The Internet has become a complex system with increasing numbers of end-systems, applications, protocols and types of networks. Although we have a good understanding of how data is transferred over the network we cannot observe what happens with our data after sending and before receiving it - how packets traverse through the network and with which QoS characteristics remains unknown. Towards this objective we have developed a multi-hop packet tracking system intended to be used in experimental facilities, such as PlanetLab, where we have made our first tests. This paper describes our packet tracking realization and the results from our prototype implementation.

Before sharing or publishing network traffic data, anonymisation is regarded as a necessary step to protect the privacy of end users. This is especially important for Internet protocol (IP) addresses that could be resolved to a single end user. The most frequently used IP address anonymisation algorithms replace each IP address with a randomly or deterministically computed pseudonym. This static mapping however can present an anonymisation vulnerability, since pattern analysis or spoofing may allow to revert the mapping for selected addresses. In this paper, we propose a new algorithm for anonymising connection data, with the emphasis on IP packet-based network data captured on computer networks. It is worth noting however that except for IP packet-based network data, it is possible to use the proposed algorithm to anonymise any kind of connection data, such as aggregated packet data, t'packet flow data, telephone connection data as well as data associated with the usage of Web services or the accesses to Web servers. We first present the new algorithm and then show that it provides better security against reversing the IP-to-pseudonym mapping at the cost of slightly reduced usefulness of the anonymised data. Specifically, we evaluate the advantages of the proposed algorithm over the most frequently used IP address anonymisation algorithms in terms of the usefulness of the anonymised data with respect to network attack detection methods.

Passive network monitoring is required for the operation and maintenance of communication networks as well as to detect frauds and attacks. Typically, raw packet-level traffic traces are collected using suitable traffic probe devices and fed to monitoring applications (IDSs, antivirus, etc.) for analysis, with potential risks for the legitimate privacy rights of the customers. This paper aims to discuss the technical feasibility and the underlying research challenges of a two-tiered privacy-preserving network monitoring system, where carefully designed data protection mechanisms can coexist with suitably adapted monitoring applications.