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Robust Random Chip ID Generation with Wide-Aperture Clocked Comparators and Maximum Likelihood Detection

机译:具有宽孔径时钟比较器的强大随机芯片ID生成和最大似然检测

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In many applications, mass-produced chips need to be tagged with individual identification numbers (i.e. chip ID). One way to do this without requiring post-fabrication programming steps is to generate the unique ID per chip exploiting random device mismatch. However, it can be prone to mis-identification due to time-varying noise that may cause a different ID to be read from the same chip each time. This paper presents a wide-aperture, low-noise clocked comparator design and a novel ID detection scheme based on maximum likelihoods (ML) that can significantly reduce the probability of mis-identification for such random chip ID generators. A prototype chip fabricated in 0.18-μm CMOS demonstrates the measured input-referred noise of the comparator as low as 265-μV_(rms), while preserving the wide input-referred offset distribution of 22-mV_(rms). As for the detection scheme, the analysis shows that when detecting 1024 unique IDs, the proposed ML detection scheme can achieve the mis-identification rate of 1.73×10~(-18) with 64-bits while the previous scheme based on Hamming distances (HD) would require 90-bits.
机译:在许多应用中,需要用各个识别号码(即芯片ID)标记大规模生产的芯片。在不需要后制造后编程步骤的情况下这样做的一种方法是生成每个芯片利用随机设备不匹配的唯一ID。然而,由于时间变化噪声可能导致每次从同一芯片读取不同的ID,可以容易地识别。本文介绍了基于最大可能性(ML)的宽孔径,低噪声时钟比较器设计和新颖的ID检测方案,可以显着降低这种随机芯片ID发电机的误差识别概率。在0.18-μmCMOS中制造的原型芯片演示了比较器的测量噪声低至265-μV_(RMS),同时保留了22-MV_(RMS)的宽输入偏移分布。对于检测方案,分析表明,当检测1024个唯一ID时,所提出的ML检测方案可以在基于汉明距离的前一级方案的情况下实现1.73×10〜(-18)的错误识别率( HD)需要90位。

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