Career records & work history
License Records
Javed Muhammad Aslam
Licenses:
License #: 040215
Category: Pharmacist
Issued Date: Aug 29, 1990
Type: PHARMACY
Category: Pharmacist
Issued Date: Aug 29, 1990
Type: PHARMACY
Javed A Aslam, 5915 Columbine Rd, Cherry Brook, MA 02493
Javed Aslam Phones & Addresses
15 Columbine Rd, Weston, MA 02493 781-4314529
Quechee, VT
Dover, MA
35 Rip Rd, Hanover, NH 03755 603-6434624 603-6439721
Lebanon, NH
Cambridge, MA
Mentions for Javed A Aslam
Javed Aslam resumes & CV records
Resumes
Associate Professor At Northeastern University And Research Consultant
Position:
Associate Professor at Northeastern University
Location:
Greater Boston Area
Industry:
Research
Work:
Northeastern University
Associate Professor Dartmouth College 1995 - 2003
Assistant Professor
Associate Professor Dartmouth College 1995 - 2003
Assistant Professor
Education:
Massachusetts Institute of Technology 1987 - 1994
Javed Aslam
Location:
Greater Boston Area
Industry:
Higher Education
Publications & IP owners
Us Patents
Vmm-Based Intrusion Detection System
US Patent:
2011000, Jan 6, 2011
Filed:
Feb 2, 2009
Appl. No.:
12/865795
Inventors:
Micha Moffie - Somerville MA, US
David Kaeli - Medway MA, US
Aviram Cohen - Lexington MA, US
Javed Aslam - Weston MA, US
Malak Alshawabkeh - Quincy MA, US
Jennifer Dy - Framingham MA, US
Fatemeh Azmandian - Taunton MA, US
David Kaeli - Medway MA, US
Aviram Cohen - Lexington MA, US
Javed Aslam - Weston MA, US
Malak Alshawabkeh - Quincy MA, US
Jennifer Dy - Framingham MA, US
Fatemeh Azmandian - Taunton MA, US
International Classification:
G06F 11/00
US Classification:
726 23, 718 1
Abstract:
An intrusion detection system collects architectural level events from a Virtual Machine Monitor where the collected events represent operation of a corresponding Virtual Machine. The events are consolidated into features that are compared with features from a known normal operating system. If an amount of any differences between the collected features and the normal features exceeds a threshold value, a compromised Virtual Machine may be indicated. The comparison thresholds are determined by training on normal and abnormal systems and analyzing the collected events with machine learning algorithms to arrive at a model of normal operation.
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