tailieunhanh - Enabling Collaborative Network Security with Privacy-Preserving Data Aggregation

Secure communication is an increasingly important application of the Internet. Without secure communication many existing social functions cannot benefit from modern technology. The primary example is commerce. The foundation of secure communication is cryptography, which enables secure communication through the use of keys. The management of these keys has proven to be a problem when the technology is taken into use. So called public key cryptography solves several of these problems, in particular it allows the keys to be transfered, in the form of a certificate, through unprotected communication cannels | Diss. ETH No. 19683 TIK-Schriftenreihe Nr. 125 Enabling Collaborative Network Security with Privacy-Preserving Data Aggregation A dissertation submitted to ETH Zurich for the degree of Doctor of Sciences presented by Martin Burkhart Master of Science ETH in Computer Science born February 6 1978 citizen of Bischofszell TG accepted on the recommendation of Prof. Dr. Bernhard Plattner examiner Dr. Xenofontas Dimitropoulos co-examiner Dr. Douglas Dykeman co-examiner 2011 Abstract Today there is a fundamental imbalance in cybersecurity. While attackers act more and more globally and coordinated . by using botnets their counterparts trying to manage and defend networks are limited to examine local information only. Collaboration across network boundaries would substantially strengthen network defense by enabling collaborative intrusion and anomaly detection. Also general network management tasks such as multi-domain traffic engineering and collection of performance statistics could substantially profit from collaborative approaches. Unfortunately privacy concerns largely prevent collaboration in multidomain networking. Data protection legislation makes data sharing illegal in certain cases especially if PII personally identifying information is involved. Even if it were legal sharing sensitive network internals might actually reduce security if the data fall into the wrong hands. Furthermore if data are supposed to be aggregated with those of a competitor sensitive business secrets are at risk. To address these privacy concerns a large number of data anonymization techniques and tools have been developed. The main goal of these techniques is to sanitize a data set before it leaves an administrative domain. Sensitive information is obscured or completely stripped off the data set. Sanitized properly organizations can safely share their anonymized data sets and aggregate information. However these anonymization techniques are generally not lossless. Therefore .