Li Xueqi, Lin Bohan, Gao Bin, Lu Yuyao, Yang Siyao, Su Zhiqiang, Shen Ting-Ying, Tang Jianshi, Qian He, Wu Huaqiang
School of Integrated Circuits, Beijing Advanced Innovation Center for Integrated Circuits, Tsinghua University, Beijing, 100084, China.
MemInsights Technology Inc., Beijing, China.
Sci Adv. 2025 Mar 28;11(13):eadr0112. doi: 10.1126/sciadv.adr0112. Epub 2025 Mar 26.
Security primitives ensure Internet of Things (IoT) security by generating stable keys from physically unclonable functions (PUFs) and unpredictable bitstreams from true random number generators (TRNGs). Considering the restricted resources on IoT motes, a promising design trend is to unify PUF and TRNG by sharing the same entropy source and multiplexing entropy extractor. Here, we report a unified PUF and TRNG chip based on a 28-nanometer embedded memristor with concealable ability. We use the memristor intrinsic FORMING condition variation and read current variation as entropy sources and design a compact on-chip entropy extractor that achieves a high throughput of 41.7 megabits per second with minimal area overhead of 0.291 MF. To prevent PUF data leakage, we developed a concealment method, protecting data when idle and enabling recovery upon demand. Comprehensive testing shows the chip has excellent performance in randomness, reliability, lifetime, and stability, achieving a 3.82-fold throughput improvement over complementary metal-oxide semiconductor-based designs in authentication tasks.
安全原语通过从物理不可克隆函数(PUF)生成稳定密钥以及从真随机数发生器(TRNG)生成不可预测比特流来确保物联网(IoT)安全。考虑到物联网节点上的资源受限,一个有前景的设计趋势是通过共享相同的熵源和复用熵提取器来统一PUF和TRNG。在此,我们报告了一种基于具有可隐藏能力的28纳米嵌入式忆阻器的统一PUF和TRNG芯片。我们将忆阻器的固有形成条件变化和读取电流变化用作熵源,并设计了一种紧凑的片上熵提取器,其实现了每秒41.7兆比特的高吞吐量,且面积开销最小,仅为0.291平方毫米。为防止PUF数据泄露,我们开发了一种隐藏方法,在空闲时保护数据,并在需要时实现数据恢复。全面测试表明,该芯片在随机性、可靠性、寿命和稳定性方面具有出色性能,在认证任务中比基于互补金属氧化物半导体的设计实现了3.82倍的吞吐量提升。