Zscaler, Inc.

Tarun Dewan

Narinder Paul

Deepen Desai

Shashank Gupta

Rex Shang

Howie Xu

Changsha Ma

Parnit Sainion

Bharath Meesala

Uday Pratap Singh

Naveen Selvan

Nirmal Singh

Rakshitha Hedge

Nirmal Singh Bhary

Rajdeepsinh Dodia

Chiragkumar Kantibhai Prajapati

Computer-implemented systems and methods include receiving unknown content in a cloud-based sandbox; performing an analysis of the unknown content in the cloud-based sandbox; obtaining events based on the analysis; running one or more exploit detection rules on the events; and providing a score based on a result of the one or more rules. The systems and methods can include classifying the unknown content as malware or clean based on the score. The analysis can include a static analysis and a dynamic analysis, with the events generated based thereon.

Exploit detection in a cloud-based sandbox

Systems and methods include performing inline monitoring of production traffic between users, the Internet, and cloud services via a cloud-based system; utilizing a trained machine learning model to inspect static properties of files in the production traffic; and classifying the traffic as one of malicious or benign based on the trained machine learning model.

Utilizing machine learning to detect malicious executable files efficiently and effectively

Systems and methods include determining a plurality of features associated with executable files, wherein the plurality of features are each based on static properties in predefined structure of the executable files; obtaining training data that includes samples of benign executable files and malicious executable files; extracting the plurality of features from the training data; and utilizing the extracted plurality of features to train a machine learning model to detect malicious executable files.

Utilizing Machine Learning to detect malicious executable files efficiently and effectively

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Mohali, India

Tarun Dewan