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Δημοσιεύσεις σε Διεθνή Περιοδικά (Journals)


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


A. Loukas, D. Damopoulos, S. A. Menesidou, Maria Eleni Skarkala, G. Kambourakis, S. Gritzalis, MILC: A Secure and Privacy-Preserving Mobile Instant Locator with Chatting, Information System Frontiers, Vol. 14, No. 3, pp. 481-497, 2012, Springer, http://link.springer.com/content/pd..., indexed in SCI-E, IF = 0.851
 

Abstract
The key issue for any mobile application or service is the way it is delivered and experienced by users, who eventually may decide to keep it on their software portfolio or not. Without doubt, security and privacy have both a crucial role to play towards this goal. Very recently, Gartner has identified the top ten of consumer mobile applications that are expected to dominate the market in the near future. Among them one can earmark location-based services in number 2 and mobile instant messaging in number 9. This paper presents a novel application namely MILC that blends both features. That is, MILC offers users the ability to chat, interchange geographic co-ordinates and make Splashes in real-time. At present, several implementations provide these services separately or jointly, but none of them offers real security and preserves the privacy of the end-users at the same time. On the contrary, MILC provides an acceptable level of security by utilizing both asymmetric and symmetric cryptography, and most importantly, put the user in control of her own personal information and her private sphere. The analysis and our contribution are threefold starting from the theoretical background, continuing to the technical part, and providing an evaluation of the MILC system. We present and discuss several issues, including the different services that MILC supports, system architecture, protocols, security, privacy etc. Using a prototype implemented in Google’s Android OS, we demonstrate that the proposed system is fast performing, secure, privacy-preserving and potentially extensible.

Επιστημονικά Συνέδρια (Conferences)


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


Maria Eleni Skarkala, Hannu Toivonen, Pirjo Moen, M. Maragoudakis, S. Gritzalis, L. Mitrou, Privacy Preservation by k-Anonymization of Weighted Social Networks, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, P. Yu, K. Carley et al., (eds), pp. 423-428, Aug, 2012, Istanbul, Turkey, IEEE CPS Conference Publishing Services, http://dl.acm.org/ft_gateway.cfm?id...
 

Abstract
Privacy preserving analysis of a social network aims at a better understanding of the network and its behavior, while at the same time protecting the privacy of its individuals. We propose an anonymization method for weighted graphs, i.e., for social networks where the strengths of links are important. This is in contrast with many previous studies which only consider unweighted graphs. Weights can be essential for social network analysis, but they pose new challenges to privacy preserving network analysis. In this paper, we mainly consider prevention of identity disclosure, but we also touch on edge and edge weight disclosure in weighted graphs. We propose a method that provides k-anonymity of nodes against attacks where the adversary has information about the structure of the network, including its edge weights. The method is efficient, and it has been evaluated in terms of privacy and utility on real word datasets.

Maria Eleni Skarkala, M. Maragoudakis, S. Gritzalis, L. Mitrou, Privacy Preserving Tree Augmented Naïve Bayesian Multi – party Implementation on Horizontally Partitioned Databases, TrustBus 2011 8th International Conference on Trust, Privacy and Security of Digital Business, S. Furnell, C. Lambrinoudakis, and G. Pernul, (eds), pp. 62 - 73, Aug, 2011, Toulouse, France, Lecture Notes in Computer Science LNCS, Springer, http://link.springer.com/content/pd...
 

Abstract
The evolution of new technologies and the spread of the Internet have led to the exchange and elaboration of massive amounts of data. Simultaneously, intelligent systems that parse and analyze patterns within data are gaining popularity. Many of these data contain sensitive information, a fact that leads to serious concerns on how such data should be managed and used from data mining techniques. Extracting knowledge from statistical databases is an essential step towards deploying intelligent systems that assist in making decisions, but also must preserve the privacy of parties involved. In this paper, we present a novel privacy preserving data mining algorithm from statistical databases that are horizontally partitioned. The novelty lies to the multi-candidate election schema and its capabilities of being a basic foundation for a privacy preserving Tree Augmented Naïve Bayesian (TAN) classifier, in order to obviate disclosure of personal information.

Βιβλία


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


Κεφάλαια σε Βιβλία


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


Επιμέλεια Πρακτικών Διεθνών Συνεδρίων


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.