Abstract. Secure storage of cryptographic keys in hardware is an essential building block for high security applications. It has been demonstrated that Physically Unclonable Functions (PUFs) based on uninitialized SRAM are an effective way to securely store a key based on the unique physical characteristics of an Integrated Circuit (IC). The startup state of an SRAM memory is unpredictable but not truly random as well as noisy, hence privacy amplification techniques and a Helper Data Algorithm (HDA) are required in order to recover the correct value of a full entropy secret key. At the core of an HDA are error correcting techniques. The best known method to recover a full entropy 128-bit key requires 4700 SRAM cells. Earlier work by Maes et al. has reduced the number of SRAM cells to 1536 by using soft decision decoding; however, this method requires multiple measurements (and thus also power resets) during the storage of a key, which will be shown to be an unacceptable overhead for many applications. This article demonstrates how soft decision decoding with only a single measurement during storage can reduce the required number of SRAM cells to 3900 (a 17% reduction) without increasing the size of en-/decoder. The number of SRAM cells can even be reduced to 2900 (a 38% reduction). This does increase cost of the decoder, but depending on design requirements it can be shown to be worthwhile. Therefore, it is possible to securely store a 128-bit key at a very low overhead in an IC or FPGA.

Abstract. PUF-based key generators have been widely considered as a root-of-trust in digital systems. They typically require an error-correcting mechanism (e.g. based on the code-offset method) for dealing with bit errors between the enrollment and reconstruction of keys. When the used PUF does not have full entropy, entropy leakage between the helper data and the device-unique key material can occur. If the entropy level of the PUF becomes too low, the PUF-derived key can be attacked through the publicly available helper data. In this work we provide several solutions for preventing this entropy leakage for PUFs suffering from bias. The methods proposed in this work pose no limit on the amount of bias that can be tolerated, which solves an important open problem for PUFbased key generation. Additionally, the solutions are all evaluated based on reliability, efficiency, leakage and reusability showing that depending on requirements for the key generator different solutions are preferable.

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S hould service capacities (such as agent groups in call centers) be pooled or not? This paper will show that there is no single answer. For the simple but generic situation of two (strictly pooled or unpooled) server groups, it will provide (1) insights and approximate formulae, (2) numerical support, and (3) general conclusions for the waiting-time effect of pooling. For a single call type, this effect is clearly positive, as represented by a pooling factor. With multiple job types, however, the effect is determined by both a pooling and a mix factor. Due to the mix factor, this effect might even be negative. In this case, it is also numerically illustrated that an improvement of both the unpooled and the strictly pooled scenario can be achieved by simple overflow or threshold scenarios. The results are of both practical and theoretical interest: practical for awareness of this negative effect, the numerical orders, and practical scenarios in call centers, and theoretical for further research in more complex situations.