Robust and unobtrusive in-vehicle physiological monitoring is crucial for ensuring driving safety and user experience. While remote physiological measurement (RPM) offers a promising non-invasive solution, its translation to real-world driving scenarios is critically constrained by the scarcity of comprehensive datasets. Existing resources are often limited in scale, modality diversity, the breadth of biometric annotations, and the range of captured conditions, thereby omitting inherent real-world challenges in driving. Here, we present PhysDrive, the first large-scale multimodal dataset for contactless in-vehicle physiological sensing with dedicated consideration of various modality settings and driving factors. PhysDrive collects data from 48 drivers, including synchronized RGB, near-infrared camera, and raw mmWave radar data, accompanied by six synchronized ground truths (ECG, BVP, Respiration, HR, RR, and SpO2). It covers a wide spectrum of naturalistic driving conditions, including driver motions, dynamic natural light, vehicle types, and road conditions. We extensively evaluate both signal‑processing and deep‑learning methods on PhysDrive, establishing a comprehensive benchmark across all modalities, and release full open‑source code with compatibility for mainstream public toolboxes. We envision PhysDrive will serve as a foundational resource and accelerate research on multimodal driver monitoring and smart‑cockpit systems.

Digital microfluidic biochips (DMFBs) are an emerging technology that implements bioassays through manipulation of discrete fluid droplets. Recent results have shown that DMFBs are vulnerable to actuation tampering attacks, where a malicious adversary modifies control signals for the purposes of manipulating results or causing denial-of-service. Such attacks leverage the highly programmable nature of DMFBs. However, practical DMFBs often employ a technique called pin mapping to reduce control pin count while simultaneously reducing the degrees of freedom available for droplet manipulation. Attempts to control specific electrodes as part of an attack cannot be made without inadvertently actuating other electrodes on-chip, which makes the tampering evident. This paper explores this tamper resistance property of pin mapping in detail. We derive relevant security metrics, evaluate the tamper resistance of several existing pin mapping algorithms, and propose a new security-aware pin mapper. Further, we develop integer linear programming-based methodologies for inserting indicator droplets into a DMFB in order to boost tamper resistance. Experimental results show that the proposed techniques can significantly increase the difficulty for an attacker to make stealthy changes to the execution of a bioassay.

Microfluidic routing fabrics are reconfigurable primitives that permit the dynamic redirection of fluids on a flow-based microfluidic biochip. Such primitives are bringing the benefits of rapid prototyping and on-the-fly reconfigurability from integrated circuits to the microfluidic domain. An unfortunate side effect of this increased flexibility is susceptibility to tampering. A malicious adversary can alter either the electronic control signals or the pneumatic control lines used to drive the routing fabric. In this paper, we provide a high-level security assessment of microfluidic systems utilizing routing fabrics, and analyze their security under actuation tampering attacks. We show that under reasonable assumptions, the permissible states of a routing fabric form a probability distribution. We provide methods for efficiently determining this distribution through a binary tree representation. We then show how to synthesize routings fabrics that exhibit well-defined behaviors. We call a routing fabric designed in such a way tamper-mitigating, as it makes the effects of tampering probabilistically less severe. We then show how the proposed methodology can be used to protect a forensic DNA barcoding application from attack.

It is expected that as digital microfluidic biochips (DMFBs) mature, the hardware design flow will begin to resemble the current practice in the semiconductor industry: design teams send chip layouts to third-party foundries for fabrication. These foundries are untrusted and threaten to steal valuable intellectual property (IP). In a DMFB, the IP consists of not only hardware layouts but also of the biochemical assays (bioassays) that are intended to be executed on-chip. DMFB designers therefore must defend these protocols against theft. We propose to “lock” biochemical assays by inserting dummy mix-split operations. We experimentally evaluate the proposed locking mechanism, and show how a high level of protection can be achieved even on bioassays with low complexity. We also demonstrate a new class of attacks that exploit the side-channel information to launch sophisticated attacks on the locked bioassay.

Digital microfluidic biochips (DMFBs) are versatile, reconfigurable systems for manipulating discrete fluid droplets. Building on the success of DMFBs, platforms based on “sea-of-electrodes,” the micro-electrode-dot-array (MEDA), has been proposed to further increase scalability and reconfigurability. Research has shown that DMFBs are susceptible to actuation tampering attacks which alter control signals and result in fluid manipulation; such attacks have yet to be studied in the context of MEDA biochips. In this paper, we assess the security of MEDA biochips under such attacks, and further argue that it is inherently a more secure platform than traditional DMFBs. First, we identify a new class of actuation tampering attacks specific to MEDA biochips: the micro-droplet attack. We show that this new attack is stealthy as it produces a subtler difference in results compared to traditional DMFBs. We then illustrate our findings through a case study of an MEDA biochip implementing a glucose measurement assay. Second, we enumerate the system features required to secure an MEDA biochip against actuation tampering attacks and show that these features are naturally implemented in MEDA.

Technological shifts in the fields of microfluidics and security are now converging. New techniques in microfluidics increasingly rely on cyberphysical integration and concepts from computer-aided design automation to provide ease-of-use, reliability, and higher throughput. Meanwhile, security concerns are extending beyond traditional information technologies as low-cost computing and sensing proliferates into an ever-increasing number of devices. This keynote paper highlights recent findings and trends in these field to motivate research in the nascent field of cyberphysical microfluidic biochip security and trust.

Advancements in digital microfluidic biochip (DMFB) technologies are paving the way for low-cost and automated platforms for implementing bio-protocols. However, the deployment of DMFBs outside of controlled settings will make them vulnerable to intellectual property (IP) theft. Bio-protocol development requires large investments for cross-domain innovations in biochemical analysis, microfluidics, and cyberphysical systems. We propose a watermarking technique for bio-protocol IP protection-a first in microfluidics-that hierarchically embeds a secret signature across these domains. Such a signature can be exclusively attributed to the owner (like a hash). The proposed solution takes into account the inherent variability in domain-specific parameters such as mixing ratio, sensor calibration, and incubation time. We describe watermarking techniques of varying complexities for different bio-protocol steps. These include watermarking for bio-protocol synthesis parameters and the cyberphysical systems control path parameters. A watermarking scheme based on integer linear programming is proposed for the sample-preparation step of a bio-protocol. The practicality of our solution is demonstrated through case studies involving an immunoassay and several mixing ratios required in the sample-preparation process of bio-protocols. The effectiveness of this approach is evaluated through various security metrics: proof of ownership score, the probability of successful tampering of the watermark, and the probability of coincidence. We also analyze the integrity of the watermark against various possible attacks: brute force search, the insertion of a new watermark, and the watermarking of more parameters.

Digital microfluidic biochips (DMFBs)---an emerging technology that implements bioassays through manipulation of discrete fluid droplets---are vulnerable to actuation tampering attacks, where a malicious adversary modifies control signals for the purposes of manipulating results or causing denial-of-service. Such attacks leverage the highly programmable nature of DMFBs. However, practical DMFBs often employ a technique called pin mapping to reduce control pin count while simultaneously reducing the degrees of freedom available for droplet manipulation. Attempts to control specific electrodes as part of an attack cannot be made without inadvertently actuating other electrodes on-chip, which makes the tampering evident. This paper explores this tamper-resistance property of pin mapping in detail. We derive relevant security metrics, evaluate the tamper-resistance of several existing pin mapping algorithms, and propose a new security-aware pin mapper with superior tamper-resistance as compared to prior work.

It is expected that as digital microfluidic biochips (DMFBs) mature, the hardware design flow will begin to resemble the current practice in the semiconductor industry: design teams send chip layouts to third party foundries for fabrication. These foundries are untrusted, and threaten to steal valuable intellectual property (IP). In a DMFB, the IP consists of not only hardware layouts, but also of the biochemical assays (bioassays) that are intended to be executed on-chip. DMFB designers therefore must defend these protocols against theft. We propose to “lock” biochemical assays through random insertion of dummy mix-split operations, subject to several design rules. We experimentally evaluate the proposed locking mechanism, and show how a high level of protection can be achieved even on bioassays with low complexity. We offer guidance on the number of dummy mixsplits required to secure a bioassay for the lifetime of a patent.

The Micro-electrode-dot-array (MEDA) is a next-generation digital microfluidic biochip (DMFB) platform that supports fine-grained control and real-time sensing of droplet movements. These capabilities permit continuous monitoring and checkpoint-based validation of assay execution on MEDA. This paper presents a class of “shadow attacks” that abuse the timing slack in the assay execution. State-of-the-art checkpoint-based validation techniques cannot expose the shadow operations. We develop a defense that introduces extra checkpoints in the assay execution at time instances when the assay is prone to shadow attacks. Experiments confirm the effectiveness and practicality of the defense.

Digital microfluidic biochips (DMFBs) integrated with processors and arrays of sensors form cyberphysical systems and consequently face a variety of unique, recently described security threats. It has been noted that techniques used for error recovery can provide some assurance of integrity when a cyberphysical DMFB is under attack. This paper proposes the use of such hardware for security purposes through the randomization of checkpoints in both space and time, and provides design guidelines for designers of such systems. We define security metrics and present techniques for improving performance through static checkpoint maps, and describe performance tradeoffs associated with static and random checkpoints. We also provide detailed classification of attack models and demonstrate the feasibility of our techniques with case studies on assays implemented in typical DMFB hardware.

Flow-based microfluidic biochips are revolutionizing biochemical research by automating complex protocols and reducing sample and reagent consumption. Integration of these biochips with sensors, actuators, and intelligent control have compounded these benefits while increasing reliability. And, many flow-based platforms have successfully transitioned to the marketplace, demonstrating their utility through several recent scientific publications. However, these microfluidic technologies and platforms have unintended security and trust implications that threaten their continued success. We survey cyberphysical flow-based microfluidic platforms and perform a security assessment. We then describe an attack on digital polymerase chain reactions and how such attacks undermine research integrity.

Microfluidic routing fabrics, or crossbars, based on transposer primitives provide benefits in manufacturability, performance, and on-the-fly reconfigurability. Many applications in microfluidics, such as DNA barcoding for single-cell analysis, are expected to benefit from these new devices. However, the control of these critical devices poses new security questions that may impact the functional integrity of a microbiology application. This paper explores the many security implications of microfluidic crossbars that directly result from their structure, programmability and use in critical applications. We analyze security performance using new metrics describing how fluids can be "scattered" to incorrect locations under fault-injection attacks, and from these derive a probability model describing the likelihood of a successful attack. We present a case study of a recently described routing fabric proposed for use in a hybrid DNA barcoding platform, and discuss how fabric designers can improve security through architectural choices.

We present a micro-electro-mechanical (MEM) relay based physical unclonable function (PUF) that is capable of sensing pressure while providing an assurance of authenticity. The unique properties of the SensorPUF arise from the pressure sensitivity of electrostatically actuated MEM relay structures. Thus, pres sure sensing is made secure by the integration of the sensor reading with the challenge-response generation circuitry. We evaluate the pressure SensorPUF design in terms of uniqueness, diffuseness, uniformity and bit-aliasing while considering the effect of pressure.

Much progress has been made in digital microfluidic biochips (DMFB), with a great body of literature addressing low-cost, high-performance, and reliable operation. Despite this progress, security of DMFBs has not been adequately addressed. We present an analysis of a DMFB system prone to malicious modification of routes and propose a DMFB defense based on spatio-temporal randomized checkpoints using CCD cameras. Absent the knowledge of the time- and space-randomized checkpoints, an attacker cannot navigate the DMFB without alerting the system. We present an algorithm to guide the placement and timing of the checkpoints such that the probability that an attack can evade detection is minimized. The efficacy of the defense mechanism is illustrated with a case study under stealthy malicious modifications.