{"product_id":"machine-learning-for-cyber-security-4th-international-conference-ml4cs-2022-guangzhou-china-december-24-2022-proceedings-part-ii-9783031200984","title":"Machine Learning for Cyber Security: 4th International Conference, ML4CS 2022, Guangzhou, China, December 2-4, 2022, Proceedings, Part II","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, held in Guangzhou, China, had 100 full papers and 46 short papers accepted for publication in the three-volume LNCS 13655, 13656, and 13657 proceedings. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 625 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 13 January 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe three-volume proceedings set LNCS 13655, 13656, and 13657 constitutes the refereed proceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which took place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers included in these proceedings were carefully reviewed and selected from 367 submissions.\u003cbr\u003e\u003cbr\u003eThe 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, was held in Guangzhou, China, from December 2 to 4, 2022. This conference brought together experts from around the world to discuss the latest advancements in machine learning and cyber security.\u003cbr\u003e\u003cbr\u003eThe proceedings of the conference were published in three volumes, LNCS 13655, 13656, and 13657. These proceedings included a total of 100 full papers and 46 short papers, which were carefully reviewed and selected from 367 submissions.\u003cbr\u003e\u003cbr\u003eThe papers covered a wide range of topics, including but not limited to:\u003cbr\u003e\u003cbr\u003eMachine learning algorithms for cyber security\u003cbr\u003e\u003cbr\u003eCyber threat detection and classification\u003cbr\u003e\u003cbr\u003eCyber security risk assessment\u003cbr\u003e\u003cbr\u003eCyber security policy and regulation\u003cbr\u003e\u003cbr\u003eThe papers presented at ML4CS 2022 showcased the latest research and developments in the field of machine learning for cyber security. The conference provided a platform for researchers, practitioners, and industry professionals to exchange ideas, share experiences, and collaborate on finding solutions to the challenges facing the cyber security industry.\u003cbr\u003e\u003cbr\u003eThe conference also featured several keynote speeches and panel discussions, which provided insights into the current state of cyber security and the future of machine learning in this field. The speakers included renowned experts from academia, industry, and government organizations.\u003cbr\u003e\u003cbr\u003eOverall, ML4CS 2022 was a successful event that contributed to the advancement of machine learning for cyber security. The proceedings of the conference will provide valuable insights and resources for researchers, practitioners, and industry professionals working in this field.\u003cbr\u003e\u003cbr\u003eThe 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, was held in Guangzhou, China, from December 2 to 4, 2022. This conference brought together experts from around the world to discuss the latest advancements in machine learning and cyber security.\u003cbr\u003e\u003cbr\u003eThe proceedings of the conference were published in three volumes, LNCS 13655, 13656, and 13657. These proceedings included a total of 100 full papers and 46 short papers, which were carefully reviewed and selected from 367 submissions.\u003cbr\u003e\u003cbr\u003eThe papers covered a wide range of topics, including but not limited to:\u003cbr\u003e\u003cbr\u003eMachine learning algorithms for cyber security\u003cbr\u003e\u003cbr\u003eCyber threat detection and classification\u003cbr\u003e\u003cbr\u003eCyber security risk assessment\u003cbr\u003e\u003cbr\u003eCyber security policy and regulation\u003cbr\u003e\u003cbr\u003eThe papers presented at ML4CS 2022 showcased the latest research and developments in the field of machine learning for cyber security. The conference provided a platform for researchers, practitioners, and industry professionals to exchange ideas, share experiences, and collaborate on finding solutions to the challenges facing the cyber security industry.\u003cbr\u003e\u003cbr\u003eThe conference also featured several keynote speeches and panel discussions, which provided insights into the current state of cyber security and the future of machine learning in this field. The speakers included renowned experts from academia, industry, and government organizations.\u003cbr\u003e\u003cbr\u003eOverall, ML4CS 2022 was a successful event that contributed to the advancement of machine learning for cyber security. The proceedings of the conference will provide valuable insights and resources for researchers, practitioners, and industry professionals working in this field.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 972g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 236 x 159 x 35 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031200984\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2023\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44302292975866,"sku":"9783031200984","price":76.85,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_30d58e4d-d2ba-4d83-ac59-e6b9f676ae9a.jpg?v=1687924330","url":"https:\/\/shulphink.com\/products\/machine-learning-for-cyber-security-4th-international-conference-ml4cs-2022-guangzhou-china-december-24-2022-proceedings-part-ii-9783031200984","provider":"Shulph Ink","version":"1.0","type":"link"}