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Third International Conference on Information
Systems Security (ICISS 2007) 16-20 December 2007 |
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Indian Institute of Technology, Delhi, India Center for Secure Information Systems, George Mason University, Fairfax, VA, USA |
TutorialsThe following tutorials will be offered at ICISS 2007: Recent Advances in Role Based Access Control, Shamik Sural (IIT Kharagpur, India)Abstract Access control models are of prime interest in computer security. The models are meant to express various complex access control needs relevant to resource protection in real world. In this respect, Role Based Access Control Model (RBAC) has been found to be quite useful and has drawn a lot of research interest over the last fifteen years. The main advantage of RBAC is the organization power of role. Roles are considered to be inherently natural and they express a single unit of job function in an organization. Biography Shamik Sural is an Associate Professor at the School of Information Technology, IIT Kharagpur India. He received the B.E. degree in Electronics & Tele-communication Engineering from Jadavpur University, Calcutta, India, in 1990, M.E. in Electrical Communication Engineering from Indian Institute of Science, Bangalore, India, in 1992 and the Ph.D. degree from Jadavpur University in 2000. Before joining IIT, he held technical and managerial positions in a number of organizations both in India as well as in the USA. Web Application: Security Threats and Challenges, Poonam Rani Gupta (CDAC, Noida, India) and P. Govind Raj (CDAC, India)Abstract The World Wide Web is growing at a very fast pace in terms of web servers and also the purpose it served. From a platform to share information it has become a platform to host applications. This trend would grow as more of Web 2.0 becomes evident. Further, in era of the Semantic Web the web would host even more intelligent application. Although, the www provides a lot of convenience, the convenience comes with an equal share of risk. Issue of confidentiality, integrity and availability of information, identity theft, and non-availability of service are some of the additional risks associated with convenience of www. Biography Dr. P.R. Gupta has more than 20 years experience in academics and research . She has M.Tech from IIT Delhi and Ph.D. in Computer Sc. & Engg from KNIT, Sultanpur. Presently, she is working as Associate Professor at CDAC , Noida . Her research interest include Ubiquitous computing, Artificial Intelligence, information security, Open Source Systems , e-governance and IPR issues,. A localized live CD version of Linux namely Abhigyan has been developed by her team for Hindi, Bengali, Tamil and Punjabi. Her group is also working for developing tools for training physically challenged people. Mr P Govind Raj is a working as project engineer at CDAC, Noida . His research interest includes Ubiquitous computing, e-Security and Open Source Systems. He has been involved in development of ABHIGYAN-a Live CD Version of Linux with Indian language support. Application of Data Mining Techniques for Computer Security, Jaideep Srivatsava (University of Minnesota, USA)Abstract Today computers control power, oil and gas delivery, communication systems, transportation networks, banking and financial services, and various other infrastructure services critical to the functioning of our society. However, as the cost of the information processing and Internet accessibility falls, more and more organizations are becoming vulnerable to a wide variety of cyber threats. According to CERT/CC (Computer Emergency Response Team/Coordination Center), the rate of cyber attacks has been more than doubling every year for some time. It has become increasingly important to make our information systems, especially those used for critical functions in the military and commercial sectors, resistant to and tolerant of such attacks. Intrusion detection, as a special form of cyber threat analysis, includes identifying a set of malicious actions that compromise the integrity, confidentiality, and availability of information resources. Traditional methods for intrusion detection are based on extensive knowledge of signatures of known attacks. The signature database has to be manually revised for each new type of intrusion that is discovered. A significant limitation of signature-based methods is that they cannot detect emerging cyber threats, since by their very nature these threats are launched using previously unknown attacks. These limitations have led to an increasing interest in intrusion detection techniques based upon data mining. The tremendous increase of novel cyber attacks has made data mining based intrusion detection techniques extremely useful in their detection. These techniques generally fall into one of two categories; misuse detection and anomaly detection. In misuse detection, each instance in a data set is labeled as 'normal' or 'attack/intrusion' and a learning algorithm is trained over the labeled data. However, standard data mining techniques are not applicable due to issues including (i) dealing with skewed class distribution (attacks/intrusions correspond to a class of interest that is much smaller, i.e. rarer, than the class representing normal behavior) and (ii) learning from data streams (attacks/intrusions very often represent sequence of events). Anomaly detection, on the other hand, builds models of normal behavior, and automatically detects new types of intrusions as deviations from normal usage. Generalizing from our experience in intrusion detection, we show that the need to detect 'rare events' and 'anomalies' from very large volumes of data, with very high degree of precision, and often in real time, is needed in many application domains. This includes transaction fraud from the financial and e-commerce domains, claims fraud and off-prescription drug usage from the medical domain, audit selection from income and sales tax, alarms from home and industrial security systems, and health monitoring of vehicles b^@^S airborne and on the road. Drawing upon our experience from collaborative projects in all of these areas, we show how research in data mining for security informatics can have much broader impact. Our goal is to initiate a two way dialogue between the security community, and many of these areas. Biography Jaideep Srivastava is a professor at the University of Minnesota, where he has established and led a research laboratory which conducts research in the information and knowledge aspects of computing. He has supervised 24 Ph.D. dissertations and 50 M.S. theses, and authored or co-authored over 200 papers in refereed journals and conferences. Dr. Srivastava have served on the editorial boards of various journals, including IEEE TPDS, IEEE TKDE, and the VLDB journal. He has also served as Program and Conference Chair for a number of prominent conferences, especially in the area of data mining, and is on the Steering Committee for the PAKDD series of conferences. He has delivered a number of keynote addresses, plenary talks, and invited tutorials at major conferences. Dr. Srivastava has a very active interaction with the industry, in both consulting and executive roles. Specifically, during a 2-year sabbatical during 1999-2001, he lead a corporate data mining team at Amazon.com (www.amazon.com) and built a data analytics department at Yodlee (www.yodlee.com) from the ground up. More recently, he spent two years as the Chief Technology Officer for Persistent Systems (http://en.wikipedia.org/wiki/Persistent_Systems), where he helped organize an R&D division with a number of Centers of Excellence. In addition, he oversaw the redesign of the training and technical vitalization program for 2,200+ engineers. He has provided technology and technology strategy advice to a number of large corporations including Cargill, United Technologies, IBM, Honeywell, 3M, and Eaton. He has served in an advisory capacity to annumber of small companies, including Lancet Software and Infobionics. Dr. Srivastava has also played an active advisory role in the government sector. Specifically, he has served as the US federal government's expert witness in a nationally significant tax case. He has served as Senior Technology Advisor to the State of Minnesota, and is on the Technology Advisory Council to the Chief Minister of Maharashtra, India. Dr. Srivastava has a PhD from the University of California, Berkeley, and bachelors in computer science from IIT Kanpur, India. He is a Fellow of the IEEE. |
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