Data Mining Tools For Malware Detection PDF Download
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| Author | : Mehedy Masud |
| Publisher | : CRC Press |
| Total Pages | : 450 |
| Release | : 2016-04-19 |
| Genre | : Computers |
| ISBN | : 1439854556 |
Download Data Mining Tools for Malware Detection Book in PDF, ePub and Kindle
Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware d
| Author | : Bhavani Thuraisingham |
| Publisher | : CRC Press |
| Total Pages | : 953 |
| Release | : 2017-11-22 |
| Genre | : Computers |
| ISBN | : 1351645765 |
Download Big Data Analytics with Applications in Insider Threat Detection Book in PDF, ePub and Kindle
Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.
| Author | : Vijay Singh Rathore |
| Publisher | : Springer Nature |
| Total Pages | : 799 |
| Release | : 2020-10-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9811560145 |
Download Rising Threats in Expert Applications and Solutions Book in PDF, ePub and Kindle
This book presents high-quality, peer-reviewed papers from the FICR International Conference on Rising Threats in Expert Applications and Solutions 2020, held at IIS University Jaipur, Rajasthan, India, on January 17–19, 2020. Featuring innovative ideas from researchers, academics, industry professionals and students, the book covers a variety of topics, including expert applications and artificial intelligence/machine learning; advanced web technologies, like IoT, big data, and cloud computing in expert applications; information and cybersecurity threats and solutions; multimedia applications in forensics, security and intelligence; advances in app development; management practices for expert applications; and social and ethical aspects of expert applications in applied sciences.
| Author | : Mihai Christodorescu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 307 |
| Release | : 2007-03-06 |
| Genre | : Computers |
| ISBN | : 0387445994 |
Download Malware Detection Book in PDF, ePub and Kindle
This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.
| Author | : Bhavani Thuraisingham |
| Publisher | : CRC Press |
| Total Pages | : 544 |
| Release | : 2017-11-22 |
| Genre | : Computers |
| ISBN | : 1498705480 |
Download Big Data Analytics with Applications in Insider Threat Detection Book in PDF, ePub and Kindle
Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.
| Author | : Priyanka Nandal |
| Publisher | : diplom.de |
| Total Pages | : 69 |
| Release | : 2017-11-21 |
| Genre | : Computers |
| ISBN | : 3960677081 |
Download Malware Detection Book in PDF, ePub and Kindle
In the present work the behavior of malicious software is studied, the security challenges are understood, and an attempt is made to detect the malware behavior automatically using dynamic approach. Various classification techniques are studied. Malwares are then grouped according to these techniques and malware with unknown characteristics are clustered into an unknown group. The classifiers used in this research are k-Nearest Neighbors (kNN), J48 Decision Tree, and n-grams.
| Author | : Muazzam Siddiqui |
| Publisher | : |
| Total Pages | : 111 |
| Release | : 2008 |
| Genre | : Computer networks |
| ISBN | : |
Download Data Mining Methods for Malware Detection Book in PDF, ePub and Kindle
This research investigates the use of data mining methods for malware (malicious programs) detection and proposed a framework as an alternative to the traditional signature detection methods. The traditional approaches using signatures to detect malicious programs fails for the new and unknown malwares case, where signatures are not available. We present a data mining framework to detect malicious programs. We collected, analyzed and processed several thousand malicious and clean programs to find out the best features and build models that can classify a given program into a malware or a clean class. Our research is closely related to information retrieval and classification techniques and borrows a number of ideas from the field. We used a vector space model to represent the programs in our collection. Our data mining framework includes two separate and distinct classes of experiments. The first are the supervised learning experiments that used a dataset, consisting of several thousand malicious and clean program samples to train, validate and test, an array of classifiers. In the second class of experiments, we proposed using sequential association analysis for feature selection and automatic signature extraction. With our experiments, we were able to achieve as high as 98.4% detection rate and as low as 1.9% false positive rate on novel malwares.
| Author | : Mark Stamp |
| Publisher | : Springer Nature |
| Total Pages | : 651 |
| Release | : 2020-12-20 |
| Genre | : Computers |
| ISBN | : 3030625826 |
Download Malware Analysis Using Artificial Intelligence and Deep Learning Book in PDF, ePub and Kindle
This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
| Author | : Bhavani Thuraisingham |
| Publisher | : CRC Press |
| Total Pages | : 457 |
| Release | : 2022-04-27 |
| Genre | : Computers |
| ISBN | : 1000557502 |
Download Secure Data Science Book in PDF, ePub and Kindle
Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science. After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media. This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.
| Author | : Joshua Saxe |
| Publisher | : No Starch Press |
| Total Pages | : 274 |
| Release | : 2018-09-25 |
| Genre | : Computers |
| ISBN | : 1593278594 |
Download Malware Data Science Book in PDF, ePub and Kindle
Malware 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.
