{"product_id":"cyber-security-and-adversarial-machine-learning-emerging-attacks-and-mitigation-strategies-9781799890638","title":"Cyber Security and Adversarial Machine Learning: Emerging Attacks and Mitigation Strategies","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book discusses deep learning vulnerabilities and cyber security, highlighting the need for robust DNN architectures and cryptographic key exchange methods in big data systems. It provides information on new threats and mitigation methods in these areas. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 300 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 30 November 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: IGI Global\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003cstrong\u003eIntroduction:\u003c\/strong\u003e\u003cbr\u003eThe field of cyber security has become increasingly important in recent years as the world becomes more connected through the internet and digital technologies. With the rise of big data, the amount of sensitive data being processed and stored has increased significantly, making it a prime target for cybercriminals. This book aims to provide an in-depth understanding of the latest threats and mitigation methods in the cyber security domain.\u003cbr\u003e\u003cstrong\u003eVulnerabilities in Deep Learning:\u003c\/strong\u003e\u003cbr\u003eDeep learning is a powerful machine learning algorithm that has revolutionized many industries, including image recognition, natural language processing, and autonomous vehicles. However, deep neural network architectures are considered to be robust to random perturbations. Nevertheless, it is shown that they could be severely vulnerable to slight but carefully crafted perturbations of the input, termed as adversarial samples. In recent years, numerous studies have been conducted in this new area called Adversarial Machine Learning to devise new adversarial attacks and to defend against these attacks with more robust DNN architectures.\u003cbr\u003e\u003cstrong\u003eProtection of Sensitive Data in Big Data Systems:\u003c\/strong\u003e\u003cbr\u003eThe protection and processing of sensitive data in big data systems is a common problem as the increase in data size increases the need for high processing power. Protection of the sensitive data on a system that contains multiple connections with different privacy policies also brings the need for proper cryptographic key exchange methods for each party, as extra work.\u003cbr\u003e\u003cstrong\u003eNew Threats in New Technologies:\u003c\/strong\u003e\u003cbr\u003eIn addition to the vulnerabilities in deep learning, there are new threats in new technologies such as vulnerabilities in artificial intelligence, data privacy problems with GDPR, and new solutions.\u003cbr\u003e\u003cstrong\u003eConclusion:\u003c\/strong\u003e\u003cbr\u003eThis book provides a comprehensive overview of the latest threats and mitigation methods in the cyber security domain. It is essential for anyone who is concerned about the security of their data and systems. By understanding the latest threats and mitigation methods, individuals and organizations can take steps to protect themselves from cybercriminals and ensure the security of their data.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781799890638\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Hardback","offer_id":44096547324154,"sku":"9781799890638","price":233.64,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_71230acf-9a2f-466d-9f57-42e59735b13f.jpg?v=1670691668","url":"https:\/\/shulphink.com\/products\/cyber-security-and-adversarial-machine-learning-emerging-attacks-and-mitigation-strategies-9781799890638","provider":"Shulph Ink","version":"1.0","type":"link"}