2014R. Beraldi, M. Paolucci, F. Petroni, L. Querzoni
LCBM: Statistics-based Parallel Collaborative Filtering
To appear in Proceedings of the 17th International Conference on Business Information Systems (BIS), 2014
"In the last ten years, recommendation systems evolved from novelties to powerful business tools, deeply changing the internet industry. Collaborative Filtering (CF) represents today’s a widely adopted strategy to build recommendation engines. The most advanced CF techniques (i.e. those based on matrix factorization) provide high quality results, but may incur prohibitive computational costs when applied to very large data sets. In this paper we present Linear Classifier of Beta distributions Means (LCBM), a novel collaborative filtering algorithm for binary ratings that is (i) inherently parallelizable and (ii) provides results whose quality is on-par with state-of-the-art solutions (iii) at a fraction of the computational cost."
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G. Lodi, L. Aniello, G. Di Luna, R. Baldoni
An Event-based Platform for Collaborative Threats Detection and Monitoring
Information Systems, volume 39, pages 175-195, 2014
"Organizations must protect their information systems from a variety of threats. Usually they employ isolated defenses such as firewalls, intrusion detection and fraud monitoring systems, without cooperating with the external world. Organizations belonging to the same markets (e.g., financial organizations, telco providers) typically suffer from the same cyber crimes. Sharing and correlating information could help them in early
detecting those crimes and mitigating the damages.
The paper introduces the Semantic Room (SR) abstraction which enables the development of collaborative and contractually regulated eventbased platforms, on the top of Internet, where data from different information systems are shared and correlated to detect and timely react to coordinated Internet-based security threats (e.g., port scans, botnet) and frauds. The paper describes the SR life cycle management and, to show the flexibility of the abstraction, it proposes the design, implementation and validation of two SRs. The first SR detects inter-domain port scan attacks, the second monitors frauds performed in Italy.
In both cases, we use real data traces for demonstrating the effectiveness of our approach. In the first SR, high detection accuracy and small detection delays are achieved whereas in the second, new fraud evidences and investigation instruments are provided to law enforcement agencies."
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