Benjamin P Edwards

US Patent:

20210150042, May 20, 2021

Filed:

Nov 15, 2019

Appl. No.:

16/685474

Inventors:

- Armonk NY, US
Frederico Araujo - White Plains NY, US
Teryl Taylor - Danbury CT, US
Marc Phillipe Stoecklin - White Plains NY, US
Benjamin James Edwards - Ossining NY, US
Ian Michael Molloy - Westchester NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 21/62
H04L 9/08
G06F 17/16
G06N 20/00

Abstract:

A neural network is trained using a training data set, resulting in a set of model weights, namely, a matrix X, corresponding to the trained network. The set of model weights is then modified to produce a locked matrix X′, which is generated by applying a key. In one embodiment, the key is a binary matrix {0, 1} that zeros (masks) out certain neurons in the network, thereby protecting the network. In another embodiment, the key comprises a matrix of sign values {−1, +1}. In yet another embodiment, the key comprises a set of real values. Preferably, the key is derived by applying a key derivation function to a secret value. The key is symmetric, such that the key used to protect the model weight matrix X (to generate the locked matrix) is also used to recover that matrix, and thus enable access to the model as it was trained.

US Patent:

20190199731, Jun 27, 2019

Filed:

Dec 22, 2017

Appl. No.:

15/851852

Inventors:

- Armonk NY, US
Taesung Lee - Ridgefield CT, US
Ian M. Molloy - Chappaqua NY, US
Suresh Chari - Scarsdale NY, US
Benjamin J. Edwards - Ossining NY, US

International Classification:

H04L 29/06
G06F 17/30

Abstract:

Jointly discovering user roles and data clusters using both access and side information by performing the following operation: (i) representing a set of users as respective vectors in a user feature space; representing data as respective vectors in a data feature space; (ii) providing a user-data access matrix, in which each row represents a user's access over the data; and (iii) co-clustering the users and data using the user-data matrix to produce a set of co-clusters.

US Patent:

20180359270, Dec 13, 2018

Filed:

Jun 12, 2017

Appl. No.:

15/619598

Inventors:

- Armonk NY, US
Benjamin Edwards - Yorktown Heights NY, US
Taesung Lee - White Plains NY, US
Ian M. Molloy - Chappaqua NY, US

International Classification:

H04L 29/06

Abstract:

Detecting anomalous user behavior is provided. User activity is logged for a set of users. The user activity is divided into distinct time intervals. For each distinct time interval, logged user activity is converted to a numerical representation of each user's activities for that distinct time interval. A clustering process is used on the numerical representations of user activities to determine which users have similar activity patterns in each distinct time interval. A plurality of peer groups of users is generated based on determining the similar activity patterns in each distinct time interval. Anomalous user behavior is detected based on a user activity change in a respective peer group of users within a distinct time interval.