Andrew Quijano

Andrew Quijano

This is Andrew's personal website, which mostly hosts his research and teaching materials.

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

Out of Our Depth with Deep Fakes: How the Law Fails Victims of Deep Fake Nonconsensual Pornography

Published in Richmond Journal of Law and Technology, 2021

This paper discusses deep fake nonconsensual pornography, and the need for Section 230 revision as copyright law would not provide sufficient protection to victims

Recommended citation: Kate Kobriger, Janet Zhang, Andrew Quijano & Joyce Guo, Out of Our Depth with Deep Fakes: How the Law Fails Victims of Deep Fake Nonconsensual Pornography, 28 Rich. J.L. & Tech 204
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Maximum Covering Subtrees for Phylogenetic Networks

Published in IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2020

This paper solved an open question about the minimum number of nodes to remove from a phylogenetic network N to make it tree-based.

Recommended citation: Davidov, Nathan, et al. "Maximum covering subtrees for phylogenetic networks." IEEE/ACM Transactions on Computational Biology and Bioinformatics 18.6 (2020): 2823-2827.
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Conference Papers

Enhanced Outsourced and Secure Inference for Tall Sparse Decision Trees

Published in IEEE - International Performance Computing and Communications Conference (IPCCC), 2024

This paper is about implementing a privacy-preserving decision tree, but in the case of tall sparse decision trees. To improve performance, we minimize number of encrypted integer comparisons while also generally preserving timing attack resistance

Recommended citation: Quijano, Andrew, et al. "Enhanced Outsourced and Secure Inference for Tall Sparse Decision Trees." 2024 IEEE International Performance, Computing, and Communications Conference (IPCCC). IEEE, 2024.
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Privacy-Preserving Drone Navigation Through Homomorphic Encryption for Collision Avoidance

Published in IEEE Local Computer Networks (LCN), 2024

This paper implements the line intersection algorithm using partially Homomorphic encryption. This approach leads to much faster performance and maintain privacy of the paths of two drones.

Recommended citation: Luedeman, Allan, et al. "Privacy-Preserving Drone Navigation Through Homomorphic Encryption for Collision Avoidance." 2024 IEEE 49th Conference on Local Computer Networks (LCN). IEEE, 2024.
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Server-side Fingerprint-Based Indoor Localization Using Encrypted Sorting

Published in IEEE Mobile Ad Hoc and Sensor Systems (MASS), 2019

This paper is about secure indoor localization using homomorphic encryption. We compare an approach of sorting encrypted numbers at the server compared to decrypting at the client phone. While decrypting at the server is slower, it does save some battery for the client

Recommended citation: Quijano, Andrew, and Kemal Akkaya. "Server-side fingerprint-based indoor localization using encrypted sorting." 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW). IEEE, 2019.
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