Daniel E Holcomb

US Patent:

20080239793, Oct 2, 2008

Filed:

Mar 28, 2007

Appl. No.:

11/729197

Inventors:

Wayne Burleson - Shutesbury MA, US
Shubhendu S. Mukherjee - Framingham MA, US
Vinod Ambrose - Northboro MA, US
Daniel E. Holcomb - Watertown MA, US

International Classification:

G11C 11/06

US Classification:

365154, 365156

Abstract:

A memory element which includes a family of fault-tolerant storage elements using complementary metal-oxide-semiconductor (CMOS) technology is provided. The memory element provides arbitrary levels of redundancy, allowing the tolerance of multiple single event upsets due to particle hits. The memory element may be used in memory arrays such as caches and register files, and clocked registers and latches found in data path and control structures.

US Patent:

20200396236, Dec 17, 2020

Filed:

Jun 22, 2020

Appl. No.:

16/908045

Inventors:

- Ann Arbor MI, US
Benjamin Andrew Ransford - Seattle WA, US
Daniel Edward Holcomb - Hadley MA, US

Assignee:

Virta Laboratories, Inc. - Ann Arbor MI

International Classification:

H04L 29/06
H04Q 9/00
G06F 21/56
G06F 1/28
H04L 12/24

Abstract:

The present disclosure describes systems and methods for detecting malware. More particularly, the system includes a monitoring device that monitors side-channel activity of a target device. The monitoring device that can work in conjunction with (or independently of) a cloud-based security analytics engine to perform anomaly detection and classification on the side-channel activity. For example, the monitoring device can calculate a first set of features that are then transmitted to the security analytics engine for anomaly detection and classification.

US Patent:

20180007074, Jan 4, 2018

Filed:

Jan 13, 2016

Appl. No.:

15/543234

Inventors:

- Ann Arbor MI, US
Benjamin Andrew Ransford - Seattle WA, US
Daniel Edward Holcomb - Hadley MA, US

Assignee:

Virta Laboratories, Inc. - Ann Arbor MI

International Classification:

H04L 29/06
G06F 1/28
H04L 12/24
H04L 29/08

Abstract:

The present disclosure describes systems and methods for detecting malware. More particularly, the system includes a monitoring device that monitors side-channel activity of a target device. The monitoring device that can work in conjunction with (or independently of) a cloud-based security analytics engine to perform anomaly detection and classification on the side-channel activity. For example, the monitoring device can calculate a first set of features that are then transmitted to the security analytics engine for anomaly detection and classification.