RFIDs etc., in increasingly diverse applications. Many of these embedded system appli- cations handle sensitive data (e.g., credit card information on a mobile phone/PDA) or perform critical functions (e.g., medical devices or automotive electronics), and the use of security protocols is imperative to maintain condentiality, integrity and authentication of these applications. Typically embedded systems have low computing power and nite energy supply based on a battery, and these factors are at odds with the computationally intensive nature of the cryptographic algorithms underlying many security protocols. In addition, secure embedded systems are vulnerable to attacks, like physical tampering, malware and side-channel attacks. Thus, design of secure embedded systems is guided by the following factors: small form factor, good performance, low energy consumption (and, thus,longer battery life), and robustness to attacks. This thesis presents our work on tackling three issues in the design of secure embedded systems: energy consumption, performance and robustness to side-channel attacks. First, we present our work on optimizing the energy consumption of the widely employed secure sockets layer (SSL) protocol running on an embedded system. We discuss results of energy analysis of various cryptographic algorithms, and the manner in which this information can be used to adapt the operation of SSL protocol to save energy. Next, we present results of our experiments on optimizing the performance of Internet protocol security (IPSec) protocol on an embedded processor. Depending on the mode of operation, the IPSec computation is dominated by cryptographic or non-cryptographic processing. We demonstrate how both these components of the IPSec protocol can be optimized by leveraging the extensible and congurable features of an embedded processor. Next, we introduce a satisfability-based framework for enabling side-channel attacks on cryptographic software running on an embedded processor. This framework enables us to identify variables in the software implementations which result in the disclosure of the secret key used. Thus, security of software implementations can be improved by better protection of these identified variables. Finally, we conclude by introducing a novel memory integrity checking protocol that has much lower communication complexity than existing Merkle tree-based protocols while incurring a modest price in computation on the processor. This scheme is based on Toeplitz matrices, and can be very efficiently realized on embedded systems with hardware extensions for bit matrix operations.
Summary
This 2008 PhD thesis examines the security challenges unique to resource-constrained embedded systems used in pervasive networks, such as mobile devices, PDAs and RFIDs. Readers will learn how computational and energy limits affect cryptographic choices, how physical tampering and malware threaten devices, and approaches to designing secure, efficient firmware and system-level protections.
Key Takeaways
- Assess trade-offs between cryptographic strength and resource constraints to select lightweight primitives suitable for battery-powered devices.
- Design firmware and system architectures that minimize attack surface while accommodating limited CPU, memory, and energy budgets.
- Implement energy-aware security protocols and optimizations (e.g., algorithm selection, duty-cycling, offloading) to preserve device lifetime.
- Mitigate physical attacks and tampering through hardware-software co-design techniques such as tamper detection, secure key storage, and redundancy.
- Evaluate threat models for embedded contexts (malware, side-channels, fault injection) and integrate corresponding countermeasures into development processes.
Who Should Read This
Embedded/firmware engineers and security researchers with some experience in constrained devices who need practical guidance on designing secure IoT and embedded systems under tight resource limits.
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