The First International Workshop on Machine Learning Security and Privacy: Experiences and Applications

The Workshop Scope:

In recent years Artificial Intelligence(AI) and Machine Learning(ML), especially deep learning, have demonstrated their superior performance on a wide variety of complex tasks including speech recognition, natural language processing, image classification, game playing and autonomous vehicles. These successes have stimulated a surge of interests in applying AI and ML techniques into communication systems and networks to deal with problems such as radio access technology classification, low energy consumption in wireless sensor networks, and the management of large scale Internet of Things (IoT). Although ML offer a new and promising design regime to wireless network systems, it has been shown that ML models and systems could severely suffers from various adversarial attacks and privacy risks. The impact of these ML-based security and privacy attacks on the wireless systems are not yet well understood and little research work has been done on it.

On the other hand, the world is moving to digitalization and intelligentization for the long term. We are at an important point in this evolution, as new forces emerge and combine to create new ways for cities to work. For instance, insights from information transfer across platforms can be exploited to reduce accidents, improve air quality, and alert disaster events. Cyber-physical systems (CPS) also bring new risks that arise due to the unexpected interaction within city services. These safety risks arise because of information that distracts users while driving, software errors in medical devices, corner cases in data-driven control, compromised sensors in drones or conflicts in societal policies. In parallel, artificial intelligence flourishes the development of cities, revolutionizing the way that public services are interacted with citizens. The data that drives the smarter city must be secure, to safely fuel unhindered progress.

Therefore, this workshop aims to bring together experts from machine learning, security, privacy, wireless communication communities and smart city to share the latest research findings, exchange ideas, experiences and work-in-process related to all aspects of secure and private machine learning applied to communication and networking systems. Finally, we hope to chart out important research directions for future work and foster research collaborations.