Google Inc.

Rachel Nakauchi

Yunkai Zhou

Mark Matthew Palatucci

Niels Provos

Clayton Woodward Bavor, Jr

Kamal P Nigam

Panayiotis Mavrommatis

Eric L Davis

Christopher K Monson

Clayton W Bavor Jr

Jr Clayton W Bavor

Intrusion features of a landing page associated with sponsored content are identified. A feature score for the landing page based on the identified intrusion features is generated, and if the feature score for the landing page exceeds a feature threshold, the landing page is classified as a candidate landing page. A sponsor account associated with the candidate landing page can be suspended, or sponsored content associated with the candidate landing page can be suspended.

Detection of malware features in a content item

Intrusive software management

Detecting an intrusive landing page

Landing pages associated with advertisements are partitioned into training landing pages and testing landing pages. Iterative training and testing of a classification mode on intrusion features of the partitioned landing pages is conducted until the occurrence of a cessation event. Feature weights are derived from the iterative training and testing, and are associated with the intrusion features. The associated feature weights and intrusion features can be used to classify other landing pages.

Intrusive feature classification model

Growing community of inventors

San Francisco, CA, United States of America

Rachel Nakauchi