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Developing secure software requires the integration of numerous methods and tools into the development process, and software design is based on shared expert knowledge, claims, and opinions. Empirical methods, including data analytics, allow extracting knowledge and insights from the data that organizations collect from their processes and tools, and from the opinions of the experts who practice these processes and methods. This book introduces the reader to the fundamentals of empirical research methods, and demonstrates how these methods can be used to hone a secure software development lifecycle based on empirical data and published best practices.
This book highlights advances in Cyber Security, Cyber Situational Awareness (CyberSA), Artificial Intelligence (AI) and Social Media. It brings together original discussions, ideas, concepts and outcomes from research and innovation from multidisciplinary experts. It offers topical, timely and emerging original innovations and research results in cyber situational awareness, security analytics, cyber physical systems, blockchain technologies, machine learning, social media and wearables, protection of online digital service, cyber incident response, containment, control, and countermeasures (CIRC3). The theme of Cyber Science 2022 is Ethical and Responsible use of AI. Includes original contributions advancing research in Artificial Intelligence, Machine Learning, Blockchain, Cyber Security, Social Media, Cyber Incident Response & Cyber Insurance. The Chapters "Municipal Cybersecurity - A Neglected Research Area? A Survey of Current Research, The Transnational Dimension of Cyber Security: The NIS Directive and its Jurisdictional Challenges, Refining the Mandatory Cybersecurity Incident Reporting under the NIS Directive 2.0: Event Types and Reporting Processes" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
This volume contains the proceedings of CloudCom 2009, the First Inter- tional Conference on Cloud Computing. The conference was held in Beijing, China, during December 1-4, 2009, and was the ?rst in a series initiated by the Cloud Computing Association (www.cloudcom.org). The Cloud Computing Association was founded in 2009 by Chunming Rong, Martin Gilje Jaatun, and Frode Eika Sandnes. This ?rst conference was organized by the Beijing Ji- tong University, Chinese Institute of Electronics, and Wuhan University, and co-organized by Huazhong University of Science and Technology, South China Normal University, and Sun Yat-sen University. Ever since the inception of the Internet, a "Cloud" has been used as a metaphor for a network-accessible infrastructure (e.g., data storage, computing hardware, or entire networks) which is hidden from users. To some, the concept of cloud computing may seem like a throwback to the days of big mainframe computers, but we believe that cloud computing makes data truly mobile, - lowing a user to access services anywhere, anytime, with any Internet browser. In cloud computing, IT-related capabilities are provided as services, accessible without requiring control of, or even knowledge of, the underlying technology. Cloud computing provides dynamic scalability of services and computing power, and although many mature technologies are used as components in cloud c- puting, there are still many unresolved and open problems.
ThisvolumecontainstheproceedingsofATC2008, the5thInternationalConf- ence on Autonomic and Trusted Computing: Bringing Safe, Self-x and Organic Computing Systems into Reality. The conference was held in Oslo, Norway, d- ing June 23-25, 2008. ATC 2008 is a successor of the First IFIP Workshop on Trusted and Au- nomic Ubiquitous and Embedded Systems (TAUES 2005, Japan), the Inter- tional Workshop on Trusted and Autonomic Computing Systems (TACS 2006, Austria), the Third International Conference on Autonomic and Trusted C- puting (ATC 2006, China), and the 4th International Conference on Autonomic and Trusted Computing (ATC 2007, Hong Kong). Computing systems including hardware, software, communication and n- worksaregrowingdramaticallyinbothscale andheterogeneity, becoming overly complex. Such complexity is getting even more critical with the ubiquitous p- meation of embedded devices and other pervasive systems. To cope with the growingandubiquitous complexity, Autonomic Computing(AC)focuses onse- manageable computing and communication systems that exhibit self-awareness, self-con?guration, self-optimization, self-healing, self-protection and other self-x operationsto the maximumextent possible without humaninterventionorgu- ance. Organic Computing (OC) additionally emphasizes natural-analogue c- cepts like self-organization and controlled emergence. Any autonomic or organic system must be trustworthy to avoid the risk of losingcontrolandto retaincon?dencethatthe systemwillnotfail.Trustand/or distrust relationships in the Internet and in pervasive infrastructures are key factorsinenablingdynamicinteractionandcooperationofvarioususers, systems and services. Trusted/Trustworthy Computing (TC) aims at making computing and communication systems as well as services available, predictable, traceable, controllable, assessable, sustainable, dependable, persistable, security/privacy protectable,
Developing secure software requires the integration of numerous methods and tools into the development process, and software design is based on shared expert knowledge, claims, and opinions. Empirical methods, including data analytics, allow extracting knowledge and insights from the data that organizations collect from their processes and tools, and from the opinions of the experts who practice these processes and methods. This book introduces the reader to the fundamentals of empirical research methods, and demonstrates how these methods can be used to hone a secure software development lifecycle based on empirical data and published best practices.
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