skip to main content
DOE Patents title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Non-harmful insertion of data mimicking computer network attacks

Abstract

Non-harmful data mimicking computer network attacks may be inserted in a computer network. Anomalous real network connections may be generated between a plurality of computing systems in the network. Data mimicking an attack may also be generated. The generated data may be transmitted between the plurality of computing systems using the real network connections and measured to determine whether an attack is detected.

Inventors:
; ;
Issue Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1257984
Patent Number(s):
9,374,380
Application Number:
13/826,736
Assignee:
Los Alamos National Security, LLC (Los Alamos, NM)
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Mar 14
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Neil, Joshua Charles, Kent, Alexander, and Hash, Jr, Curtis Lee. Non-harmful insertion of data mimicking computer network attacks. United States: N. p., 2016. Web.
Neil, Joshua Charles, Kent, Alexander, & Hash, Jr, Curtis Lee. Non-harmful insertion of data mimicking computer network attacks. United States.
Neil, Joshua Charles, Kent, Alexander, and Hash, Jr, Curtis Lee. Tue . "Non-harmful insertion of data mimicking computer network attacks". United States. https://www.osti.gov/servlets/purl/1257984.
@article{osti_1257984,
title = {Non-harmful insertion of data mimicking computer network attacks},
author = {Neil, Joshua Charles and Kent, Alexander and Hash, Jr, Curtis Lee},
abstractNote = {Non-harmful data mimicking computer network attacks may be inserted in a computer network. Anomalous real network connections may be generated between a plurality of computing systems in the network. Data mimicking an attack may also be generated. The generated data may be transmitted between the plurality of computing systems using the real network connections and measured to determine whether an attack is detected.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {6}
}

Patent:

Save / Share:

Works referenced in this record:

The link-prediction problem for social networks
journal, January 2007

  • Liben-Nowell, David; Kleinberg, Jon
  • Journal of the American Society for Information Science and Technology, Vol. 58, Issue 7, p. 1019-1031
  • DOI: 10.1002/asi.20591

A survey of coordinated attacks and collaborative intrusion detection
journal, February 2010

  • Zhou, Chenfeng Vincent; Leckie, Christopher; Karunasekera, Shanika
  • Computers & Security, Vol. 29, Issue 1, p. 124-140
  • DOI: 10.1016/j.cose.2009.06.008

Alert correlation in a cooperative intrusion detection framework
conference, January 2002


Identifying botnets by capturing group activities in DNS traffic
journal, January 2012


Probabilistic Alert Correlation
book, January 2001

  • Valdes, Alfonso; Skinner, Keith; Goos, Gerhard
  • Recent Advances in Intrusion Detection, p. 54-68
  • DOI: 10.1007/3-540-45474-8_4

Scan Statistics for the Online Detection of Locally Anomalous Subgraphs
journal, August 2013


Two-tier data-driven intrusion detection for automatic generation control in smart grid
conference, December 2014

  • Ali, Muhammad Qasim; Yousefian, Reza; Al-Shaer, Ehab
  • 2014 IEEE Conference on Communications and Network Security, p. 292-300
  • DOI: 10.1109/CNS.2014.6997497