Abstract-In this paper we present a new placement method for cellbased layout styles. It is composed of alternating and interacting global optimization and partitioning steps that are followed by an optimization of the area utilizaiton. Methods using the divide-and-conquer paradigm usually lose the global view by generating smaller and smaller subproblems. In contrast, GORDIAN maintains the simultaneous treatment of all cells over all global optimization steps, thereby considering constraints that reflect the current dissection of the circuit. The global optimizations are performed by solving quadratic programming problems that possess unique global minima. Improved partitioning schemes for the stepwise refinement of the placement are introduced. The area utilization is optimized by an exhaustive slicing procedure. The placement method has been applied to real world problems and excellent results in terms of both placement quality and computation time have been obtained.

Embedded security systems based on Physical Unclonable Functions (PUFs) offer interesting protection properties, such as tamper resistance and unclonability. However, to establish PUFs as a high security primitive in the long run, their vulnerability to side-channel attacks has to be investigated. For this purpose, we analysed the side-channel leakage of PUF architectures and fuzzy extractor implementations. We identified several attack vectors within common PUF constructions and introduce two side-channel attacks on fuzzy extractors. Our proof-ofconcept attack on an FPGA implementation of a fuzzy extractor shows that it is possible to extract the cryptographic key derived from a PUF by side-channel analysis.

In this contribution, we present Complementary Index-Based Syndrome coding (C-IBS), a new and flexible fuzzy embedder for Physical Unclonable Functions (PUFs). C-IBS applies IBS several times to the same group of PUF outputs. The additional parameter permits an application specific tradeoff between error correction capability and implementation complexity. We demonstrate the flexibility of C-IBS by providing efficient solutions that optimize error correction, helper data size or decoder complexity for a well-known key generation scenario. Further, we present encoding criteria that characterize C-IBS fuzzy embedders in general. A hardware implementation is compared to previous work and substantiates the efficiency of C-IBS. The low implementation complexity of C-IBS facilitates the usage for resource constrained cryptographic applications

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Secret key generation with Physical Unclonable Functions (PUFs) is an alternative to conventional secure key storage with non-volatile memory.In a PUF, secret bits are generated by evaluating the internal state of a physical source. Typically, error correction is applied in two stages to remove the instability in the measurement that is caused by environmental influences.We present a new syndrome coding scheme, called Differential Sequence Coding (DSC), for the first error correction stage. DSC applies a fixed reliability criterion and searches the PUF output sequence sequentially until a number of suitable PUF outputs is found. This permits to guarantee the reliability of the indexed PUF outputs. Our analysis demonstrates that DSC is information theoretically secure and highly efficient.To the best of our knowledge, we are the first to propose a convolutional code with Viterbi decoder as second stage error correction for PUFs. We adapt an existing bounding technique for the output bit error probability to our scenario to make reliability statements without the need of laborious simulations.Aiming for a low implementation overhead in hardware, a serialized low complexity FPGA implementation of DSC and the Viterbi decoder is used in this work.For a reference SRAM PUF scenario, PUF size is reduced by 20% and the helper data size decreases by over 40% compared to the best referenced FPGA implementations in each class with a minor increase in the number of slices.