Counterfeiting of goods and electronic devices is a growing problem that has a huge economic impact on the electronics industry. Sometimes the consequences are even more dramatic, when critical systems start failing due to the use of counterfeit lower quality components. Hardware Intrinsic security (i.e. security systems built on the unique electronic fingerprint of a device) offers the potential to reduce the counterfeiting problem drastically. In this paper we will show how Hardware Intrinsic Security (HIS) can be used to prevent various forms of counterfeiting and over-production. HIS technology can also be used to bind software or user data to specific hardware devices, which provides additional security to both soft- and hardware vendors as well as consumers using HIS-enabled products. Besides showing the benefits of HIS, we will also provide an extensive overview of the results (both scientific and industrial) that Intrinsic-ID has achieved studying and implementing HIS.

Due to the unattended nature of WSN (Wireless Sensor Network) deployment, each sensor can be subject to physical capture, cloning and unauthorized device alteration. In this paper, we use the embedded SRAM, often available on a wireless sensor node, for secure data (cryptographic keys, IDs) generation which is more resistant to physical attacks. We evaluate the physical phenomenon that the initial state of a 6T-SRAM cell is highly dependent on the process variations, which enables us to use the standard SRAM circuit, as a Physical Unclonable Function (PUF). Important requirements to serve as a PUF are that the start-up values of an SRAM circuit are uniquely determined, unpredictable and similar each time the circuit is turned on. We present the evaluation results of the internal SRAM memories of low power ICs as PUFs and the statistical analysis of the results. The experimental results prove that the low power 90nm commercial 6T-SRAMs are very useful as a PUF. As far as we know, this is the first work that provides an extensive evaluation of 6T-SRAM-based PUF, at different environmental, electrical, and ageing conditions to representing the typical operating conditions of a WSN.

We address the problem of designing optimal schemes for the generation of secure cryptographic keys from continuous noisy data. We argue that, contrary to the discrete case, a universal fuzzy extractor does not exist. This implies that in the continuous case, key extraction schemes have to be designed for particular probability distributions. We extend the known definitions of the correctness and security properties of fuzzy extractors. Our definitions apply to continuous as well as discrete variables. We propose a generic construction for fuzzy extractors from noisy continuous sources, using independent partitions. The extra freedom in the choice of discretization, which does not exist in the discrete case, is advantageously used to give the extracted key a uniform distribution. We analyze the privacy properties of the scheme and the error probabilities in a one-dimensional toy model with simplified noise. Finally, we study the security implications of incomplete knowledge of the source's probability distribution${\BBP }$. We derive a bound on the min-entropy of the extracted key under the worst-case assumption, where the attacker knows${\BBP }$exactly.

In this paper we propose the idea of using soft decision information in helper data algorithms (HDA). We derive and verify a distribution for the responses of SRAM-based physically unclonable functions (PUFs) and show that soft decision information becomes available without loss in min-entropy of the fuzzy secret. This significantly improves the implementation overhead of using an SRAM PUF + HDA for cryptographic key generation compared to previous constructions.

The increasing use of biometrics has given rise to new privacy concerns. Biometric encryption systems have been proposed in order to alleviate such concerns: rather than comparing the biometric data directly, a key is derived from these data and subsequently knowledge of this key is proved. One specific application of biometric encryption is the use of biometric sketches: in this case biometric template data are protected with biometric encryption. We address the question whether one can undermine a user's privacy given access to biometrically encrypted documents, and more in particular, we examine if an attacker can determine whether two documents were encrypted using the same biometric. This is a particular concern for biometric sketches that are deployed in multiple locations: in one scenario the same biometric sketch is deployed everywhere; in a second scenario the same biometric data is protected with two different biometric sketches. We present attacks on template protection schemes that can be described as fuzzy sketches based on error-correcting codes. We demonstrate how to link and reverse protected templates produced by code-offset and bit-permutation sketches.

In recent years, there has been a tremendous increase in the usage of IT based systems in vehicles, with predictions that in the near future, more than 90% of innovations in the automotive sector will be centered on IT software and hardware. However, innovation also means that intellectual property (IP) is created, which is valuable to third (potentially) untrusted and malicious parties. In particular, automobiles are already suffering from security issues, such as illegal copying of software IP, counterfeiting of electronic components, illegal tampering with digital data inside the electronic control units (ECUs), etc. Recently, physical unclonable functions (PUFs) attracted significant interest for numerous applications such as protection of software and hardware IP, secure key storage and component identification, to name a few. In this paper, we describe how PUFs can be used for secure key storage, component identification, IP protection in vehicle applications, and their suitability for vehicle insurance applications.

In this paper we provide an overview of physical unclonable functions and explain why they are a very valuable technology to protect a company's IP and hence at the same time its brand. Physical unclonable functions are unclonable physical structures that map challenges to responses. They inherit their unclonability from the (deep sub-micron) process variations during manufacturing. They can be turned into a useful tool to generate very secure secret keys in ICs and to provide keys to protect valuable IP of fabless IC companies, IP Vendors and design houses. We will present several examples and explain cryptographic algorithms and protocols to use them in IP protection applications.

The cryptographic protocols that we use in everyday life rely on the secure storage of keys in consumer devices. Protecting these keys from invasive attackers, who open a device to steal its key, is a challenging problem. We propose controlled physical random functions (CPUFs) as an alternative to storing keys and describe the core protocols that are needed to use CPUFs. A physical random functions (PUF) is a physical system with an input and output. The functional relationship between input and output looks like that of a random function. The particular relationship is unique to a specific instance of a PUF, hence, one needs access to a particular PUF instance to evaluate the function it embodies. The cryptographic applications of a PUF are quite limited unless the PUF is combined with an algorithm that limits the ways in which the PUF can be evaluated; this is a CPUF. A major difficulty in using CPUFs is that you can only know a small set of outputs of the PUF—the unknown outputs being unrelated to the known ones. We present protocols that get around this difficulty and allow a chain of trust to be established between the CPUF manufacturer and a party that wishes to interact securely with the PUF device. We also present some elementary applications, such as certified execution.

In recent years, IP protection of FPGA hardware designs has become a requirement for many IP vendors. To this end solutions have been proposed based on the idea of bitstream encryption, symmetric-key primitives, and the use of Physical Unclonable Functions (PUFs). In this paper, we propose new protocols for the IP protection problem on FPGAs based on public-key (PK) cryptography, analyze the advantages and costs of such an approach, and describe a PUF intrinsic to current FPGAs based on SRAM properties. A major advantage of using PK-based protocols is that they do not require the private key stored in the FPGA to leave the device, thus increasing security. This added security comes at the cost of additional hardware resources but it does not cause significant performance degradation.

We investigate the recently introduced notion of smooth Renyi entropy for the case of ergodic information sources, thereby generalizing previous work which concentrated mainly on i.i.d. information sources. We will actually consider ergodic quantum information sources, of which ergodic classical information sources are a special case. We prove that the average smooth Renyi entropy rate will approach the entropy rate of a stationary, ergodic source, which is equal to the Shannon entropy rate for a classical source and the von Neumann entropy rate for a quantum source.

We propose methods to estimate the secrecy-rate of fuzzy sources (e.g. biometrics and physical unclonable functions (PUFs)) using context-tree weighting. In this paper we focus on PUFs. In order to show that our estimates are realistic we first generalize Maurer's (1993) result to the ergodic case. Then we focus on the fact that the entropy of a stationary two-dimensional structure is a limit of a series of conditional entropies, a result by Anastassiou and Sakrison (1982). We extend this result to the conditional entropy of one two-dimensional structure given another one. Finally we show that the general CTW-method approaches the source entropy also in the two-dimensional stationary case. We further extend this result to the two-dimensional conditional entropy. Based on the obtained results we do several measurements on (our) optical PUFs. These measurements allow us to conclude that a secrecy-rate of 0.3 bit/location is possible

Recently, a quantum key exchange protocol that uses squeezed states was presented by Gottesman and Preskill. In this paper we give a generic security proof for this protocol. The method used for this generic security proof is based on recent work by Christiandl, Renner and Ekert

Recently, an information theoretical model for quantum secret sharing (QSS) schemes was introduced. By using this model, we prove that pure state quantum threshold schemes (QTS) can be constructed from quantum MDS codes and vice versa. In particular, we consider stabilizer codes and give a constructive proof of their relation with QTS. Furthermore, we reformulate the monotone span program (MSP) construction according to the information theoretical model and check the recoverability and secrecy requirement. Finally, we consider QSS schemes which are based on quantum teleportation

This work presents a general secure biometric authentication algorithm that guarantees privacy protection of biometric templates. These are all based on the use of a one-way transform and helper data, which is used to achieve noise robustness at the input of the one-way transform. The biometrics templates obtained during enrollment are described by sequences of n i.i.d. random variables. A hashed form of the template is stored together with helper data in a database that is vulnerable to attacks from the inside.

A "physical uncloneable function" (PUF) is a function that is realized by a physical system, such that the function is easy to evaluate but the physical system is hard to characterize. PUFs were introduced as a cost-effective way of generating secure keys for cryptographic purposes. A PUF is a physical system designed such that it interacts in a complicated way with stimuli (challenges) and leads to unique but unpredictable responses. A PUF is similar to a keyed hash function. The key is the physical system consisting of many "random" components.