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Instead the contents decay rather slowly, in particular if the DRAM chips are cooled to low temperatures. This effect opens an attack vector on cryptographic applications that keep decrypted keys in DRAM. An attacker with access to the target computer can reboot it or remove the RAM modules and quickly copy the RAM contents to non-volatile memory. By exploiting the known cryptographic structure of the cipher and layout of the key data in memory, in our application an AES key schedule with redundancy, the resulting memory image can be searched for sections that could correspond to decayed cryptographic keys; then, the attacker can attempt to reconstruct the original key. However, the runtime of these algorithms grows rapidly with increasing memory image size, error rate and complexity of the bit error model, which limits the practicability of the approach.In this work, we study how the algorithm for key search can be accelerated with custom computing machines. We present an FPGA-based architecture on a Maxeler dataflow computing system that outperforms a software implementation up to 205x, which significantly improves the practicability of cold-attacks against AES.","lang":"eng"}],"user_id":"15278","ddc":["040"],"citation":{"bibtex":"@inproceedings{Riebler_Kenter_Sorge_Plessl_2013, title={FPGA-accelerated Key Search for Cold-Boot Attacks against AES}, DOI={10.1109/FPT.2013.6718394}, booktitle={Proceedings of the International Conference on Field-Programmable Technology (FPT)}, publisher={IEEE}, author={Riebler, Heinrich and Kenter, Tobias and Sorge, Christoph and Plessl, Christian}, year={2013}, pages={386–389} }","mla":"Riebler, Heinrich, et al. “FPGA-Accelerated Key Search for Cold-Boot Attacks against AES.” Proceedings of the International Conference on Field-Programmable Technology (FPT), IEEE, 2013, pp. 386–89, doi:10.1109/FPT.2013.6718394.","apa":"Riebler, H., Kenter, T., Sorge, C., & Plessl, C. (2013). 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After suitable components have been found, they are automatically integrated, configured and brought to execution in an On-The-Fly Compute Center. We envision that these future compute centers will continue to leverage three current trends in large scale computing which are an increasing amount of parallel processing, a trend to use heterogeneous computing resources, and—in the light of rising energy cost—energy-efficiency as a primary goal in the design and operation of computing systems. 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