In data-communication networks, network reliability is of great concern to both network operators and customers. Therefore, network operators want to determine what services could be affected by software vulnerabilities being exploited that are present within their data-communication network. To determine what services could be affected by a software vulnerability being exploited, it is fundamentally important to know the ongoing tasks in a network. A particular task may depend on multiple network services, spanning many network devices. Unfortunately, dependency details are often not documented and are difficult to discover by relying on human expert knowledge. In monitored networks huge amounts of data are available and by applying data mining techniques, we are able to extract information of ongoing network activities. From a data mining perspective, we are interested to test the potential of applying data mining techniques to real-life applications. © 2016 The Authors and IOS Press.
|Title of host publication
|Proceedings of the 1st International Workshop on AI for Privacy and Security, PrAISe@ECAI 2016, The Hague, Netherlands,29.08.-02.09.
|Number of pages
|1583 - 1585
|Published - 01.08.2016
|22nd European Conference on Artificial Intelligence
- The Hague, Netherlands
Duration: 29.08.2016 → 02.09.2016
Conference number: 126200
DFG Research Classification Scheme
- 409-06 Information Systems, Process and Knowledge Management