Patterns And Anomalies PDF Download
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Author | : Kaustav Das |
Publisher | : |
Total Pages | : 152 |
Release | : 2009 |
Genre | : Anomaly detection (Computer security) |
ISBN | : |
Download Detecting Patterns of Anomalies Book in PDF, ePub and Kindle
Abstract: "An anomaly is an observation that does not conform to the expected normal behavior. With the ever increasing amount of data being collected universally, automatic surveillance systems are becoming more popular and are increasingly using data mining methods to detect patterns of anomalies. Detecting anomalies can provide useful and actionable information in a variety of real-world scenarios. For example, in disease monitoring, a timely detection of an epidemic can potentially save many lives. The diverse nature of real-world datasets, and the difficulty of obtaining labeled training data make it challenging to develop a universal framework for anomaly detection. We focus on a key feature of most real world scenarios, that multiple anomalous records are usually generated by a common anomalous process. In this thesis we develop methods that utilize the similarity between records in these groups or patterns of anomalies to perform better detection. We also investigate new methods for detection of individual record anomalies, which we then incorporate into the group detection methods. A recurring feature of our methods is combinatorial search over some space (e.g. over all subsets of attributes, or over all subsets of records). We use a variety of computational speedup tricks and approximation techniques to make these methods scalable to large datasets. Since most of our motivating problems involve datasets having categorical or symbolic values, we focus on categorical valued datasets. Apart from this, we make few assumptions about the data, and our methods are very general and applicable to a wide variety of domains. Additionally, we investigate anomaly pattern detection in data structured by space and time. Our method generalizes the popular method of spatiotemporal scan statistics to learn and detect specific, time-varying spatial patterns in the data. Finally, we show an efficient and easily interpretable technique for anomaly detection in multivariate time series data. We evaluate our methods on a variety of real world data sets including both real and synthetic anomalies."
Author | : Mark Talabis |
Publisher | : Syngress |
Total Pages | : 183 |
Release | : 2014-11-25 |
Genre | : Computers |
ISBN | : 0128005068 |
Download Information Security Analytics Book in PDF, ePub and Kindle
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. Written by security practitioners, for security practitioners Real-world case studies and scenarios are provided for each analytics technique Learn about open-source analytics and statistical packages, tools, and applications Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes Learn how to utilize big data techniques to assist in incident response and intrusion analysis
Author | : David W. Smith |
Publisher | : W.B. Saunders Company |
Total Pages | : 536 |
Release | : 1976 |
Genre | : Medical |
ISBN | : |
Download Recognizable Patterns of Human Malformation Book in PDF, ePub and Kindle
Author | : Ethne Barnes |
Publisher | : John Wiley & Sons |
Total Pages | : 230 |
Release | : 2012-09-25 |
Genre | : Science |
ISBN | : 1118430778 |
Download Atlas of Developmental Field Anomalies of the Human Skeleton Book in PDF, ePub and Kindle
Written by one of the most consulted authorities on the subject, Atlas of Developmental Field Anomalies of the Human Skeleton is the pre-eminent resource for developmental defects of the skeleton. This guide focuses on localized bone structures utilizing the morphogenetic approach that addresses the origins of variability within specific developmental fields during embryonic development. Drawings and photographs make up most of the text, forming a picture atlas with descriptive text for each group of illustrations. Each section and subdivision is accompanied by brief discussions and drawings of morphogenetic development.
Author | : Michael Davis |
Publisher | : |
Total Pages | : |
Release | : 2014 |
Genre | : |
ISBN | : |
Download Discovering Patterns and Anomalies in Graphs with Discrete and Numeric Attributes Book in PDF, ePub and Kindle
Author | : Wayne Michael Hall |
Publisher | : Bloomsbury Publishing USA |
Total Pages | : 458 |
Release | : 2009-12-22 |
Genre | : Political Science |
ISBN | : 0313382662 |
Download Intelligence Analysis Book in PDF, ePub and Kindle
This book offers a vast conceptual and theoretical exploration of the ways intelligence analysis must change in order to succeed against today's most dangerous combatants and most complex irregular theatres of conflict. Intelligence Analysis: How to Think in Complex Environments fills a void in the existing literature on contemporary warfare by examining the theoretical and conceptual foundations of effective modern intelligence analysis—the type of analysis needed to support military operations in modern, complex operational environments. This volume is an expert guide for rethinking intelligence analysis and understanding the true nature of the operational environment, adversaries, and most importantly, the populace. Intelligence Analysis proposes substantive improvements in the way the U.S. national security system interprets intelligence, drawing on the groundbreaking work of theorists ranging from Carl von Clauswitz and Sun Tzu to M. Mitchell Waldrop, General David Petraeus, Richards Heuer, Jr., Orson Scott Card, and others. The new ideas presented here will help the nation to amass a formidable, cumulative intelligence power, with distinct advantages over any and all adversaries of the future regardless of the level of war or type of operational environment.
Author | : Michael Charles Davis |
Publisher | : |
Total Pages | : 0 |
Release | : 2014 |
Genre | : |
ISBN | : |
Download Discovering Patterns and Anomalies in Graphs with Discrete and Numeric Attributes Book in PDF, ePub and Kindle
Author | : Saira Banu |
Publisher | : Nova Science Publishers |
Total Pages | : 0 |
Release | : 2021 |
Genre | : Anomaly detection (Computer security) |
ISBN | : 9781536192643 |
Download Anomaly Detection Book in PDF, ePub and Kindle
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data. This book will mainly target researchers and higher graduate learners in computer science and data science.
Author | : Prithiviraj Muthumanickam |
Publisher | : Linköping University Electronic Press |
Total Pages | : 58 |
Release | : 2019-11-25 |
Genre | : |
ISBN | : 9179299652 |
Download Data Abstraction and Pattern Identification in Time-series Data Book in PDF, ePub and Kindle
Data sources such as simulations, sensor networks across many application domains generate large volumes of time-series data which exhibit characteristics that evolve over time. Visual data analysis methods can help us in exploring and understanding the underlying patterns present in time-series data but, due to their ever-increasing size, the visual data analysis process can become complex. Large data sets can be handled using data abstraction techniques by transforming the raw data into a simpler format while, at the same time, preserving significant features that are important for the user. When dealing with time-series data, abstraction techniques should also take into account the underlying temporal characteristics. This thesis focuses on different data abstraction and pattern identification methods particularly in the cases of large 1D time-series and 2D spatio-temporal time-series data which exhibit spatiotemporal discontinuity. Based on the dimensionality and characteristics of the data, this thesis proposes a variety of efficient data-adaptive and user-controlled data abstraction methods that transform the raw data into a symbol sequence. The transformation of raw time-series into a symbol sequence can act as input to different sequence analysis methods from data mining and machine learning communities to identify interesting patterns of user behavior. In the case of very long duration 1D time-series, locally adaptive and user-controlled data approximation methods were presented to simplify the data, while at the same time retaining the perceptually important features. The simplified data were converted into a symbol sequence and a sketch-based pattern identification was then used to identify patterns in the symbolic data using regular expression based pattern matching. The method was applied to financial time-series and patterns such as head-and-shoulders, double and triple-top patterns were identified using hand drawn sketches in an interactive manner. Through data smoothing, the data approximation step also enables visualization of inherent patterns in the time-series representation while at the same time retaining perceptually important points. Very long duration 2D spatio-temporal eye tracking data sets that exhibit spatio-temporal discontinuity was transformed into symbolic data using scalable clustering and hierarchical cluster merging processes, each of which can be parallelized. The raw data is transformed into a symbol sequence with each symbol representing a region of interest in the eye gaze data. The identified regions of interest can also be displayed in a Space-Time Cube (STC) that captures both the temporal and contextual information. Through interactive filtering, zooming and geometric transformation, the STC representation along with linked views enables interactive data exploration. Using different sequence analysis methods, the symbol sequences are analyzed further to identify temporal patterns in the data set. Data collected from air traffic control officers from the domain of Air traffic control were used as application examples to demonstrate the results.
Author | : |
Publisher | : |
Total Pages | : 1020 |
Release | : 1984 |
Genre | : Fishes |
ISBN | : |
Download Collected Reprints Book in PDF, ePub and Kindle