Toward Secure Microfluidic Fully Programmable Valve Array Biochips

Abstract

The fully programmable valve array (FPVA) is a general-purpose programmable flow-based microfluidic platform, akin to the VLSI field-programmable gate array (FPGA). FPVAs are dynamically reconfigurable and, hence, are suitable in a broad spectrum of applications involving immunoassays and cell analysis. Since these applications are safety critical, addressing security concerns is vital for the success and adoption of FPVAs. This study evaluates the security of FPVA biochips. We show that FPVAs are vulnerable to malicious operations similar to digital and flow-based microfluidic biochips. FPVAs are further prone to new classes of attacks-tunneling and deliberate aging. This study establishes security metrics and describes possible attacks on real-life bioassays. Furthermore, we study the use of machine learning (ML) techniques to detect and classify attacks based on the golden and real-time biochip state. In order to boost the classifier's performance, we propose a smart checkpointing mechanism. Experimental results are presented to showcase: 1) best-fit ML model classifier; 2) performance of different tradeoffs in checkpointing; and 3) effectiveness of the proposed smart checkpointing scheme.