The distributed nature of peer-to-peer and ad-hoc networks makes "securing" them against the activities of even a small fraction of malicious users particularly challenging.

• Time coordination in P2P and ad-hoc networks

• "Physical" information transport in mobile networks

• Secure Distributed Hash Tables (DHTs)

• Secure distributed voting systems

People: Enoch Peserico (contact person)

The proliferation of wideband connections, while opening the market to a large number of innovative web-based applications, also turns any home PC into a target for intrusions and drafting into botnets. Furthermore, the "Connected World" vision at the very base of both the Internet of Things and the Cyber-Physical systems makes every object both a target for an attack and a possible injection point for malware. Thus, the capability to exchange electronic data in a secure framework is a basic requirement of the economy of our modern society, and impacts on several other fields (e.g.

The research in Information Access and Search Engines is concerned with the design, the integration and the evaluation of advanced, scalable systems based on theoretical statistical and probabilistic methods. The combination of theoretical statistical and probabilistic methods, either classical or not classical (e.g. quantum), aims at evolving search engines to more advanced and complex search machines. The group is currently active in:

• Bagging algorithms for multivariate selection of features with local similarity

•  Mining of probabilistic dependencies between features

People: Silvana Badaloni (contact person)

• Biometric systems, to study novel approaches for biometric encryption, to develop new biometric systems (several biometric characteristics are studied: fingerprint/face/palm/knuckleprint/on-line signature/iris/hand identification).

•  Bioinformatics, to develop new methods for protein, peptide and gene classification, data mining for medical diagnosis. These tools are very useful for speeding the process of developing new drugs.

Nowadays, large amounts of data are produced in a wide spectrum of domains. The effective exploitation of this data, reckoned as one of the most important scientific challenges of the 21st century, requires a sharp paradigm shift with respect to traditional computing. Our research concerns the design, analysis, and engineering of algorithmic techniques for dealing with big data, exploring tradeoffs between computation efficiency and solution quality.Specific areas of investigation are listed below.

Support to medical diagnosis with classification and data mining techniquesPeople: Loris Nanni (contact person), Carlo Fantozzi, Andrea Pietracaprina, Geppino Pucci