WICCA & McAfee: From the Underground to Autonomous Cars

WICCA is teaming up with the ladies of McAfee Advanced Threat Research and Advanced Programs Group teams for a special meetup!
Three women from both these teams will be presenting their research to our community, and everyone is welcome to join.

Talks:

MuddyWater, the APT that targets the Middle East
Covering Threat Intelligence from a nation state perspective, and going over some Muddywater examples that have encoding.

Fooling Autonomous Cars with Model-Hacking
Adversarial machine learning (AML) refers to exploiting underlying vulnerabilities present in intelligent systems by deliberately crafting malicious inputs at various stages of learning. Such inputs, often referred to as adversarial perturbations, result in compromised or misleading outcomes which may have dangerous effects. Although research in this field has been conducted since the past two decades atleast, AML gained immense attention when researchers demonstrated that deep learning based systems often have a blind spot which makes them easily fooled by imperceptible functions. The rise of Generative Adversarial Networks (GANs) played an important role in further pushing the barriers of research. We at McAfee leveraged such existent weaknesses in classifiers and applied it to autonomous cars that rely on AI to recognize and classify traffic signs. We developed physical adversarial stickers on a speed limit sign to cause a targeted misclassification of our custom classifier.

How Chinese Cybercriminals Use Business Playbook to Revamp Underground
This research centers on the emerging threats and trends from the Chinese cybercriminal underground and analyzes the current business models and techniques used by the Chinese cybercriminals. It also highlights drastic changes in operations of Chinese cybercriminals, including the tactics and strategies they are borrowing from Russian cybercriminals.

Presenters:

Jessica Saavedra-Morales – Analyst – Major Campaigns – Advanced Threat Research
Jessica focuses on threat intelligence in the Middle East and Latin American region where she focuses on applying new techniques to tracking threat actors. With a degree in networking and a degree in information technology, Jessica has a background in the tech field for almost two decades. Being fluent in Spanish has steered her to Latin America where she worked with various businesses in the private sector, hunting IOCs and monitoring the threat landscape for any new variants. Jessica thrives on being detailed and thorough in all aspects of life, and is well aligned with McAfee’s mission and future.
https://www.mcafee.com/blogs/author/jessica-saavedra-morales/

Shivangee Trivedi
Shivangee Trivedi is a machine learning researcher working at the cross roads of AI and security for McAfee’s Advanced Threat Research team. She has an active interest in adversarial machine learning, deep learning, computer vision and natural language processing. She obtained her Master’s degree in computer science with a focus on data science from the University of Texas at Dallas and has been with McAfee ATR since 2017. She has worked on sentiment analysis and various supervised classification problems pertaining to computer vision.
https://www.mcafee.com/blogs/author/shivangee-trivedi/

Anne An
Anne An is a senior security researcher for McAfee Labs, where she performs in-depth research on advanced attacks, cybercriminal threats, geopolitical intelligence, risk analysis, as well as cyber campaigns and threat groups in the Asia-Pacific region. Prior to joining McAfee, An held a variety of research positions in advanced threat research and strategic threat intelligence, and delivered regular briefings to senior executives in the cybersecurity field.
https://www.mcafee.com/blogs/author/anne-an/