Invention Grant
- Patent Title: Quantitative unified analytic neural networks
-
Application No.: US15741172Application Date: 2016-10-24
-
Publication No.: US10691795B2Publication Date: 2020-06-23
- Inventor: Keng Leng Albert Lim
- Applicant: Certis Cisco Security Pte Ltd
- Applicant Address: SG Singapore
- Assignee: Certis Cisco Security Pte Ltd
- Current Assignee: Certis Cisco Security Pte Ltd
- Current Assignee Address: SG Singapore
- Agency: BakerHostetler
- International Application: PCT/SG2016/050515 WO 20161024
- International Announcement: WO2018/080392 WO 20180503
- Main IPC: G06F21/55
- IPC: G06F21/55 ; G06F21/56 ; H04L29/06 ; G06F21/31 ; G06N3/04 ; G06N20/00 ; G06F17/18 ; G06K9/62 ; G06N3/08 ; G06N7/00

Abstract:
This document describes a system and method for quantitatively unifying and assimilating all unstructured, unlabelled and/or fragmented real-time and non-real-time cyber threat data generated by a plurality of sources. These sources may include cyber-security surveillance systems that are equipped with machine learning capabilities.
Public/Granted literature
- US20190095618A1 QUANTITATIVE UNIFIED ANALYTIC NEURAL NETWORKS Public/Granted day:2019-03-28
Information query