Subject: [Maprg] Call for virtual participation to the 1st Workshop on Security and Privacy for Mobile AI (MAISP)

From: KLEOMENIS KATEVAS <[email-masked]>
Date: Fri, 18 Jun 2021 13:02:40 +0000

[Please accept our apologies for potential cross-postings]

Call for virtual participation to the 1st Workshop on Security and Privacy for Mobile AI (MAISP), co-located with ACM MobiSys 2021.
https://maisp.gitlab.io

This 1st edition of the S&P for Mobile AI workshop aims to bring together researchers in the areas of security and privacy with respect to mobile systems, networking, and AI, to discuss challenging topics, share new ideas, and exchange experiences across these areas, from both theoretical and experimental perspectives.

Where: Virtual
Timezone: CEST
When: 14.00 - 20.30, June 24th, 2021

Highlights:
* Four keynotes:
- "Can we trust AI to secure our edge?" by Paul Patras (University of Edinburgh | Net AI)
- "Defence Against Dark Artefacts" by Hamed Haddadi (Imperial College London | Brave Software)
- "Decentralized Privacy Preserving Artificial Intelligence for Next Generation Telco Industry" by Diego Perino (Telefonica Research)
- "The ML data center is dead: What comes next?" by Nic Lane (University of Cambridge | Samsung AI Center)

* Paper Presentations:
- "Open, Sesame! Introducing Access Control to Voice Services"
- "Your Eyes Show What Your Eyes See (Y-EYES): Challenge-Response Anti-Spoofing Method for Mobile Security Using Corneal Specular Reflections"
- "Temporal Consistency Checks to Detect LiDAR Spoofing Attacks on Autonomous Vehicle Perception"
- "Surprising Privacy Threats from Innocuous Sensors"
- "Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs"

Registrations for the full MobiSys '21 and all workshops:
- ACM/SIG Professional Member: $20
- ACM/SIG Student Member: $10
- Non-Member: $50
- Non-Member Student: $30
through https://www.sigmobile.org/mobisys/2021/registration.html

--
Kleomenis Katevas
Research Scientist, Telefónica R&D
https://minoskt.github.io

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