Title :
TSC: Trustworthy and Scalable Cytometry
Author :
Mehdi Javanmard;Mohsen Amini Salehi;Saman Zonouz
Author_Institution :
Electr. &
Abstract :
Accurate flow cytometry analyses for disease diagnosis purposes requires powerful computational and storage resources that are rarely available in clinical settings. The emerging high-performance cloud computing technologies could potentially address the above-mentioned scalability challenge, however, potentially untrusted cloud infrastructures increases the security and privacy concerns significantly as the attackers may gain knowledge about the patient identity and medical information and affect the consequent course of treatment. In this paper, we present TSC, a trustworthy scalable Cloud-based solution to provide remote cytometry analysis capabilities. TSC enables the medical laboratories to upload the acquired high-frequency raw measurements to the cloud for remote cytometry analysis with high-confidence data security guarantees. In particular, using fundamental cryptographic security solutions, such as the trusted platform module framework, TSC eliminates any possibility of unauthorized sensitive patient data exfiltration to untrusted parties, e.g., malicious or compromised cloud providers. Our evaluation results show that TSC effectively facilitates scalable and efficient disease diagnoses while preserving the patient privacy and treatment correctness.
Keywords :
"Cloud computing","Cryptography","Diseases","Proteins","Electrodes","Sensors"
Conference_Titel :
High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on
DOI :
10.1109/HPCC-CSS-ICESS.2015.125