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Applied math for security : a Pythonic introduction to graph theory and computational geometry /

"A math-based guide for information security practitioners. Teaches how to use concepts from various fields of mathematics, such as graph theory, computational geometry, and statistics, to create and implement ready-to-use security tools. Features code examples in Python and hands-on proof-of-c...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Reilly, Daniel (Security researcher) (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: San Francisco : No Starch Press, 2023.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |a Applied math for security :  |b a Pythonic introduction to graph theory and computational geometry /  |c Daniel Reilly. 
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264 1 |a San Francisco :  |b No Starch Press,  |c 2023. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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504 |a Includes bibliographical references and index. 
505 0 |a Setting up the environment -- Programming and math conventions -- Network and graph theory -- Creating a network graph from packets -- Analyzing social networks derived from Tweets -- Analyzing social network evolution with Monte Carlo simulations -- Computational geometry theory -- Triangulating locations from OpenCell data -- Emergency service planning with Voronoi diagrams -- Computational geometry for facial recognition -- Understanding the art gallery problem -- Going beyond the proof of concept -- Delivering Python applications. 
520 |a "A math-based guide for information security practitioners. Teaches how to use concepts from various fields of mathematics, such as graph theory, computational geometry, and statistics, to create and implement ready-to-use security tools. Features code examples in Python and hands-on proof-of-concept projects for solving real-world problems"--  |c Provided by publisher. 
588 |a Description based on print version record and CIP data provided by publisher; resource not viewed. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Data protection  |x Mathematics. 
650 0 |a Data protection  |x Mathematical models. 
650 7 |a Data protection  |x Mathematics.  |2 fast  |0 (OCoLC)fst00887969 
776 0 8 |i Print version:  |a Reilly, Daniel  |t Applied math for security  |d San Francisco : No Starch Press, 2023  |z 9781718502567  |w (DLC) 2023002853 
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