Detecting The Unknown
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Pattern Recognition
Author: Apostolos Antonacopoulos
language: en
Publisher: Springer Nature
Release Date: 2024-11-29
The multi-volume set of LNCS books with volume numbers 15301-15333 constitutes the refereed proceedings of the 27th International Conference on Pattern Recognition, ICPR 2024, held in Kolkata, India, during December 1–5, 2024. The 963 papers presented in these proceedings were carefully reviewed and selected from a total of 2106 submissions. They deal with topics such as Pattern Recognition; Artificial Intelligence; Machine Learning; Computer Vision; Robot Vision; Machine Vision; Image Processing; Speech Processing; Signal Processing; Video Processing; Biometrics; Human-Computer Interaction (HCI); Document Analysis; Document Recognition; Biomedical Imaging; Bioinformatics.
Predicting the Unknown: Machine Learning for Zero-Day Vulnerability Detection – A Data-Driven Approach to Securing the Future
Author: Hariprasad Sivaraman
language: en
Publisher: Libertatem Media Private Limited
Release Date: 2022-07-15
Zero-day vulnerabilities pose one of the most pressing cybersecurity threats, allowing attackers to exploit software flaws before security teams can respond. Predicting the Unknown: Machine Learning for Zero- Day Vulnerability Detection presents a cutting-edge approach to combating these threats using AI-driven techniques, empowering security professionals with proactive defense strategies. This book explores the limitations of traditional security models—such as signature-based and heuristic detection—and highlights how machine learning (ML) is transforming zero-day threat detection. Readers will discover how ML models, including anomaly detection, supervised and unsupervised learning, and reinforcement learning, can analyze vast datasets of network traffic and system logs to identify emerging vulnerabilities before they are exploited. From feature engineering and real-time anomaly detection to adversarial machine learning and evasion tactics, Predicting the Unknown delves into the core components of AI-powered cybersecurity. The book also examines advanced ML techniques like deep learning and reinforcement learning, showcasing their role in dynamic threat mitigation. Packed with case studies, technical insights, and future trends—including the integration of quantum computing and explainable AI—this book provides a comprehensive roadmap for security professionals, data scientists, and researchers. Whether you're looking to strengthen enterprise defenses or pioneer nextgeneration cybersecurity solutions, Predicting the Unknown equips you with the tools to stay ahead of evolving cyber threats.
Emergency Characterization of Unknown Materials
Emergency Characterization of Unknown Materials, Second Edition is fully updated to serve as a portable reference that can be used in the field and laboratory by workers who are responsible for a safe response to and management of unknown hazardous materials. As with the first edition, the book emphasizes public safety and the management of life safety hazards, including strategies and emerging technologies to identify the hazards presented by an unknown material. When responding to a hazardous material emergency involving an unknown substance, firefighters and HAZMAT teams are primarily interested in protecting public safety. The book details risk analysis procedures to identify threats and vulnerabilities, analyzing them to determine how such risks can be eliminated or reduced. If an unknown material can be identified with a high degree of confidence, that can considerably change the response, and measures to be taken. In addition, the book covers practical field applications with updated and additional examples of field instruments. The hazard identification methods presented are intended for use by frontline workers. The test methods presented involve manipulation of small sample amounts – using, literally, a hands-on approach. The three technologies used by first responders and military personnel to identify unknown chemicals, Raman spectroscopy, FTIR spectroscopy and high-pressure mass spectroscopy, are covered in depth. Features Presents how to identify unknown materials and, if identification is not possible, to characterize the hazards of the material Offers practical examples to introduce new first responders to hazardous materials response Provides up-to-date field applications of the latest developments in commercially available instrumentation Details practical sample manipulations to help the reader successfully identify materials with popular high-end instrumentation Includes several examples of spectra and describes ways in which the reader can utilize data to inform decision making New coverage to this edition includes a chapter and content that focuses on sample manipulation and separations using instruments developed and revised since the first edition was published. These sample manipulations may be performed in the field with a very simple toolkit, which is fully outlined and explained in detail. Identifying the hazards of the unknown substance is essential to plan for response, contingencies and sustained actions. As such, Emergency Characterization of Unknown Materials, Second Edition will be a welcome and essential resource to all response and safety professionals concerned with hazardous materials.