A survey on the (in)security of trusted execution environments

As the number of security and privacy attacks continue to grow around the world, there is an ever increasing need to protect our personal devices. As a matter of fact, more and more manufactures are relying on Trusted Execution Environments (TEEs) to shield their devices. In particular, ARM TrustZone (TZ) is being widely used in numerous embedded devices, especially smartphones, and this technology is the basis for secure solutions both in industry and academia. However, as shown in this paper, TEE is not bullet-proof and it has been successfully attacked numerous times and in very different ways. To raise awareness among potential stakeholders interested in this technology, this paper provides an extensive analysis and categorization of existing vulnerabilities in TEEs and highlights the design flaws that led to them. The presented vulnerabilities, which are not only extracted from existing literature but also from publicly available exploits and databases, are accompanied by some effective countermeasures to reduce the likelihood of new attacks. The paper ends with some appealing challenges and open issues.Funding for open access charge: Universidad de Málaga / CBUA This work has been partially supported by the Spanish Ministry of Science and Innovation through the SecureEDGE project (PID2019-110565RB-I00), and by the by the Andalusian FEDER 2014–2020 Program through the SAVE project (PY18-3724)

Methods for finding the sources of leakage in cache-timing attacks and removing the profiling phase

Cryptographic algorithms are widely used in daily life in order to ensure data confidentiality and privacy. These algorithms are extensively analyzed by scientists against a theoretical deficiency. However, these theoretically verified algorithms could still posses security risks if they are not cautiously implemented. Side-channel analysis can infer the secret key by using the information leakage due to implementation flaws. One of the most studied side-channel attack is the Bernstein’s cache-timing attack. This attack owes its reputation to its ability to succeed without a spy process, which is needed to create intentional cache contentions in other cache attacks. However, the exact leakage sources of the Bernstein’s attack remained uncertain to a large extent. Moreover, the need for an identical target system to perform its profiling phase makes the attack unrealistic for real world computing platforms. In this dissertation we address these two problems. Firstly, we propose a methodology to reveal the exact sources of the information leakage. The iv proposed methodology makes use of hardware performance counters to count the number of cache misses, to which the code blocks in the program are subject. Our methodology can help the developers analyze their implementations and fix their code in the early phases of the development. Secondly, we present an approach to extract simplified cache timing-behavior models analytically and propose to use these generated models instead of a profiling phase. The fact that the attack can be accomplished without a profiling phase will lead the attack to be considered a more realistic threat than the attack originally proposed by Bernstein. We believe that, this improved version of the attack will encourage the cryptographic system designers to take further precautions against the attack