Cheesehacks Track: SECURITY AND PRIVACY
Inspiration
Explaining and Harnessing Adversarial Examples (Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy, 2015)
What it does
From a single video feed source, we can classify objects through 3 different architectures, while maintaining integrity from attackers using noise attacks or intentional changes on the bitwise level of frames.
How we built it
Python for our encryption/decription algoritms, React for the frontend, and Docker cluster for the AI object detection nodes. Kafka/RedPanda for sending frames upstream so all nodes can fetch frames from 1 source, rather than 1 source pushing to many nodes.
Challenges we ran into
Ensuring that all nodes were in sync with each other during frame ingestion.
Accomplishments that we're proud of
Implementing a functional solution to a real world problem that is only growing in its attack vector.
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