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This report discusses Digital Forensics and Cyber-Security and different vulnerabilities that put the users at risk of compromising their sensitive data and making it available to attackers. With the raising of new threats aiming at technology, some people are not aware of hackers stealing their data. This study will discuss what Cyber-Security is and how many people are aware of what it all entails. This study will also recommendations on how to recognize attacks and learn basic terms to help inform the public. The study utilizes surveys of students from Hampton University so the authors can make the proper analysis and recommendations regarding the issue.
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Discriminative Pattern Mining for Runtime Security Enforcement of Cyber-Physical Point-of-Care Medical Technology
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.
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- Award ID(s):
- 1837472
- PAR ID:
- 10301322
- Date Published:
- Journal Name:
- 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC)
- Page Range / eLocation ID:
- 1066 to 1072
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/COMPSAC51774.2021.00145
