Download or read book Data Mining and Reverse Engineering written by Stefano Spaccapietra and published by Springer. This book was released on 2013-03-14 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Searching for Semantics: Data Mining, Reverse Engineering Stefano Spaccapietra Fred M aryanski Swiss Federal Institute of Technology University of Connecticut Lausanne, Switzerland Storrs, CT, USA REVIEW AND FUTURE DIRECTIONS In the last few years, database semantics research has turned sharply from a highly theoretical domain to one with more focus on practical aspects. The DS- 7 Working Conference held in October 1997 in Leysin, Switzerland, demon strated the more pragmatic orientation of the current generation of leading researchers. The papers presented at the meeting emphasized the two major areas: the discovery of semantics and semantic data modeling. The work in the latter category indicates that although object-oriented database management systems have emerged as commercially viable prod ucts, many fundamental modeling issues require further investigation. Today's object-oriented systems provide the capability to describe complex objects and include techniques for mapping from a relational database to objects. However, we must further explore the expression of information regarding the dimensions of time and space. Semantic models possess the richness to describe systems containing spatial and temporal data. The challenge of in corporating these features in a manner that promotes efficient manipulation by the subject specialist still requires extensive development.

Download or read book Data Mining and Reverse Engineering written by S. Spaccapietra and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Mining and Reverse Engineering written by Stefano Spaccapietra and published by Springer. This book was released on 1998-04-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Searching for Semantics: Data Mining, Reverse Engineering Stefano Spaccapietra Fred M aryanski Swiss Federal Institute of Technology University of Connecticut Lausanne, Switzerland Storrs, CT, USA REVIEW AND FUTURE DIRECTIONS In the last few years, database semantics research has turned sharply from a highly theoretical domain to one with more focus on practical aspects. The DS- 7 Working Conference held in October 1997 in Leysin, Switzerland, demon strated the more pragmatic orientation of the current generation of leading researchers. The papers presented at the meeting emphasized the two major areas: the discovery of semantics and semantic data modeling. The work in the latter category indicates that although object-oriented database management systems have emerged as commercially viable prod ucts, many fundamental modeling issues require further investigation. Today's object-oriented systems provide the capability to describe complex objects and include techniques for mapping from a relational database to objects. However, we must further explore the expression of information regarding the dimensions of time and space. Semantic models possess the richness to describe systems containing spatial and temporal data. The challenge of in corporating these features in a manner that promotes efficient manipulation by the subject specialist still requires extensive development.

Download or read book Data Mining and Machine Learning for Reverse Engineering written by Honghui Ding and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Reverse engineering is fundamental for understanding the inner workings of new malware, exploring new vulnerabilities in existing systems, and identifying patent infringements in the distributed executables. It is the process of getting an in-depth understanding of a given binary executable without its corresponding source code. Reverse engineering is a manually intensive and time-consuming process that relies on a thorough understanding of the full development stack from hardware to applications. It requires a much steeper learning curve than programming. Given the unprecedentedly vast amount of data to be analyzed and the significance of reverse engineering, the overall question that drives the studies in this thesis is how can data mining and machine learning technologies make cybersecurity practitioners more productive to uncover the provenance, understand the intention, and discover the issues behind the data in a scalable way. In this thesis, I focus on two data-driven solutions to help reverse engineers analyzing binary data: assembly clone search and behavioral summarization. Assembly code clone search is emerging as an Information Retrieval (IR) technique that helps address security problems. It has been used for differing binaries to locate the changed parts, identifying known library functions such as encryption, searching for known programming bugs or zero-day vulnerabilities in existing software or Internet of Things (IoT) devices firmware, as well as detecting software plagiarism or GNU license infringements when the source code is unavailable. However, designing an effective search engine is difficult, due to varieties of compiler optimization and obfuscation techniques that make logically similar assembly functions appear to be dramatically different. By working closely with reverse engineers, I identify three different scenarios of reverse engineering and develop novel data mining and machine learning models for assembly clone search to address the respective challenges. By developing an intelligent assembly clone search platform, I optimize the process of reverse engineering by addressing the information needs of reverse engineers. Experimental results suggest that Kam1n0 is accurate, efficient, and scalable for handling a large volume of data.The second part of the thesis goes beyond optimizing an information retrieval process for reverse engineering. I propose to automatically and statically characterize the behaviors of a given binary executable. Behavioral indicators denote those potentially high-risk malicious behaviors exhibited by malware, such as unintended network communications, file encryption, keystroke logging, abnormal registry modifications, sandbox evasion, and camera manipulation. I design a novel neural network architecture that models the different aspects of an executable. It is able to predict over 139 suspicious and malicious behavioral indicators, without running the executable. The resulting system can be used as an additional binary analytic layer to mitigate the issues of polymorphism, metamorphism, and evasive techniques. It also provides another behavioral abstraction of malware to security analysts and reverse engineers. Therefore, it can reduce the data to be manually analyzed, and the reverse engineers can focus on the binaries that are of their interest. In summary, this thesis presents four original research projects that not only advance the knowledge in reverse engineering and data mining, but also contribute to the overall safety of our cyber world by providing open-source award-winning binary analysis systems that empower cybersecurity practitioners"--

Download or read book Data Mining and Reverse Engineering written by Stefano Spaccapietra and published by . This book was released on 2014-01-15 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Classification of Malware Using Reverse Engineering and Data Mining Techniques written by Ravindar Reddy Ravula and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detecting new and unknown malware is a major challenge in today's software security profession. A lot of approaches for the detection of malware using data mining techniques have already been proposed. Majority of the works used static features of malware. However, static detection methods fall short of detecting present day complex malware. Although some researchers proposed dynamic detection methods, the methods did not use all the malware features. In this work, an approach for the detection of new and unknown malware was proposed and implemented. 582 malware and 521 benign software samples were collected from the Internet. Each sample was reverse engineered for analyzing its effect on the operating environment and to extract the static and behavioral features. The raw data extracted from the reverse engineering was preprocessed and two datasets are obtained: dataset with reversed features and dataset with API Call features. Feature reduction was performed manually on the dataset with reversed features and the features that do not contribute to the classification were removed. Machine learning classification algorithm, J48 was applied to dataset with reversed features to obtain classification rules and a decision tree with the rules was obtained. To reduce the tree size and to obtain optimum number of decision rules, attribute values in the dataset with reversed features were discretized and another dataset was prepared with discretized attribute values. The new dataset was applied to J48 algorithm and a decision tree was generated with another set of classification rules. To further reduce the tree and number of decision rules, the dataset with discretized features was subjected to a machine learning tool, BLEM2 which is based on the rough sets and produces decision rules. To test the accuracy of the rules, the dataset with decision rules from BLEM2 was given as input to J48 algorithm. The same procedure was followed for the dataset with API Call features. Another set of experiments was conducted on the three datasets using Naïve Bayes classifier to generate training model for classification. All the training models were tested with an independent training set. J48 decision tree algorithm produced better results with DDF and DAF datasets with accuracies of 81.448% and 89.140% respectively. Naïve Bayes classifier produced better results with DDF dataset with an accuracy of 85.067%.

Download or read book Reverse Engineering written by A.C. Telea and published by BoD – Books on Demand. This book was released on 2012-03-07 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reverse engineering encompasses a wide spectrum of activities aimed at extracting information on the function, structure, and behavior of man-made or natural artifacts. Increases in data sources, processing power, and improved data mining and processing algorithms have opened new fields of application for reverse engineering. In this book, we present twelve applications of reverse engineering in the software engineering, shape engineering, and medical and life sciences application domains. The book can serve as a guideline to practitioners in the above fields to the state-of-the-art in reverse engineering techniques, tools, and use-cases, as well as an overview of open challenges for reverse engineering researchers.

Download or read book Evolutionary Algorithm Based Automated Reverse Engineering and Defect Discovery written by and published by . This book was released on 2007 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: A data mining based procedure for automated reverse engineering and defect discovery has been developed. The data mining algorithm for reverse engineering uses a genetic program (GP) as a data mining function. A GP is an evolutionary algorithm that automatically evolves populations of computer programs or mathematical expressions, eventually selecting one that is optimal in the sense that it maximizes a fitness function. The system to be reverse engineered is typically a subcomponent of a sensor that may not be disassembled and for which there are no design documents. The sensor is used to create a database of input signals and output measurements. Rules about the likely design properties of the sensor are collected from experts. The rules are used to create a fitness function for the GP, allowing GP-based data mining. This procedure incorporates not only the experts' rules into the fitness function, but also the information in the database. The information extracted through this process is the internal design specifications of the sensor. These design properties can be used to create a fitness function for a genetic algorithm (GA), which is in turn used to search for defects in the digital logic (DL) design. In this report, design flaws in two different sensor systems are detected using a GA. One of these systems makes passive detections, the other makes up part of a radar. In the second case, detecting the flaw allows the design of a radar jamming signal. Uncertainty related to the input-output database and the expert-based rule set can significantly alter the reverse engineering results. This report provides significant experimental and theoretical results related to GP-based data mining for reverse engineering. It presents methods of quantifying uncertainty. Finally, it examines methods for reducing the uncertainty.

Download or read book Reversing written by Eldad Eilam and published by John Wiley & Sons. This book was released on 2011-12-12 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beginning with a basic primer on reverse engineering-including computer internals, operating systems, and assembly language-and then discussing the various applications of reverse engineering, this book provides readers with practical, in-depth techniques for software reverse engineering. The book is broken into two parts, the first deals with security-related reverse engineering and the second explores the more practical aspects of reverse engineering. In addition, the author explains how to reverse engineer a third-party software library to improve interfacing and how to reverse engineer a competitor's software to build a better product. * The first popular book to show how software reverse engineering can help defend against security threats, speed up development, and unlock the secrets of competitive products * Helps developers plug security holes by demonstrating how hackers exploit reverse engineering techniques to crack copy-protection schemes and identify software targets for viruses and other malware * Offers a primer on advanced reverse-engineering, delving into "disassembly"-code-level reverse engineering-and explaining how to decipher assembly language

Download or read book Data Mining for Scientific and Engineering Applications written by R.L. Grossman and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Download or read book Reverse Engineering written by Ruth Hinrichs and published by . This book was released on 2015-03-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reverse engineering consists of a broad range of activities whose main function is to extract knowledge about the structure, application and behaviour of natural or manmade objects. Enhanced data mining and processing algorithms, and a development of data sources has opened various avenues for reverse engineering applications. This book demonstrates different functions of this field in various other areas. This book consists of a comprehensive summary of the field of reverse engineering and will also serve as a roadmap for practitioners of various fields regarding the applications of reverse engineering in their concerned fields.

Download or read book Reverse Engineering written by A.C. Telea and published by IntechOpen. This book was released on 2012-03-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reverse engineering encompasses a wide spectrum of activities aimed at extracting information on the function, structure, and behavior of man-made or natural artifacts. Increases in data sources, processing power, and improved data mining and processing algorithms have opened new fields of application for reverse engineering. In this book, we present twelve applications of reverse engineering in the software engineering, shape engineering, and medical and life sciences application domains. The book can serve as a guideline to practitioners in the above fields to the state-of-the-art in reverse engineering techniques, tools, and use-cases, as well as an overview of open challenges for reverse engineering researchers.

Download or read book Reverse Engineering written by A.C. Telea and published by IntechOpen. This book was released on 2012-03-07 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reverse engineering encompasses a wide spectrum of activities aimed at extracting information on the function, structure, and behavior of man-made or natural artifacts. Increases in data sources, processing power, and improved data mining and processing algorithms have opened new fields of application for reverse engineering. In this book, we present twelve applications of reverse engineering in the software engineering, shape engineering, and medical and life sciences application domains. The book can serve as a guideline to practitioners in the above fields to the state-of-the-art in reverse engineering techniques, tools, and use-cases, as well as an overview of open challenges for reverse engineering researchers.

Download or read book Journal on Data Semantics XV written by Stefano Spaccapietra and published by Springer. This book was released on 2011-08-09 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence. Volume XV results from a rigorous selection among 25 full papers received in response to two calls for contributions issued in 2009 and 2010. In addition, this volume contains a special report on the Ontology Alignment Evaluation Initiative, an event that has been held once a year in the last five years and has attracted considerable attention from the ontology community. This is the last LNCS transactions volume of the Journal on Data Semantics; the next issue will appear as a regular Springer Journal, published quarterly starting from 2012.

Download or read book Knowledge Discovery Knowledge Engineering and Knowledge Management written by Ana Fred and published by Springer. This book was released on 2013-04-10 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Third International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management, IC3K 2011, held in Paris, France, in October 2011. This book includes revised and extended versions of a strict selection of the best papers presented at the conference; 39 revised full papers together with one invited lecture were carefully reviewed and selected from 429 submissions. According to the three covered conferences KDIR 2011, KEOD 2011, and KMIS 2011, the papers are organized in topical sections on knowledge discovery and information retrieval, knowledge engineering and ontology development, and on knowledge management and information sharing.

Download or read book On the Move to Meaningful Internet Systems 2002 CoopIS DOA and ODBASE written by Zahir Tari and published by Springer Science & Business Media. This book was released on 2002-10-16 with total page 1388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the three confederated conferences CoopIS 2002, DOA 2002, and ODBASE 2002, held in Irvine, CA, USA, in October/November 2002. The 77 revised full papers and 10 posters presented were carefully reviewed and selected from a total of 291 submissions. The papers are organized in topical sections on interoperability, workflow, mobility, agents, peer-to-peer and ubiquitous, work process, business and transaction, infrastructure, query processing, quality issues, agents and middleware, cooperative systems, ORB enhancements, Web services, distributed object scalability and heterogeneity, dependability and security, reflection and reconfiguration, real-time scheduling, component-based applications, ontology languages, conceptual modeling, ontology management, ontology development and engineering, XML and data integration, and tools for the intelligent Web.

Download or read book Intelligent Data Mining written by Da Ruan and published by Springer Science & Business Media. This book was released on 2005-08-24 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.