Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Deep Learning in Textual Low-Data Regimes for Cybersecurity

Deep Learning in Textual Low-Data Regimes for Cybersecurity

Bayer, Markus

Paperback

Series: Technology, Peace and Security I Technologie, Frieden Und Sicherheit

Technology & EngineeringGeneral MathematicsProbability & Statistics

ISBN10: 3658487771
ISBN13: 9783658487775
Publisher: Springer Vieweg
Published: Aug 21 2025
Pages: 347
Weight: 0.99
Height: 0.84 Width: 5.83 Depth: 8.27
Language: English
In today's fast-paced cybersecurity landscape, professionals are increasingly challenged by the vast volumes of cyber threat data, making it difficult to identify and mitigate threats effectively. Traditional clustering methods help in broadly categorizing threats but fall short when it comes to the fine-grained analysis necessary for precise threat management. Supervised machine learning offers a potential solution, but the rapidly changing nature of cyber threats renders static models ineffective and the creation of new models too labor-intensive. This book addresses these challenges by introducing innovative low-data regime methods that enhance the machine learning process with minimal labeled data. The proposed approach spans four key stages:

Data Acquisition: Leveraging active learning with advanced models like GPT-4 to optimize data labeling.

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