DNA fingerprinting can offer remarkable benefits, especially for point-of-care diagnostics, information forensics, and analysis. However, the pressure to drive down costs is likely to lead to cheap untrusted solutions and a multitude of unprecedented risks. These risks will especially emerge at the frontier between the cyberspace and DNA biology. To address these risks, we perform a forensic-security assessment of a typical DNA-fingerprinting flow. We demonstrate, for the first time, benchtop analysis of biochemical-level vulnerabilities in flows that are based on a standard quantification assay known as polymerase chain reaction (PCR). After identifying potential vulnerabilities, we realize attacks using benchtop techniques to demonstrate their catastrophic impact on the outcome of the DNA fingerprinting. We also propose a countermeasure, in which DNA samples are each uniquely barcoded (using synthesized DNA molecules) in advance of PCR analysis, thus demonstrating the feasibility of our approach using benchtop techniques. We discuss how molecular barcoding could be utilized within a cyber-biological framework to improve DNA-fingerprinting security against a wide range of threats, including sample forgery. We also present a security analysis of the DNA barcoding mechanism from a molecular biology perspective.

Considerable effort has recently been directed toward the implementation of molecular bioassays on digital-microfluidic biochips (DMFBs). However, today's solutions suffer from the drawback that multiple sample pathways are not supported and on-chip reconfigurable devices are not efficiently exploited. As a result, impractical manual intervention is needed to process protocols for gene-expression analysis. To overcome this problem, we first describe our benchtop experimental studies to understand gene-expression analysis and its relationship to the biochip design specification. We then introduce an integrated framework for quantitative gene-expression analysis using DMFBs. The proposed framework includes: 1) a spatial-reconfiguration technique that incorporates resource-sharing specifications into the synthesis flow; 2) an interactive firmware that collects and analyzes sensor data based on quantitative polymerase chain reaction; and 3) a real-time resource-allocation scheme that responds promptly to decisions about the protocol flow received from the firmware layer. This framework is combined with cyberphysical integration to develop the first design-automation framework for quantitative gene expression. Simulation results show that our adaptive framework efficiently utilizes on-chip resources to reduce time-to-result without sacrificing the chip's lifetime.

Advances in digital-microfluidic biochips have led to miniaturized platforms that can implement biomolecular assays. However, these designs are not adequate for running multiple sample pathways because they consider unrealistic static schedules; hence runtime adaptation based on assay outcomes is not supported and only a rigid path of bioassays can be run on the chip. We present a design framework that performs fluidic task assignment, scheduling, and dynamic decision-making for quantitative epigenetics. We first describe our benchtop experimental studies to understand the relevance of chromatin structure on the regulation of gene function and its relationship to biochip design specifications. The proposed method models biochip design in terms of real-time multiprocessor scheduling and utilizes a heuristic algorithm to solve this NP-hard problem. Simulation results show that the proposed algorithm is computationally efficient and it generates effective solutions for multiple sample pathways on a resource-limited biochip. We also present experimental results using an embedded microcontroller as a testbed.