Datashapes, Inc.

Akamai Technologies, Inc.

Other

California Institute of Technology

Rokio, Inc.

Tyson J Thomas

Jeffrey Brian Adams

Michael P Kelley

Eric C Schneider

Frank George Evans

Kristopher Robert Buschelman

Karl P Geiger

Timothy J Carruthers

Zhige Xin

Zixu Wang

A bot detection service associated with an overlay network operates to score traffic as a probability of being a bot, as opposed to returning a binary classification (i.e., bot or human). According to the approach herein, scoring is determined through probability estimates, wherein a score (the probability) is based on considering a set of detections concurrently. In one embodiment, all (or substantially all) triggered (current) threat detections contribute to the score. The preferred approach penalizes requests that fail all (or substantially all) combinations of detection algorithms. According to a further feature, an automated tuning (autotuning) is also applied, e.g., using real-time empirical statistical models, to adapt the measurement of false positive probability for one or more threat detection algorithms to suit customer traffic trends. The approach herein is also extensible to include any number of future threat detection algorithms.

Combining multiple detection algorithms into a confidence score for bot detection

Methods and apparatus are described that enable consumers of media content to identify and navigate to content of interest. A graphical user interface (GUI) is provided in association with media content in which entities (e.g., keywords or distinct speakers) represented in the media content are presented in relation to the media timeline of the media content.

Navigating content by relevance

A bot detection service is enhanced by providing improved threat scoring using dynamic clustering of telemetry data received from a server. The detection approach leverages the notion that bot traffic is statistically anomalous compared to empirical models of human traffic. In particular, bots have more similar and repeating network patterns (i.e., lists of field values derived from client telemetry) that lend themselves to tighter clustering than random human traffic. The technique herein leverages this notion by providing a bot detection service with a network pattern clustering algorithm that differentiates bot-versus-human traffic by searching for similar and repeating network patterns that cluster together by virtue of having lesser variation (as compared to human traffic) in their field value sets.

Detecting automated attacks on computer systems using real-time clustering

Methods, apparatuses and systems directed to pattern learning, recognition, and metrology. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In certain implementations, the present invention provides for methods and systems suitable for analyzing and recognizing patterns in biological signals such as multi-electrode array waveform data. In other implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes. In other implementations, the present invention provides methods and systems for dynamic learning of patterns in supervised and unsupervised manners.

Pattern recognition system

A fishing tool is provided to enable retrieval of a fish from a mineral extraction system. The downhole fishing tool includes a frustoconical member for guiding broken fish such as a broken pipe into a channel created by a sliding car and an edge of a body of the downhole fishing tool. The channel enlarges by sliding the sliding car along the body of the downhole fishing tool. The downhole fishing tool body and sliding car are aligned such that the sliding car slides diagonally across the body of the downhole fishing tool thus creating a larger channel at a first point along the diagonal than at a second point along the diagonal.

Downhole fishing tool

A pattern recognizer which uses neuromorphs with a fixed amount of energy that is distributed among the elements. The distribution of the energy is used to form a histogram which is used as a feature vector.

Growing community of inventors

San Francisco, CA, United States of America

Tyson J Thomas