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Author: Françoise Fogelman-Soulié
Publisher: IOS Press
Published: 2008
Total Pages: 388
ISBN-13: 1586038982
DOWNLOAD EBOOKThe real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. This book is suitable for those interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues.
Author: Jure Leskovec
Publisher: Cambridge University Press
Published: 2014-11-13
Total Pages: 480
ISBN-13: 1107077230
DOWNLOAD EBOOKNow in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Sumeet Dua
Publisher: CRC Press
Published: 2016-04-19
Total Pages: 256
ISBN-13: 1439839433
DOWNLOAD EBOOKWith the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible
Author: Jaideep Vaidya
Publisher: Springer Science & Business Media
Published: 2005-11-29
Total Pages: 146
ISBN-13: 9780387258867
DOWNLOAD EBOOKPrivacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.
Author: Mohammed J. Zaki
Publisher: Cambridge University Press
Published: 2020-01-30
Total Pages: 779
ISBN-13: 1108473989
DOWNLOAD EBOOKNew to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.
Author: Anoop Singhal
Publisher: Springer Science & Business Media
Published: 2007-04-06
Total Pages: 166
ISBN-13: 0387476539
DOWNLOAD EBOOKThe application of data warehousing and data mining techniques to computer security is an important emerging area, as information processing and internet accessibility costs decline and more and more organizations become vulnerable to cyber attacks. These security breaches include attacks on single computers, computer networks, wireless networks, databases, or authentication compromises. This book describes data warehousing and data mining techniques that can be used to detect attacks. It is designed to be a useful handbook for practitioners and researchers in industry, and is also suitable as a text for advanced-level students in computer science.
Author: Daniel Barbará
Publisher: Springer Science & Business Media
Published: 2002-05-31
Total Pages: 286
ISBN-13: 9781402070549
DOWNLOAD EBOOKData mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security. Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.
Author: National Research Council
Publisher: National Academies Press
Published: 2013-09-03
Total Pages: 191
ISBN-13: 0309287812
DOWNLOAD EBOOKData mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author: Brij Gupta
Publisher:
Published: 2021
Total Pages: 336
ISBN-13: 9781799884132
DOWNLOAD EBOOK"This book explores the key concepts of data mining and utilizing them on online social media platforms, offering valuable insight into data mining approaches for big data and sentiment analysis in online social media and covering many important security and other aspects and current trends"--
Author: Joshua Saxe
Publisher: No Starch Press
Published: 2018-09-25
Total Pages: 274
ISBN-13: 1593278594
DOWNLOAD EBOOKMalware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization. Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis. You'll learn how to: - Analyze malware using static analysis - Observe malware behavior using dynamic analysis - Identify adversary groups through shared code analysis - Catch 0-day vulnerabilities by building your own machine learning detector - Measure malware detector accuracy - Identify malware campaigns, trends, and relationships through data visualization Whether you're a malware analyst looking to add skills to your existing arsenal, or a data scientist interested in attack detection and threat intelligence, Malware Data Science will help you stay ahead of the curve.
