Handbook of Research on Machine and Deep Learning Applications for Cyber Security PDF Download
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Author: Ganapathi, Padmavathi
Publisher: IGI Global
ISBN: 1522596135
Category : Computers
Languages : en
Pages : 506
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Book Description
As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Author: Ganapathi, Padmavathi
Publisher: IGI Global
ISBN: 1522596135
Category : Computers
Languages : en
Pages : 506
Get Book Here
Book Description
As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Author: Wenke Lee
Publisher: Springer Science & Business Media
ISBN: 0387687688
Category : Computers
Languages : en
Pages : 178
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Book Description
Botnets have become the platform of choice for launching attacks and committing fraud on the Internet. A better understanding of Botnets will help to coordinate and develop new technologies to counter this serious security threat. Botnet Detection: Countering the Largest Security Threat consists of chapters contributed by world-class leaders in this field, from the June 2006 ARO workshop on Botnets. This edited volume represents the state-of-the-art in research on Botnets.
Author: Kwangjo Kim
Publisher: Springer
ISBN: 9811314446
Category : Computers
Languages : en
Pages : 92
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Book Description
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.
Author: Aboul-Ella Hassanien
Publisher: Springer Nature
ISBN: 3030442896
Category : Technology & Engineering
Languages : en
Pages : 880
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Book Description
This book presents the proceedings of the 1st International Conference on Artificial Intelligence and Computer Visions (AICV 2020), which took place in Cairo, Egypt, from April 8 to 10, 2020. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, intelligent systems and applications, and intelligent networks.
Author: Tony Thomas
Publisher: Springer Nature
ISBN: 9811517061
Category : Computers
Languages : en
Pages : 217
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Book Description
This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Author: Ali Dehghantanha
Publisher: Springer
ISBN: 3319739514
Category : Computers
Languages : en
Pages : 334
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Book Description
This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.
Author: D. Jude Hemanth
Publisher: Springer Nature
ISBN: 9811676100
Category : Technology & Engineering
Languages : en
Pages : 1042
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Book Description
This book gathers selected papers presented at the 5th International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI 2021), organized by JCT College of Engineering and Technology, Coimbatore, Tamil Nadu, India during 27 – 28 August 2021. This book solicits the innovative research ideas and solutions for almost all the intelligent data intensive theories and application domains. The general scope of this book covers the design, architecture, modeling, software, infrastructure and applications of intelligent communication architectures and systems for big data or data-intensive applications. In particular, this book reports the novel and recent research works on big data, mobile and wireless networks, artificial intelligence, machine learning, social network mining, intelligent computing technologies, image analysis, robotics and autonomous systems, data security and privacy.
Author: G. Ranganathan
Publisher: Springer Nature
ISBN: 9811653011
Category : Technology & Engineering
Languages : en
Pages : 944
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Book Description
This book features selected papers from the International Conference on Soft Computing for Security Applications (ICSCS 2021), held at Dhirajlal Gandhi College of Technology, Tamil Nadu, India, during June 2021. It covers recent advances in the field of soft computing techniques such as fuzzy logic, neural network, support vector machines, evolutionary computation, machine learning and probabilistic reasoning to solve various real-time challenges. The book presents innovative work by leading academics, researchers, and experts from industry.
Author: Piotr Gaj
Publisher: Springer
ISBN: 3030219526
Category : Computers
Languages : en
Pages : 429
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Book Description
This book constitutes the thoroughly refereed proceedings of the 26th International Conference on Computer Networks, CN 2019, held in Gliwice, Poland, in June 2019. The 29 full papers presented were carefully reviewed and selected from 64 submissions. They are organized in topical sections on computer networks; communications; and queueing theory and queuing networks.
Author: Pradeep Kumar Singh
Publisher: Springer Nature
ISBN: 3030305775
Category : Computers
Languages : en
Pages : 1164
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Book Description
This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data Mining and Internet of Things (IoT). It gathers papers presented at ICETIT 2019, the 1st International Conference on Emerging Trends in Information Technology, which was held in Delhi, India, in June 2019. This conference series represents a targeted response to the growing need for research that reports on and assesses the practical implications of IoT and network technologies, AI and machine learning, data analytics and cloud computing, security and privacy, and next generation computing technologies.
