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2022-03-22
Love, Fred, Leopold, Jennifer, McMillin, Bruce, Su, Fei.  2021.  Discriminative Pattern Mining for Runtime Security Enforcement of Cyber-Physical Point-of-Care Medical Technology. 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC). :1066—1072.
Point-of-care diagnostics are a key technology for various safety-critical applications from providing diagnostics in developing countries lacking adequate medical infrastructure to fight infectious diseases to screening procedures for border protection. Digital microfluidics biochips are an emerging technology that are increasingly being evaluated as a viable platform for rapid diagnosis and point-of-care field deployment. In such a technology, processing errors are inherent. Cyber-physical digital biochips offer higher reliability through the inclusion of automated error recovery mechanisms that can reconfigure operations performed on the electrode array. Recent research has begun to explore security vulnerabilities of digital microfluidic systems. This paper expands previous work that exploits vulnerabilities due to implicit trust in the error recovery mechanism. In this work, a discriminative data mining approach is introduced to identify frequent bioassay operations that can be cyber-physically attested for runtime security protection.
2020-11-02
Lin, Chun-Yu, Huang, Juinn-Dar, Yao, Hailong, Ho, Tsung-Yi.  2018.  A Comprehensive Security System for Digital Microfluidic Biochips. 2018 IEEE International Test Conference in Asia (ITC-Asia). :151—156.

Digital microfluidic biochips (DMFBs) have become popular in the healthcare industry recently because of its lowcost, high-throughput, and portability. Users can execute the experiments on biochips with high resolution, and the biochips market therefore grows significantly. However, malicious attackers exploit Intellectual Property (IP) piracy and Trojan attacks to gain illegal profits. The conventional approaches present defense mechanisms that target either IP piracy or Trojan attacks. In practical, DMFBs may suffer from the threat of being attacked by these two attacks at the same time. This paper presents a comprehensive security system to protect DMFBs from IP piracy and Trojan attacks. We propose an authentication mechanism to protect IP and detect errors caused by Trojans with CCD cameras. By our security system, we could generate secret keys for authentication and determine whether the bioassay is under the IP piracy and Trojan attacks. Experimental results demonstrate the efficacy of our security system without overhead of the bioassay completion time.

2017-06-05
Love, Fred, McMillin, Bruce, Tulasidas, Sivanesan, Balachandran, W..  2016.  Multiple Security Domain Nondeducibility for Point-of-care Diagnostic Technology: WiP Abstract. Proceedings of the 7th International Conference on Cyber-Physical Systems. :42:1–42:1.

Microfluidics is an interdisciplinary science focusing on the development of devices and systems that process low volumes of fluid for applications such as high throughput DNA sequencing, immunoassays, and entire Labs-on-Chip platforms. Microfluidic diagnostic technology enables these advances by facilitating the miniaturization and integration of complex biochemical processing through a microfluidic biochip [1]. This approach tightly couples the biochemical operations, sensing system, control algorithm, and droplet-based biochip. During the process the status of a droplet is monitored in real-time to detect operational errors. If an error has occurred, the control algorithm dynamically reconfigures to allow recovery and rescheduling of on-chip operations. During this recovery procedure the droplet that is the source of the error is discarded to prevent the propagation of the error and the operation is repeated. Threats to the operation of the microfluidics biochip include (1) integrity: an attack can modify control electrodes to corrupt the diagnosis, and (2) privacy: what can a user/operator deduce about the diagnosis? It is challenging to describe both these aspects using existing models; as Figure 1 depicts there are multiple security domains, Unidirectional information flows shown in black indicate undesirable flows, the bidirectional black arrows indicate desirable, but possibly corrupted, information flows, and the unidirectional red arrows indicate undesirable information flows. As with Stuxnet, a bidirectional, deducible information flow is needed between the monitoring security domain and internal security domain (biochip) [2]. Simultaneously, the attacker and the operators should receive a nondeducible information flow. Likewise, the red attack arrows should be deducible to the internal domain. Our current security research direction uses the novel approach of Multiple Security Domain Nondeducibility [2] to explore the vulnerabilities of exploiting this error recovery process through information flow leakages and leads to protection of the system through desirable information flows.