Gary Warner

Birmingham, Alabama, United States Contact Info
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Experience & Education

  • DarkTower

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Licenses & Certifications

Publications

  • Tracking Criminals on Facebook: A Case Study from a Digital Forensics REU Program

    Presented at the 10th Annual ADFSL Conference on Digital Forensics, Security and Law

    See publication
  • Spam Campaign Cluster Detection using Redirected URLs and Randomized Sub-Domains

    SocialInformatics 2014

    A technique for detecting major spam campaigns based on UR:s present in the spam emails was proposed. The URLs that carried significance were the ones that redirected to another page and the ones having randomized sub-domains but common domain names.

    Other authors
  • CURLA: Cloud-Based Spam URL Analyzer for Very Large Datasets

    7th IEEE International Conference on Cloud Computing

    Other authors
  • UDaaS: A Cloud-based URL-Deduplication-as-a-Service for Big Datasets

    4th IEEE International Conference on Big Data and Cloud Computing (BDCloud)

    Other authors
  • Phish-Net: Investigating Phish Clusters Using Drop Email Addresses

    APWG eCrime Researchers Summit

  • Koobface, the Evolution of the Social Botnet

    IEEE

    A paper accepted at the Anti Phishing Working Group Ecrimes Researchers' Summit in Dallas Texas October, 2010. Paper was published and presented at this conference.

  • Lexical Feature Based Phishing URL Detection Using Online Learning

    AISec '10: Proceedings of the 3rd ACM workshop on Artificial intelligence and security

    This paper evaluated machine learning techniques to determine whether phishing URLs have distinguishing characteristics that, when taken as an ensemble, can identify likely phish solely based on the nature of their URL.

    Other authors
    • aaron blum
    • thamar solorio
  • An Empirical Analysis of Phishing Blacklists

    Sixth Conference on Email and Anti-Spam

    This paper demonstrated that newly identified phishing websites were very poorly detected by current anti-phishing toolbars. The findings differ from previous findings primarily because we detected the emerging phish so much earlier than previous researchers.

    Other authors
    See publication
  • Mining spam email to identify common origins for forensic application

    SAC '08 Proceedings of the 2008 ACM symposium on Applied computing

    This paper was the first publication of how the UAB Spam Data Mine extracts metadata about spam messages and uses that information to create clusters based on an agglomerative hierarchical clustering algorithm.

    Other authors
    See publication

Patents

  • System and method for conducting a non-exact matching analysis on a phishing website

    Issued US 8495735

    A system and method for enhancing spam avoidance efficiency by automatically identifying a phishing website without human intervention. The system receives a stream of suspect Internet urls for potential phishing websites and uses a comparison strategy to determine whether the potential phishing website has already be labeled as a bonefid phishing website. A comparison system is utilized in which similarity data is calculated on various elements of the potential phishing website and then…

    A system and method for enhancing spam avoidance efficiency by automatically identifying a phishing website without human intervention. The system receives a stream of suspect Internet urls for potential phishing websites and uses a comparison strategy to determine whether the potential phishing website has already be labeled as a bonefid phishing website. A comparison system is utilized in which similarity data is calculated on various elements of the potential phishing website and then compared to similarity data of known phishing websites. Various types of similarity measure methodologies are potentially incorporated and a similarity threshold value can be varied in order to respond to phishing threats.

    Other inventors
    See patent
  • System and method for identifying a phishing website

    Issued US 8468597

    A system and method for enhancing spam avoidance efficiency by automatically identifying a phishing website without human intervention. The system receives a stream of suspect Internet urls for potential phishing websites and uses a comparison strategy to determine whether the potential phishing website has already be labeled as a bonefid phishing website. A comparison system is utilized in which similarity data is calculated on various elements of the potential phishing website and then…

    A system and method for enhancing spam avoidance efficiency by automatically identifying a phishing website without human intervention. The system receives a stream of suspect Internet urls for potential phishing websites and uses a comparison strategy to determine whether the potential phishing website has already be labeled as a bonefid phishing website. A comparison system is utilized in which similarity data is calculated on various elements of the potential phishing website and then compared to similarity data of known phishing websites. Various types of categorization structures and notification strategies are utilized in the system.

    Other inventors
    See patent
  • System and method for branding a phishing website using advanced pattern matching

    Issued US 8381292

    A system and method for enhancing spam avoidance efficiency and brand protection by automatically identifying a phishing website without human intervention. The system receives a stream of suspect Internet urls for potential phishing websites and uses a comparison strategy to determine whether the potential phishing website has already be labeled as a bonefid phishing website. A comparison system is utilized in which similarity data is calculated on various elements of the potential phishing…

    A system and method for enhancing spam avoidance efficiency and brand protection by automatically identifying a phishing website without human intervention. The system receives a stream of suspect Internet urls for potential phishing websites and uses a comparison strategy to determine whether the potential phishing website has already be labeled as a bonefid phishing website. A comparison system is utilized in which similarity data is calculated on various elements of the potential phishing website and then compared to similarity data of known phishing websites and known brands to determine whether the site needs human intervention. Various types of categorization structures and notification strategies are utilized in the system, including the adjustment of threshold comparison values in response to the identification of a potential phishing site displaying a brand of interest.

    Other inventors
    See patent

Courses

  • Computer Forensics

    JS402 / JS502

  • Computer Security

    CS436

  • Digital Media Forensics

    CJ437/CJ537

  • Investigating Malicious Attacks

    CJ-438/538

  • Investigating Online Crime

    CS/JS437

  • Malware Analysis

    CJ 407

  • Terrorism and Intelligence

    JS340

Organizations

  • Anti-Phishing Working Group

    -

    - Present
  • Birmingham InfraGard

    -

    - Present

    The Birmingham InfraGard chapter held its first meeting in my auditorium at Energen Headquarters on September 6, 2001. We still meet monthly. For details, see: http://www.birmingham-infragard.org

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