The non-technical handbook for cyber security risk management Solving Cyber Risk distills a decade of research into a practical framework for cyber security. Blending statistical data and cost information with research into the culture, psychology, and business models of the hacker community, this book provides business executives, policy-makers, and individuals with a deeper understanding of existing future threats, and an action plan for safeguarding their organizations. Key Risk Indicators reveal vulnerabilities based on organization type, IT infrastructure and existing security measures, while expert discussion from leading cyber risk specialists details practical, real-world methods of risk reduction and mitigation. By the nature of the business, your organization’s customer database is packed with highly sensitive information that is essentially hacker-bait, and even a minor flaw in security protocol could spell disaster. This book takes you deep into the cyber threat landscape to show you how to keep your data secure. Understand who is carrying out cyber-attacks, and why Identify your organization’s risk of attack and vulnerability to damage Learn the most cost-effective risk reduction measures Adopt a new cyber risk assessment and quantification framework based on techniques used by the insurance industry By applying risk management principles to cyber security, non-technical leadership gains a greater understanding of the types of threat, level of threat, and level of investment needed to fortify the organization against attack. Just because you have not been hit does not mean your data is safe, and hackers rely on their targets’ complacence to help maximize their haul. Solving Cyber Risk gives you a concrete action plan for implementing top-notch preventative measures before you’re forced to implement damage control.

To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information, and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master degree students and PhD researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those to cyber risk management datasets. It will also leverage real-world financial instances to practise business product modelling and data analysis. The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, and reduce data breaches and cyber-attack vulnerabilities.

This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity. The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.

With our ever-increasing reliance on computer technology in every field of modern life, the need for continuously evolving and improving cyber security remains a constant imperative. This book presents the 3 keynote speeches and 10 papers delivered at the 2nd Singapore Cyber Security R&D Conference (SG-CRC 2017), held in Singapore, on 21-22 February 2017. SG-CRC 2017 focuses on the latest research into the techniques and methodologies of cyber security. The goal is to construct systems which are resistant to cyber-attack, enabling the construction of safe execution environments and improving the security of both hardware and software by means of mathematical tools and engineering approaches for the design, verification and monitoring of cyber-physical systems. Covering subjects which range from messaging in the public cloud and the use of scholarly digital libraries as a platform for malware distribution, to low-dimensional bigram analysis for mobile data fragment classification, this book will be of interest to all those whose business it is to improve cyber security.

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques. This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals. Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.

This is THE book for every serious researcher in theoretical computer science. The book exposes critical detail in problem solving and researching in the fields of algorithms and complexity that no other book has ever done. It reveals the secrets of doing research and the way of thinking that are so natural to the world’s top computer scientists. Such skills and thinking are so “second nature” to every top computer scientist that they are not even mentioned or talked about. This book is thus for everyone who seriously wants to become an excellent researcher but may not have such skills and thinking.

UPSC Mains Solved Previous Papers – General Studies Paper 3 (2013 Onwards)

1. The book is designed for preparation of civil services exams 2. It is divided into 4 papers and segmented into topics. 3. Last 5 Years solved papers are given to understand the changing paper. 4. Chapterwise Questions are provided from 2020 to 1997 for practice. 5. Solved Papers 2020-2017 are given for practice. Candidates, who are appearing in IAS Main Exams, are always in need of comprehensive and accurate study material which could actually serve the purpose for the smart and cumulative understanding of the subject. General Studies is a very dynamic topic which requires in depth analysis and vast knowledge. With the current edition of "IAS Mains General Studies Chapterwise Solved Papers 2020-1997" candidates are guided with the authentic source of information following the current paper pattern. The book is divided into 4 Parts providing complete practice of each paper. Every chapter is loaded with good number of questions from 1997 to 2020 along with detailed solutions. Solved Papers (2020-2017) are provided to get the better insight of the question papers and its pattern. TOC Solved Paper 2020-2017 (Paper - I, II, III, IV), Paper I – Indian Heritage and Culture, History and Geography of the World and Society, Paper II – Governance, Constitution, Polity, Social Justice and International Relations, Paper III – Technology, Economic Development, Biodiversity, Environment, Security and Disaster Management, Paper IV – Ethics, Integrity and Aptitude.

This book provides the latest research findings, and discusses, from both theoretical and practical perspectives, innovative research methods and development techniques related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems and secure intelligent cloud systems. It also presents the synergies among various paradigms in such a multi-disciplinary field of intelligent collaborative systems. With the rapid development of the Internet, we are experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm, which locates people at the very centre of networks and exploits the value of individuals’ connections, relations and collaboration. Social networks are also playing a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems. Virtual campuses, virtual communities and organizations strongly leverage intelligent networking and collaborative systems by means of a great variety of formal and informal electronic relations, such as business-to-business, peer-to-peer and various types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and autonomously. In addition, the latest, powerful technologies based on grid and wireless infrastructure as well as cloud computing are currently enhancing collaborative and networking applications significantly, but are also facing new issues and challenges. The principal purpose of the research and development community is to stimulate research that will lead to the creation of responsive environments for networking and, in the longer term, the development of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning.