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    1. Data och IT
    2. Nätverk och kommunikation

    Hands-On Machine Learning for Cybersecurity

    Safeguard your system by making your machines intelligent using the Python ecosystem

    AvSoma Halder,Sinan Ozdemir

    Häftad, Engelska, 2018

    649 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Get into the world of smart data security using machine learning algorithms and Python librariesKey FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook DescriptionCyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain.The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not.Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systemsWhat you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is forThis book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

    Produktinformation

    • Utgivningsdatum:2018-12-31
    • Mått:191 x 235 x 18 mm
    • Vikt:597 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:318
    • Förlag:Packt Publishing Limited
    • ISBN:9781788992282

    Utforska kategorier

    • Nätverk och kommunikation inom Data och IT
    • Artificiell intelligens inom Data och IT
    • IT-säkerhet inom Data och IT

    Mer om författaren

    Soma Halder is the data science lead of the big data analytics group at Reliance Jio Infocomm Ltd, one of India's largest telecom companies. She specializes in analytics, big data, cybersecurity, and machine learning. She has approximately 10 years of machine learning experience, especially in the field of cybersecurity. She studied at the University of Alabama, Birmingham where she did her master's with an emphasis on Knowledge discovery and Data Mining and computer forensics. She has worked for Visa, Salesforce, and AT&T. She has also worked for start-ups, both in India and the US (E8 Security, Headway ai, and Norah ai). She has several conference publications to her name in the field of cybersecurity, machine learning, and deep learning. Sinan is an active lecturer focusing on large language models and a former lecturer of data science at the Johns Hopkins University. He is the author of multiple textbooks on data science and machine learning including "Quick Start Guide to LLMs". Sinan is currently the founder of LoopGenius which uses AI to help people and businesses boost their sales and was previously the founder of the acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. He holds a Master's Degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco.

    Innehållsförteckning

    • Table of ContentsBasics of Machine Learning in Cyber Security Time series analysis and Ensemble modellingSegregating legitimate and lousy URLsKnocking down captchasUsing Data Science to catch email frauds and spamsEfficient Network Anomaly detection using K Means Decision Tree and context based malicious event detectionCatching impersonators and hackers red handedChange the game with TensorflowFinancial frauds and how deep learning can mitigate themPractical Case Studies in Cyber Security