%ASamuel Jero, Maria%BJournal Name: Proceedings of the ... Innovative Applications of Artificial Intelligence Conference; Journal Volume: 11; Journal Issue: 1 %D2019%I %JJournal Name: Proceedings of the ... Innovative Applications of Artificial Intelligence Conference; Journal Volume: 11; Journal Issue: 1 %K %MOSTI ID: 10099364 %PMedium: X %TLeveraging Textual Specifications for Grammar-based Fuzzing of Network Protocols. %XGrammar-based fuzzing is a technique used to find soft- ware vulnerabilities by injecting well-formed inputs generated following rules that encode application semantics. Most grammar-based fuzzers for network protocols rely on human experts to manually specify these rules. In this work we study automated learning of protocol rules from textual specifications (i.e. RFCs). We evaluate the automatically extracted protocol rules by applying them to a state-of-the-art fuzzer for transport protocols and show that it leads to a smaller number of test cases while finding the same attacks as the system that uses manually specified rules. %0Journal Article