In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability. - Includes data deduplication methods for a wide variety of applications - Includes concepts and implementation strategies that will help the reader to use the suggested methods - Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable methods for their applications - Focuses on reduced storage, backup, recovery, and reliability, which are the most important aspects of implementing data deduplication approaches - Includes case studies

The world is experiencing an unprecedented period of change and growth through all the electronic and technilogical developments and everyone on the planet has been impacted. What was once ‘science fiction’, today it is a reality. This book explores the world of many of once unthinkable advancements by explaining current technologies in great detail. Each chapter focuses on a different aspect - Machine Vision, Pattern Analysis and Image Processing - Advanced Trends in Computational Intelligence and Data Analytics - Futuristic Communication Technologies - Disruptive Technologies for Future Sustainability. The chapters include the list of topics that spans all the areas of smart intelligent systems and computing such as: Data Mining with Soft Computing, Evolutionary Computing, Quantum Computing, Expert Systems, Next Generation Communication, Blockchain and Trust Management, Intelligent Biometrics, Multi-Valued Logical Systems, Cloud Computing and security etc. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

Until now, the only way to capture, store, and effectively retain constantly growing amounts of enterprise data was to add more disk space to the storage infrastructure, an approach that can quickly become cost-prohibitive as information volumes continue to grow and capital budgets for infrastructure do not. In this IBM® Redbooks® publication, we introduce data deduplication, which has emerged as a key technology in dramatically reducing the amount of, and therefore the cost associated with storing, large amounts of data. Deduplication is the art of intelligently reducing storage needs through the elimination of redundant data so that only one instance of a data set is actually stored. Deduplication reduces data an order of magnitude better than common data compression techniques. IBM has the broadest portfolio of deduplication solutions in the industry, giving us the freedom to solve customer issues with the most effective technology. Whether it is source or target, inline or post, hardware or software, disk or tape, IBM has a solution with the technology that best solves the problem. This IBM Redbooks publication covers the current deduplication solutions that IBM has to offer: IBM ProtecTIER® Gateway and Appliance IBM Tivoli® Storage Manager IBM System Storage® N series Deduplication

Data is the lifeblood of modern business, and modern data centers have extremely demanding requirements for size, speed, and reliability. Storage Area Networks (SANs) and Network Attached Storage (NAS) allow organizations to manage and back up huge file systems quickly, thereby keeping their lifeblood flowing. W. Curtis Preston's insightful book takes you through the ins and outs of building and managing large data centers using SANs and NAS. As a network administrator you're aware that multi-terabyte data stores are common and petabyte data stores are starting to appear. Given this much data, how do you ensure that it is available all the time, that access times and throughput are reasonable, and that the data can be backed up and restored in a timely manner? SANs and NAS provide solutions that help you work through these problems, with special attention to the difficulty of backing up huge data stores. This book explains the similarities and differences of SANs and NAS to help you determine which, or both, of these complementing technologies are appropriate for your network. Using SANs, for instance, is a way to share multiple devices (tape drives and disk drives) for storage, while NAS is a means for centrally storing files so they can be shared. Preston exams each technology with a vendor neutral approach, starting with the building blocks of a SAN and how they can be assembled for effective storage solutions. He covers day-to-day management and backup and recovery for both SANs and NAS in detail. Whether you're a seasoned storage administrator or a network administrator charged with taking on this role, you'll find all the information you need to make informed architecture and data management decisions. The book fans out to explore technologies such as RAID and other forms of monitoring that will help complement your data center. With an eye on the future, other technologies that might affect the architecture and management of the data center are explored. This is sure to be an essential volume in any network administrator's or storage administrator's library.

As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

This book presents recent advances in quality measures in data mining.

This two-volume set LNCS 12239-12240 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS. The total of 142 full papers presented in this two-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: Artificial intelligence and internet of things. Part II: Internet of things, information security, big data and cloud computing, and information processing.