X. Sean Wang

Bhavani Thuraisingham

Steve Furnell

This is the first joint working conference between the IFIP Working Groups 11. 1 and 11. 5. We hope this joint conference will promote collaboration among researchers who focus on the security management issues and those who are interested in integrity and control of information systems. Indeed, as management at any level may be increasingly held answerable for the reliable and secure operation of the information systems and services in their respective organizations in the same manner as they are for financial aspects of the enterprise, there is an increasing need for ensuring proper standards of integrity and control in information systems in order to ensure that data, software and, ultimately, the business processes are complete, adequate and valid for intended functionality and expectations of the owner (i. e. the user organization). As organizers, we would like to thank the members of the international program committee for their review work during the paper selection process. We would also like to thank the authors of the invited papers, who added valuable contribution to this first joint working conference. Paul Dowland X. Sean Wang December 2005 Contents Preface vii Session 1 - Security Standards Information Security Standards: Adoption Drivers (Invited Paper) 1 JEAN-NOEL EZINGEARD AND DAVID BIRCHALL Data Quality Dimensions for Information Systems Security: A Theorectical Exposition (Invited Paper) 21 GURVIRENDER TEJAY, GURPREET DHILLON, AND AMITA GOYAL CHIN From XML to RDF: Syntax, Semantics, Security, and Integrity (Invited Paper) 41 C. FARKAS, V. GowADiA, A. JAIN, AND D.

IFIP TC-11 WG 11.1 & WG 11.5 Joint Working Conference

Security Management, Integrity, and Internal Control in Information Systems

Although the use of cloud computing platforms and applications has expanded rapidly, most books on the subject focus on high-level concepts. There has long been a need for a book that provides detailed guidance on how to develop secure clouds. Filling this void, Developing and Securing the Cloud provides a comprehensive overview of cloud computing technology. Supplying step-by-step instruction on how to develop and secure cloud computing platforms and web services, it includes an easy-to-understand, basic-level overview of cloud computing and its supporting technologies. Presenting a framework for secure cloud computing development, the book describes supporting technologies for the cloud such as web services and security. It details the various layers of the cloud computing framework, including the virtual machine monitor and hypervisor, cloud data storage, cloud data management, and virtual network monitor. It also provides several examples of cloud products and prototypes, including private, public, and U.S. government clouds. Reviewing recent developments in cloud computing, the book illustrates the essential concepts, issues, and challenges in developing and securing today’s cloud computing platforms and applications. It also examines prototypes built on experimental cloud computing systems that the author and her team have developed at the University of Texas at Dallas. This diverse reference is suitable for those in industry, government, and academia. Technologists will develop the understanding required to select the appropriate tools for particular cloud applications. Developers will discover alternative designs for cloud development, and managers will understand if it’s best to build their own clouds or contract them out.

Developing and Securing the Cloud

Mehedy Masud

Latifur Khan

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 detection. Integrating theory with practical techniques and experimental results, it focuses on malware detection applications for email worms, malicious code, remote exploits, and botnets. The authors describe the systems they have designed and developed: email worm detection using data mining, a scalable multi-level feature extraction technique to detect malicious executables, detecting remote exploits using data mining, and flow-based identification of botnet traffic by mining multiple log files. For each of these tools, they detail the system architecture, algorithms, performance results, and limitations. Discusses data mining for emerging applications, including adaptable malware detection, insider threat detection, firewall policy analysis, and real-time data mining Includes four appendices that provide a firm foundation in data management, secure systems, and the semantic web Describes the authors’ tools for stream data mining From algorithms to experimental results, this is one of the few books that will be equally valuable to those in industry, government, and academia. It will help technologists decide which tools to select for specific applications, managers will learn how to determine whether or not to proceed with a data mining project, and developers will find innovative alternative designs for a range of applications.

Data Mining Tools for Malware Detection

Vinod Yegneswaran

XiaoFeng Wang

This volume constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Security and Privacy in Communication Networks, SecureComm 2015, held in Dallas, TX, USA, in October 2015. The 29 regular and 10 poster papers presented were carefully reviewed and selected from 107 submissions. It also presents 9 papers accepted of the workshop on Applications and Techniques in Cyber Security, ATCS 2015. The papers are grouped in the following topics: mobile, system, and software security; cloud security; privacy and side channels; Web and network security; crypto, protocol, and model.

11th International Conference, SecureComm 2015, Dallas, TX, USA, October 26-29, 2015, Revised Selected Papers

Security and Privacy in Communication Networks

Murat Kantarcioglu

Satyen Abrol

Raymond Heatherly

Vaibhav Khadilkar

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technologies that ensure the privacy of the participants of the network as well as provide controlled access to the information posted and exchanged by the participants. The authors explore security and privacy issues for social media systems, analyze such systems, and discuss prototypes they have developed for social media systems whose data are represented using semantic web technologies. These experimental systems have been developed at The University of Texas at Dallas. The material in this book, together with the numerous references listed in each chapter, have been used for a graduate-level course at The University of Texas at Dallas on analyzing and securing social media. Several experimental systems developed by graduate students are also provided. The book is divided into nine main sections: (1) supporting technologies, (2) basics of analyzing and securing social networks, (3) the authors’ design and implementation of various social network analytics tools, (4) privacy aspects of social networks, (5) access control and inference control for social networks, (6) experimental systems designed or developed by the authors on analyzing and securing social networks, (7) social media application systems developed by the authors, (8) secure social media systems developed by the authors, and (9) some of the authors’ exploratory work and further directions.

Analyzing and Securing Social Networks

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

Bhavani Thuraisingham

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