Download Free Detection And Mitigation Of Insider Attacks In A Cloud Infrastructure Emerging Research And Opportunities Book in PDF and EPUB Free Download. You can read online Detection And Mitigation Of Insider Attacks In A Cloud Infrastructure Emerging Research And Opportunities and write the review.

Businesses constantly face online hacking threats or security breaches in their online mainframe that expose sensitive information to the wrong audience. Companies look to store their data in a separate location, distancing the availability of the information and reducing the risk of data breaches. Modern organizations need to remain vigilant against insider attacks, cloud computing risks, and security flaws within their mainframe. Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities is an essential reference source that discusses maintaining a secure management of sensitive data, and intellectual property and provides a robust security algorithm on consumer data. Featuring research on topics such as public cryptography, security principles, and trustworthy computing, this book is ideally designed for IT professionals, business managers, researchers, students, and professionals seeking coverage on preventing and detecting the insider attacks using trusted cloud computing techniques.
In today’s modern age of information, new technologies are quickly emerging and being deployed into the field of information technology. Cloud computing is a tool that has proven to be a versatile piece of software within IT. Unfortunately, the high usage of Cloud has raised many concerns related to privacy, security, and data protection that have prevented cloud computing solutions from becoming the prevalent alternative for mission critical systems. Up-to-date research and current techniques are needed to help solve these vulnerabilities in cloud computing. Modern Principles, Practices, and Algorithms for Cloud Security is a pivotal reference source that provides vital research on the application of privacy and security in cloud computing. While highlighting topics such as chaos theory, soft computing, and cloud forensics, this publication explores present techniques and methodologies, as well as current trends in cloud protection. This book is ideally designed for IT specialists, scientists, software developers, security analysts, computer engineers, academicians, researchers, and students seeking current research on the defense of cloud services.
Infrastructure development presents significant challenges for both developing and developed countries, hindering their progress in achieving the Sustainable Development Goals (SDGs). Governments often struggle to effectively leverage the necessary resources and expertise for financing and managing infrastructure projects, resulting in untapped potential for sustainable and inclusive development. Achieving the Sustainable Development Goals Through Infrastructure Development, edited by Cristina Raluca Gh. Popescu, Poshan Yu, and Yue Wei, offers a comprehensive guide to address these challenges. Focusing on public-private partnerships (PPPs) as a transformative solution, the book equips policymakers, investors, practitioners, and researchers with the essential knowledge and tools needed to navigate the complexities of infrastructure development and leverage the expertise and resources of the private sector. By showcasing successful case studies, analyzing critical success factors, and providing valuable insights into the implementation of PPPs in both developing and developed countries, this book becomes an indispensable resource for driving progress towards the SDGs. Covering crucial topics such as financing, risk management, legal frameworks, and sustainability considerations, it empowers readers to make informed decisions and foster collaborative partnerships between the public and private sectors. Through its comprehensive roadmap, this book enables stakeholders to unlock the full potential of sustainable and inclusive infrastructure development, paving the way for a prosperous future for all.
In the last few decades, the use of the Internet has grown tremendously, and the use of online communications has grown even more. The lack of security in private messages between individuals, however, allows hackers to collect loads of sensitive information. Modern security measures are required to prevent this attack on the world’s communication technologies. Advanced Digital Image Steganography Using LSB, PVD, and EMD: Emerging Research and Opportunities provides evolving research exploring the theoretical and practical aspects of data encryption techniques and applications within computer science. The book provides introductory knowledge on steganography and its importance, detailed analysis of how RS and PDH are performed, discussion on pixel value differencing principles, and hybrid approaches using substitution, PVD, and EMD principles. It is ideally designed for researchers and graduate and under graduate students seeking current research on the security of data during transit.
Intelligent technologies have emerged as imperative tools in computer science and information security. However, advanced computing practices have preceded new methods of attacks on the storage and transmission of data. Developing approaches such as image processing and pattern recognition are susceptible to breaches in security. Modern protection methods for these innovative techniques require additional research. The Handbook of Research on Intelligent Data Processing and Information Security Systems provides emerging research exploring the theoretical and practical aspects of cyber protection and applications within computer science and telecommunications. Special attention is paid to data encryption, steganography, image processing, and recognition, and it targets professionals who want to improve their knowledge in order to increase strategic capabilities and organizational effectiveness. As such, this book is ideal for analysts, programmers, computer engineers, software engineers, mathematicians, data scientists, developers, IT specialists, academicians, researchers, and students within fields of information technology, information security, robotics, artificial intelligence, image processing, computer science, and telecommunications.
As the advancement of technology continues, cyber security continues to play a significant role in today’s 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.
Understanding cybersecurity principles and practices is vital to all users of IT systems and services, and is particularly relevant in an organizational setting where the lack of security awareness and compliance amongst staff is the root cause of many incidents and breaches. If these are to be addressed, there needs to be adequate support and provision for related training and education in order to ensure that staff know what is expected of them and have the necessary skills to follow through. Cybersecurity Education for Awareness and Compliance explores frameworks and models for teaching cybersecurity literacy in order to deliver effective training and compliance to organizational staff so that they have a clear understanding of what security education is, the elements required to achieve it, and the means by which to link it to the wider goal of good security behavior. Split across four thematic sections (considering the needs of users, organizations, academia, and the profession, respectively), the chapters will collectively identify and address the multiple perspectives from which action is required. This book is ideally designed for IT consultants and specialist staff including chief information security officers, managers, trainers, and organizations.
With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.
Businesses constantly face online hacking threats or security breaches in their online mainframe that expose sensitive information to the wrong audience. Companies look to store their data in a separate location, distancing the availability of the information and reducing the risk of data breaches. Modern organizations need to remain vigilant against insider attacks, cloud computing risks, and security flaws within their mainframe. Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities is an essential reference source that discusses maintaining a secure management of sensitive data, and intellectual property and provides a robust security algorithm on consumer data. Featuring research on topics such as public cryptography, security principles, and trustworthy computing, this book is ideally designed for IT professionals, business managers, researchers, students, and professionals seeking coverage on preventing and detecting the insider attacks using trusted cloud computing techniques.
This book defines the nature and scope of insider problems as viewed by the financial industry. This edited volume is based on the first workshop on Insider Attack and Cyber Security, IACS 2007. The workshop was a joint effort from the Information Security Departments of Columbia University and Dartmouth College. The book sets an agenda for an ongoing research initiative to solve one of the most vexing problems encountered in security, and a range of topics from critical IT infrastructure to insider threats. In some ways, the insider problem is the ultimate security problem.