Our editorial team has handpicked the best of the best talks at RSA Conference - one of the largest IT Security Conference in the world. Following is the list of top talks on Machine Learning at RSA Conference USA 2018.
RSA Conference held its event in San Francisco, CA at the Moscone Center & Marriott Marquis and brought together a record number of 50,000 attendees.Attendees experienced keynotes, peer-to-peer sessions, top notch track sessions, tutorials and seminars. Keynotes, sessions and debates focused on New Attack Technique, Encryption, Artificial Intelligence, Machine Learning, Internet Of Things, Cloud Security & Virtualization & many more.
(Source: RSA Conference USA 2018)
1. Evolution of AI Bots for Real-Time Adaptive Security
Speaker: Thomas Caldwell
AI bots historically emerged as chatbots. Early versions were rule-based, adding NLP and machine learning turned them into AI-based bots to be used in sales and support. Thousands of times faster than humans without fatigue, these AI bots have arrived. They are now being applied to Real-Time Adaptive Security. Analyzing cross domain context, events and weeding out false positives in milliseconds.
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2. Fighting Malware with Graph Analytics: An End-to-End Case Study
Speaker: Mayana Pereira
Graph analysis is a powerful tool for modeling malicious group behavior and detecting anomalies in domains ranging from traffic analysis to fraud detection. This talk will cover techniques and open-source tools for graph analytics, including an end-to-end analysis of a novel application of graph analytics to malware detection: from real data collection to the visualization of results.
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3. Security and Privacy of Machine Learning
Speaker: Ian Goodfellow
Machine learning is a powerful new tool that can be used for security applications (for example, to detect malware) but machine learning itself introduces many new attack surfaces. For example, attackers can control the output of machine learning models by manipulating their inputs or training data. In this session, I give an overview of the emerging field of machine learning security and privacy.
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