Extended Abstract: Analysis of 1000 Arbiter PUF based RFID Tags

In this extended abstract a large-scale analysis of 4- way Arbiter PUFs is performed with measurement results from 1000 RFID tags. Arbiter PUFs are one of the most important building blocks in PUF-based protocols and have been the subject of many papers. However, in the past often only software simulations or a limited number of test chips were available for analysis. Therefore, the goal of this work is to verify earlier findings in regard to the uniqueness and reliability of Arbiter PUFs by using a much larger measurement set. Furthermore, we used machine learning algorithms to approximate and compare the internal delay differences of the employed PUF. One of the main research questions in this paper is to examine if any “outliers” occurred, i.e., if some tags performed considerably different. This might for example happen due to some unusual manufacturing variations or faults. However, our findings are that for all of the analyzed tags the parameters fell within the range of a Gaussian distribution without significant outliers. Hence, our results are indeed in line with the results of prior work

Trojans in Early Design Steps—An Emerging Threat

Hardware Trojans inserted by malicious foundries during integrated circuit manufacturing have received substantial attention in recent years. In this paper, we focus on a different type of hardware Trojan threats: attacks in the early steps of design process. We show that third-party intellectual property cores and CAD tools constitute realistic attack surfaces and that even system specification can be targeted by adversaries. We discuss the devastating damage potential of such attacks, the applicable countermeasures against them and their deficiencies

Robust Fuzzy Extractors and Helper Data Manipulation Attacks Revisited: Theory vs Practice

Fuzzy extractors have been proposed in 2004 by Dodis et al. as a secure way to generate cryptographic keys from noisy sources. In recent years, fuzzy extractors have become an important building block in hardware security due to their use in secure key generation based on Physical Unclonable Functions (PUFs). Fuzzy extractors are provably secure against passive attackers. A year later Boyen et al. introduced robust fuzzy extractors which are also provably secure against active attackers, i.e., attackers that can manipulate the helper data. In this paper we show that the original provable secure robust fuzzy extractor construction by Boyen et al. actually does not fulfill the error-correction requirements for practical PUF applications. The fuzzy extractors proposed for PUF-based key generation on the other hand that fulfill the error-correction requirements cannot be extended to such robust fuzzy extractors, due to a strict bound $t$ on the number of correctable errors. While it is therefore tempting to simply ignore this strict bound, we present novel helper data manipulation attacks on fuzzy extractors that also work if a ``robust fuzzy extractor-like\u27\u27 construction without this strict bound is used. Hence, this paper can be seen as a call for action to revisit this seemingly solved problem of building robust fuzzy extractors. The new focus should be on building more efficient solutions in terms of error-correction capability, even if this might come at the costs of a proof in a weaker security model

Active and Passive Side-Channel Attacks on Delay Based PUF Designs

Physical Unclonable Functions (PUFs) have emerged as a lightweight alternative to traditional cryptography. The fact that no secret key needs to be stored in non-volatile memory makes PUFs especially well suited for embedded systems in which securely generating and storing secret keys is difficult and expensive. Compared to traditional cryptography, PUFs are often believed to be more resistant to implementation attacks. In this paper we will take a closer look at this assumption. Using a controlled Arbiter PUF as an example, we show that just like traditional cryptography strong PUFs are susceptible to implementation attacks. By combining machine learning with with side-channel analysis we are able to attack designed based on Arbiter PUFs that on are resistant to normal machine learning attacks. We use two different side-channels for our attacks: a passive power side-channel and an active fault attack based on altering the supply voltage of the controlled PUF. Even in the presence of considerable noise both attacks can accurately model the Controlled Arbiter PUF. Hence, the assumption that PUFs are generally more resistant against side-channel attacks is not necessarily true and side-channel resistance needs to be considered when PUF designs are evaluated

Combining Optimization Objectives: New Machine-Learning Attacks on Strong PUFs

Strong Physical Unclonable Functions (PUFs), as a promising security primitive, are supposed to be a lightweight alternative to classical cryptography for purposes such as device authentication. Most of the proposed candidates, however, have been plagued by machine-learning attacks breaking their security claims. The Interpose PUF (iPUF), which has been introduced at CHES 2019, was explicitly designed with state-of-the-art machine-learning attacks in mind and is supposed to be impossible to break by classical and reliability attacks. In this paper, we analyze its vulnerability to reliability attacks. Despite the increased difficulty, these attacks are still feasible, against the original authors’ claim. We explain how adding constraints to the machine-learning objective streamlines reliability attacks and allows us to model all individual components of an iPUF successfully. In order to build a practical attack, we give several novel contributions. First, we demonstrate that reliability attacks can be performed not only with CMA-ES but also with gradient-based optimization. Second, we show that the switch to gradient-based reliability attacks makes it possible to combine reliability attacks, weight constraints, and Logistic Regression (LR) into a single optimization objective. This framework makes machine-learning attacks more efficient, as it exploits knowledge of responses and reliability information at the same time. Third, we show that a differentiable model of the iPUF exists and how it can be utilized in a combined reliability attack. We confirm that iPUFs are harder to break than regular XOR Arbiter PUFs. However, we are still able to break (1,10)-iPUF instances, which were originally assumed to be secure, with less than 10^7 PUF response queries

Bitstream Fault Injections (BiFI) – Automated Fault Attacks against SRAM-based FPGAs

This contribution is concerned with the question whether an adversary can automatically manipulate an unknown FPGA bitstream realizing a cryptographic primitive such that the underlying secret key is revealed. In general, if an attacker has full knowledge about the bitstream structure and can make changes to the target FPGA design, she can alter the bitstream leading to key recovery. However, this requires challenging reverse-engineering steps in practice. We argue that this is a major reason why bitstream fault injection attacks have been largely neglected in the past. In this paper, we show that malicious bitstream modifications are i) much easier to conduct than commonly assumed and ii) surprisingly powerful. We introduce a novel class of bitstream fault injection (BiFI) attacks which does not require any reverse-engineering. Our attacks can be automatically mounted without any detailed knowledge about either the bitstream format of the design or the crypto primitive which is being attacked. Bitstream encryption features do not necessarily prevent our attack if the integrity of the encrypted bitstream is not carefully checked. We have successfully verified the feasibility of our attacks in practice by considering several publicly available AES designs. As target platforms, we have conducted our experiments on Spartan-6 and Virtex-5 Xilinx FPGAs

A Design Methodology for Stealthy Parametric Trojans and Its Application to Bug Attacks

Over the last decade, hardware Trojans have gained increasing attention in academia, industry and by government agencies. In order to design reliable countermeasures, it is crucial to understand how hardware Trojans can be built in practice. This is an area that has received relatively scant treatment in the literature. In this contribution, we examine how particularly stealthy Trojans can be introduced to a given target circuit. The Trojans are triggered by violating the delays of very rare combinational logic paths. These are parametric Trojans, i.e., they do not require any additional logic and are purely based on subtle manipulations on the sub-transistor level to modify the parameters of the transistors. The Trojan insertion is based on a two-phase approach. In the rst phase, a SAT-based algorithm identies rarely sensitized paths in a combinational circuit. In the second phase, a genetic algorithm smartly distributes delays for each gate to minimize the number of faults caused by random vectors. As a case study, we apply our method to a 32-bit multiplier circuit resulting in a stealthy Trojan multiplier. This Trojan multiplier only computes faulty outputs if specic combinations of input pairs are applied to the circuit. The multiplier can be used to realize bug attacks, introduced by Biham et al. In addition to the bug attacks proposed previously, we extend this concept for the specic fault model of the path delay Trojan multiplier and show how it can be used to attack ECDH key agreement protocols. Our method is a general approach to path delay faults. It is a versatile tool for designing stealthy Trojans for a given circuit and is not restricted to multipliers and the bug attack

Universal Quake Statistics: From Compressed Nanocrystals to Earthquakes

Slowly-compressed single crystals, bulk metallic glasses (BMGs), rocks, granular materials, and the earth all deform via intermittent slips or “quakes”. We find that although these systems span 12 decades in length scale, they all show the same scaling behavior for their slip size distributions and other statistical properties. Remarkably, the size distributions follow the same power law multiplied with the same exponential cutoff. The cutoff grows with applied force for materials spanning length scales from nanometers to kilometers. The tuneability of the cutoff with stress reflects “tuned critical” behavior, rather than self-organized criticality (SOC), which would imply stress-independence. A simple mean field model for avalanches of slipping weak spots explains the agreement across scales. It predicts the observed slip-size distributions and the observed stress-dependent cutoff function. The results enable extrapolations from one scale to another, and from one force to another, across different materials and structures, from nanocrystals to earthquakes

The collapse of intermediate structures?

How can we explain the rise of President Trump and the attraction of his campaign behavior before and since he took office? We argue here that the collapse of ‘intermediate structures’ has been a key factor; that the associations and groups which are building blocks of pluralistic politics have been eroded to such an extent that Trump’s personality politics have been able to take over the political stage

Population Structure of Staphylococcus aureus from Remote African Babongo Pygmies

Staphylococcus aureus is a bacterium that colonizes humans worldwide. The anterior nares are its main ecological niche. Carriers of S. aureus are at a higher risk of developing invasive infections. Few reports indicated a different clonal structure and profile of virulence factors in S. aureus isolates from Sub-Saharan Africa. As there are no data about isolates from remote indigenous African populations, we conducted a cross-sectional survey of S. aureus nasal carriage in Gabonese Babongo Pygmies. The isolates were characterized regarding their susceptibility to antibiotic agents, possession of virulence factors and clonal lineage. While similar carriage rates were found in populations of industrialized countries, isolates that encode the genes for the Panton-Valentine leukocidin (PVL) were clearly more prevalent than in European countries. Of interest, many methicillin-susceptible S. aureus isolates from Babongo Pygmies showed the same genetic background as pandemic methicillin-resistant S. aureus (MRSA) clones. We advocate a surveillance of S. aureus in neglected African populations to control the development of resistance to antibiotic drugs with particular respect to MRSA and to assess the impact of the high prevalence of PVL-positive isolates