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Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique on data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining addresses the optimization problem of “hiding” sensitive association rules which due to its combinatorial nature admits a number of heuristic solutions that will be proposed and presented in this book. Exact solutions of increased time complexity that have been proposed recently are also presented as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a discussion regarding unsolved problems and future directions. Specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem. Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.

Association rule mining. --- Data mining. --- Association rule mining --- Data mining --- Computer Science --- Engineering & Applied Sciences --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Computer science. --- Computer software --- Data structures (Computer science). --- Algorithms. --- Database management. --- Artificial intelligence. --- Computer Science. --- Database Management. --- Information Systems Applications (incl. Internet). --- Artificial Intelligence (incl. Robotics). --- Data Structures, Cryptology and Information Theory. --- Algorithm Analysis and Problem Complexity. --- Performance and Reliability. --- Reusability. --- Database searching --- Data structures (Computer scienc. --- Computer software. --- Operating systems (Computers). --- Artificial Intelligence. --- Data Structures and Information Theory. --- Computer operating systems --- Computers --- Disk operating systems --- Systems software --- Software, Computer --- Computer systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Operating systems --- Application software. --- Computer software—Reusability. --- Algorism --- Algebra --- Arithmetic --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Foundations

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Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique on data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining addresses the optimization problem of hiding  sensitive association rules which due to its combinatorial nature admits a number of heuristic solutions that will be proposed and presented in this book. Exact solutions of increased time complexity that have been proposed recently are also presented as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a discussion regarding unsolved problems and future directions. Specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem. Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.

Complex analysis --- Production management --- Computer science --- Programming --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- betrouwbaarheid --- complexe analyse (wiskunde) --- applicatiebeheer --- apps --- informatica --- informatiesystemen --- database management --- informatietechnologie --- algoritmen --- KI (kunstmatige intelligentie) --- architectuur (informatica)

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This book constitutes the refereed proceedings of the International ECML/PKDD Workshop on Privacy and Security Issues in Data Mining and Machine Learning, PSDML 2010, held in Barcelona, Spain, in September 2010. The 11 revised full papers presented were carefully reviewed and selected from 21 submissions. The papers range from data privacy to security applications, focusing on detecting malicious behavior in computer systems.

Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- machine learning --- data mining --- informatica --- maatschappij --- database management --- informatica management --- robots