{"product_id":"explainable-artificial-intelligence-for-cyber-security-next-generation-artificial-intelligence-9783030966294","title":"Explainable Artificial Intelligence for Cyber Security: Next Generation Artificial Intelligence","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eExplainable artificial intelligence (XAI) is essential for understanding and interpreting complex AI algorithms, particularly in cyber security where traditional algorithms may be unable to address zero-day attacks. This book serves as a valuable resource for professionals working in both fields. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 280 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 19 April 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Nature Switzerland AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eExplainable Artificial Intelligence (XAI) is poised to revolutionize the field of artificial intelligence, offering a transformative approach to understanding and interpreting complex algorithms. In recent years, AI has become an integral part of our daily lives, solving a wide range of problems, including cyber security. However, traditional AI algorithms are not equipped to handle the growing threat of zero-day cyber attacks. This book serves as a valuable resource for professionals working in cyber security and artificial intelligence, providing insights into the latest developments and techniques in XAI.\u003cbr\u003e\u003cbr\u003eThe traditional black box nature of AI algorithms has limited their ability to be understood and interpreted by humans. XAI aims to bridge this gap by providing explanations and insights into the decision-making processes of AI systems. This involves developing methods and tools that can generate human-readable explanations for AI decisions, enabling users to trust and validate the output of AI systems.\u003cbr\u003e\u003cbr\u003eOne of the key challenges in XAI is the complexity of AI algorithms and the vast amount of data they require to operate effectively. XAI techniques such as feature visualization, decision trees, and explainable neural networks can help to simplify the understanding of AI algorithms and make them more accessible to a wider audience.\u003cbr\u003e\u003cbr\u003eIn the field of cyber security, XAI has the potential to play a critical role in detecting and responding to cyber threats. By analyzing large amounts of data and identifying patterns and anomalies, XAI algorithms can help security professionals identify potential threats and take proactive measures to mitigate them.\u003cbr\u003e\u003cbr\u003eFor example, XAI algorithms can be used to analyze network traffic and identify suspicious activity, such as the use of malware or the infiltration of a network by an attacker. XAI algorithms can also be used to analyze user behavior and identify patterns that may indicate a potential security breach, such as the reuse of passwords or the use of vulnerable software.\u003cbr\u003e\u003cbr\u003eIn addition to its applications in cyber security, XAI has the potential to transform a wide range of industries, including healthcare, finance, and transportation. By providing insights into the decision-making processes of AI systems, XAI can help businesses make more informed decisions and improve their operations.\u003cbr\u003e\u003cbr\u003eHowever, there are also challenges associated with the development and deployment of XAI. One of the biggest challenges is the lack of standardized approaches and frameworks for XAI. This can make it difficult for researchers and practitioners to collaborate and share their expertise.\u003cbr\u003e\u003cbr\u003eTo address these challenges, there is a growing need for interdisciplinary collaboration and the development of open-source tools and datasets. This will enable researchers and practitioners to work together to develop and improve XAI techniques and make them more accessible to a wider audience.\u003cbr\u003e\u003cbr\u003eIn conclusion, explainable artificial intelligence (XAI) is a rapidly evolving field that has the potential to revolutionize the way we understand and interpret complex algorithms. XAI offers a transformative approach to cyber security, enabling security professionals to trust and validate the output of AI systems. By providing explanations and insights into the decision-making processes of AI systems, XAI can help detect and respond to cyber threats, and transform a wide range of industries. However, there are also challenges associated with the development and deployment of XAI, and there is a growing need for interdisciplinary collaboration and the development of open-source tools and datasets to address these challenges. As the field of XAI continues to evolve, it will be important to stay informed and up-to-date with the latest developments and techniques to capitalize on the potential benefits of this exciting technology.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 606g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783030966294\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Hardback","offer_id":44102971654394,"sku":"9783030966294","price":119.55,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1662154592628_book.jpg?v=1662312775","url":"https:\/\/shulphink.com\/products\/explainable-artificial-intelligence-for-cyber-security-next-generation-artificial-intelligence-9783030966294","provider":"Shulph Ink","version":"1.0","type":"link"}