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An Energy-Efficient Compressed Sensing-Based Encryption Scheme for Wireless Neural Recording
IEEE Journal on Emerging and Selected Topics in Circuits and Systems ( IF 3.7 ) Pub Date : 2021-04-22 , DOI: 10.1109/jetcas.2021.3074938
Xilin Liu , Andrew G. Richardson , Jan Van der Spiegel

This paper presents a compressed sensing (CS) based encryption scheme for wireless neural recording. An ultrahigh efficiency was achieved by leveraging CS for simultaneous data compression and encryption. CS enables sub-Nyquist sampling of neural signals by taking advantage of their intrinsic sparsity, while the CS process simultaneously encrypts the data with the sampling matrix being the cryptographic key. To share the key over an insecure wireless channel, we implemented an elliptic-curve cryptography (ECC) based key exchanging protocol. Local key shuffle and updating were adopted to eliminate the risks of potential information leakage. CS was executed in an application-specific integrated circuits (ASIC) fabricated in 180nm CMOS technology. Mixed-signal circuits were designed to optimize the power efficiency of the matrix-vector multiplication (MVM) of the CS operation. The ECC was implemented in a low-power Cortex-M0 based microcontroller (MCU). To be protected from timing attacks, the implementation avoided possible data-dependent branches. A wireless neural recorder prototype has been developed to demonstrate the proposed scheme. The prototype achieved an 8× data rate reduction and a 35× power saving compared with conventional implementation. The overall power consumption of ASIC and MCU was 442μW during the encrypted wireless transmission. The average correlated coefficient between the reconstructed signals and the uncompressed signals was 0.973, while the ciphertext-only attacks (CoA) achieved no better than 0.054 over 200,000 attacks. This work demonstrates a promising data compression and encryption scheme that can be used in a wide range of low-power signal recording systems with security requirements.

中文翻译:


一种基于压缩感知的节能无线神经记录加密方案



本文提出了一种基于压缩感知(CS)的无线神经记录加密方案。利用 CS 同时进行数据压缩和加密,实现了超高效率。 CS 利用神经信号固有的稀疏性实现了亚奈奎斯特采样,同时 CS 过程同时以采样矩阵作为加密密钥对数据进行加密。为了通过不安全的无线通道共享密钥,我们实现了基于椭圆曲线加密 (ECC) 的密钥交换协议。采用本地密钥洗牌和更新的方式,消除潜在的信息泄露风险。 CS 在采用 180nm CMOS 技术制造的专用集成电路 (ASIC) 中执行。混合信号电路旨在优化 CS 运算的矩阵向量乘法 (MVM) 的功效。 ECC 在基于 Cortex-M0 的低功耗微控制器 (MCU) 中实现。为了防止时序攻击,该实现避免了可能的数据相关分支。已经开发出无线神经记录器原型来演示所提出的方案。与传统实现相比,该原型实现了 8 倍的数据速率降低和 35 倍的节能。加密无线传输过程中ASIC和MCU的整体功耗为442μW。重建信号和未压缩信号之间的平均相关系数为 0.973,而纯密文攻击 (CoA) 在 200,000 次攻击中的效果不高于 0.054。这项工作展示了一种有前途的数据压缩和加密方案,可广泛用于具有安全要求的低功耗信号记录系统。
更新日期:2021-04-22
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