A secure boot protocol is fundamental to ensuring the integrity of the trusted computing base of a secure system. The use of digital signature algorithms (DSAs) based on traditional asymmetric cryptography, particularly for secure boot, leaves such systems vulnerable to the threat of quantum computers. This paper presents the first post-quantum secure boot solution, implemented fully as hardware for reasons of security and performance. In particular, this work uses the eXtended Merkle Signature Scheme (XMSS), a hash-based scheme that has been specified as an IETF RFC. The solution has been integrated into a secure SoC platform around RISC-V cores and evaluated on an FPGA and is shown to be orders of magnitude faster compared to corresponding hardware/software implementations and to compare competitively with a fully hardware elliptic curve DSA based solution.

While machine learning and deep neural networks in particular, have undergone massive progress in the past years, this ubiquitous paradigm faces a relatively newly discovered challenge, adversarial attacks. An adversary can leverage a plethora of attacking algorithms to severely reduce the performance of existing models, therefore threatening the use of AI in many safety-critical applications. Several attempts have been made to try and understand the root cause behind the generation of adversarial examples. In this paper, we try to relate the geometry of the high-dimensional space in which the model operates and optimizes, and the properties and problems therein, to such adversarial attacks. We present the mathematical background, the intuition behind the existence of adversarial examples and substantiate them with empirical results from our experiments.

We present a solution for online simultaneous localization and mapping (SLAM) self-calibration in the presence of drift in calibration parameters in order to support accurate long-term operation. Calibration parameters such as the camera focal length or camera-to-IMU extrinsics are frequently subject to drift over long periods of operation, inducing cumulative error in the reconstruction. The key contributions are modeling calibration parameters as a spatiotemporal quantity: sensor-to-sensor spatial calibration and sensor intrinsic parameters are continuously time-varying, with statistical tests for change detection and regression. An analysis of the long term effects of inappropriately modeling time-varying sensor calibration is also provided. Constant-time operation is achieved by selecting only a fixed number of informative segments of the trajectory for calibration parameter estimation, giving the added benefit of avoiding early linearization errors by not rolling past measurements into a prior distribution. Our approach is validated with simulated and real-world data.

In this paper we give an evaluation of different direct methods for computing frame-to-frame motion estimates of a moving sensor rig composed of an RGB-D camera and an inertial measurement unit. In particular, we compare how semi-dense and fully dense tracking methods, with and without the aid of an inertial measurement unit (IMU), perform with respect to changes in image resolution, shutter speed, frame-rates, as well as image and depth noise. To perform an accurate and unbiased evaluation we employ a series of synthetically generated datasets using a simulated sensor rig composed of an RGB-D camera and an IMU. Our findings show that in the absence of motion blur or for cameras with high enough frame-rates relative to the camera motion, the methods are comparable when taking in consideration both accuracy and computation time.

Photons can be exploited to reveal secrets of security ICs like smartcards, secure microcontrollers, and cryptographic coprocessors. One such secret is the secret key of cryptographic algorithms. This work gives an overview about current research on revealing these secret keys by exploiting the photonic side channel. Different analysis methods are presented. It is shown that the analysis of photonic emissions also helps to gain knowledge about the attacked device and thus poses a threat to modern security ICs. The presented results illustrate the differences between the photonic and other side channels, which do not provide fine-grained spatial information. It is shown that the photonic side channel has to be addressed by software engineers and during chip design.

At the cutting edge of today's security research and development, the SHA-3 competition evaluates a new secure hashing standard in succession to SHA-2. The five remaining candidates of the SHA-3 competition are BLAKE, Grøstl, JH, Keccak, and Skein. While the main focus was on the algorithmic security of the candidates, a side channel analysis has only been performed for BLAKE and Grøstl [1]. In order to equally evaluate all candidates, we identify side channel attacks on JH-MAC, Keccak-MAC, and Skein-MAC and demonstrate the applicability of the attacks by attacking their respective reference implementation. Additionally, we revisit the side channel analysis of Grøstl and introduce a profiling based side channel attack, which emphasizes the importance of side channel resistant hash functions by recovering the input to the hash function using only the measured power consumption.

Side-channel analysis has become an important field of research for the semiconductor industry and for the academic sector as well. Of particular interest is constructive side-channel analysis as it supports a target-oriented associated design process. The main goal is to increase the side-channel resistance of cryptographic implementations within the design phase by a combination of advanced stochastic methods with design methods, tools, and countermeasures. In this contribution we present a new enhanced tool that utilizes symmetry properties to assist the side-channel evaluation of cryptographic implementations. This technique applies a symmetry metric, which is introduced as an engineering tool to verify the suitability of the leakage model in the evaluation phase of security-sensitive designs. Additionally, this approach also supports the designer in the selection of appropriate time instants.

We introduce a stochastic method for the security evaluation and dynamic power consumption analysis in the context of side-channel analysis. This method allows to estimate data-dependent power consumption induced by secret parameters, e.g. a cryptographic key, which may be exploited in power attacks. In particular, IP-cores for security applications on FPGAs have to be made secure against these attacks. We show that the same stochastic methods provide FPGA designers constructive feedback on the information leakage of the design. Applied as a constructive tool these stochastic methods allow the designer to quantify the side-channel resistance and weaknesses of the IP-core design, a feature which supports the design of secure and side-channel resistant implementations, especially on FPGAs.

In its recently published TCG mobile reference architecture, the TCG Mobile Phone Work Group specifies a new concept to enable trust into future mobile devices. For this purpose, the TCG devises a trusted mobile platform as a set of trusted engines on behalf of different stakeholders supported by a physical trust-anchor. In this paper, we present our perception on this emerging specification. We propose an approach for the practical design and implementation of this concept and how to deploy it to a trustworthy operating platform. In particular we propose a method for the take-ownership of a device by the user and the migration (i.e., portability) of user credentials between devices.