Kaalbi Technologies Private Limited

Radware, Ltd.

Neeraj Kumar Gupta

Rakesh Thatha

Harisankar Haridas

Sonal Lalchand Oswal

Mohit Rajput

Aman Rawka

Sonal Laichand Oswal

A system and method for detecting and blocking bots are presented. The method includes receiving unlabeled data regarding a visitor of a web source, grouping the received unlabeled data with similar characteristics into a group of data, detecting, based on the group of data, at least one anomaly, and determining, based on the at least one detected anomaly, several visitors to be blacklisted.

System and method for detecting bots based on iterative clustering and feedback-driven adaptive learning techniques

A system of method of detecting bots are presented. The method includes receiving access patterns of a visitor accessing a protected web property, encoding each of the access patterns into a fixed length feature vector, determining an offline-trained model based on past data, generating an anomaly score based on the fixed length feature vector and an offline-trained model, and determining the visitor to be a bot, when the generated anomaly score associated with the visitor reaches a predetermined threshold.

System and method for detecting bots using semi-supervised deep learning techniques

A system and method for detecting bots. The method includes receiving a request to access a server, the request is being received from a client device, and responsive to the request, causing the client device to download a script code file to the client device. The script code file, when executed, collects a profile, and the profile includes a plurality of parameters. The method also includes receiving the created profile, generating a score based on the plurality of parameters to identify a bot, and initiating a mitigation action based on the identified bot.

System and method for detecting bots based on anomaly detection of JavaScript or mobile app profile information

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Bengaluru, India

Neeraj Kumar Gupta