About me
For a long time, my background has led me to the field of Information Security. I believe that technology should be used to overcome the limitations we have as human beings in order to enhance our experience in our daily lives. However, criminals throughout the globe do not necessarily agree with such a premise and use the technological advancements for nefarious purposes. Because of these ill-intended people, an entire field has evolved, which aims to figure out how to secure the technological environment in which we live today. A fundamental goal of this field is to preserve the security and privacy of the end-users. In particular, the research I conduct focuses on the security and privacy of cyber-physical systems, more specifically industrial control systems and the internet of things.
Looking into the future, I believe that incorporating machine learning in an information security implementation can bring an exciting outcome. To the best of my knowledge, the current trend of machine learning applications within the information security field revolves around the usage of machine learning to implement sophisticated anomaly detection schemes. However, I have the conviction that this is just the most intuitive application, and we have yet to discover the true potential of machine learning in this field.
Degrees
in progress
Ph.D. in Computer Science
University of California, Santa Cruz - Santa Cruz, CA, United States
2015 - 2017
M.Sc. in Information Security
Universidad de Los Andes - Bogotá, Colombia
2004 - 2011
B.Sc. in Systems Engineering and Computer Science
Universidad de Los Andes - Bogotá, Colombia
2004 - 2011
B.Sc. in Electronics Engineering
Universidad de Los Andes - Bogotá, Colombia
Certifications
Luis Salazar, Neil Ortiz, Xi Qin, and Alvaro A. Cardenas. 2020.
Towards a High-Fidelity Network Emulation of IEC 104 SCADA Systems. In Proceedings of the 2020 Joint Workshop on CPS&IoT Security and Privacy (CPSIOTSEC'20). Association for Computing Machinery, New York, NY, USA, 3-12.
https://doi.org/10.1145/3411498.3419969
Quinonez R.,
Salazar L., Giraldo J., Cardenas A.A. (2020)
Dynamic Sensor Processing for Securing Unmanned Vehicles. In: Darema F., Blasch E., Ravela S., Aved A. (eds) Dynamic Data Driven Application Systems. DDDAS 2020. Lecture Notes in Computer Science, vol 12312. Springer, Cham.
https://doi.org/10.1007/978-3-030-61725-7_30
Raul Quinonez, University of Texas at Dallas; Jairo Giraldo, University of Utah;
Luis Salazar, University of California, Santa Cruz; Erick Bauman, University of Texas at Dallas; Alvaro Cardenas, University of California, Santa Cruz; Zhiqiang Lin, Ohio State University. 2020.
SAVIOR: Securing Autonomous Vehicles with Robust Physical Invariants. In the 29th USENIX Security Symposium (USENIX Security 20), August, 2019. USENIX Association, pp 895-912. ISBN 978-1-939133-17-5
https://www.usenix.org/conference/usenixsecurity20/presentation/quinonez
Luis E. Salazar and Alvaro A. Cardenas. 2019.
Enhancing the Resiliency of Cyber-Physical Systems with Software-Defined Networks. In ACM Workshop on Cyber-Physical Systems Security & Privacy (CPS-SPC'19), November 11, 2019, London, United Kingdom. ACM, New York, NY, USA, 12 pages.
https://doi.org/10.1145/3338499.3357356