Argumentation-based Security for Social Good
Auteurs : Karafili E., Kakas A.C., Spanoudakis N.I., Lupu E.C.
Publication : In the AAAI 2017 Spring Symposium on AI for Social Good (AISOC17), Stanford University, March 27-29, 2017
The increase of connectivity and the impact it has in every day life is raising new and existing security problems that are becoming important for social good. We introduce two particular problems: cyber attack attribution and regulatory data sharing. For both problems, decisions about which rules to apply, should be taken under incomplete and context dependent information. The solution we propose is based on argumentation reasoning, that is a well suited technique for implementing decision making mechanisms under conflicting and incomplete information. Our proposal permits us to identify the attacker of a cyber attack and decide the regulation rule that should be used while using and sharing data. We illustrate our solution through concrete examples.