Prospex: Protocol Specification Extraction
By Paolo Milani Comparetti, Gilbert Wondracek, Christopher Krügel, Engin Kirda. IEEE Symposium on Security and Privacy, 2009
316 citations recorded by the source corpus.
Subfields: Information Systems, Software, Signal Processing
View Paper: https://www.semanticscholar.org/paper/540256bd5be8ac0af9a71d3247f0dbc2d83f5070
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Christopher Krügel
- Giovanni Vigna
- Guofei Gu
- Erik Poll
- Joeri de Ruiter
- Tao Wei
- X. Zhang
- Abhik Roychoudhury
In Software
- Marcel Böhme
- Abhik Roychoudhury
- Giovanni Vigna
- Guofei Gu
- Erik Poll
- Joeri de Ruiter
- Edward J. Schwartz
- Tao Wei
In Signal Processing
- Giovanni Vigna
- Christopher Krügel
- Guofei Gu
- Edward J. Schwartz
- Sang Kil Cha
- Erik Poll
- Joeri de Ruiter
- Manuel Egele
Citations in the corpus
- SOK: (State of) The Art of War: Offensive Techniques in Binary Analysis (2016, background): “Others introduce work from protocol analysis to improve fuzzing coverage [22].”
- AFLNET: A Greybox Fuzzer for Network Protocols (2020, background): “In terms of state machine inferencing, we can distinguish passive learning approaches [23], [24] that learn the protocol state machine from a corpus of message sequences and active learning approaches [25]– [27] that leverage Angluin’s L∗ algorithm to actively query the protocol implementations with”
- Protocol State Fuzzing of TLS Implementations (2015, methodology): “For example, in [14] passive learning techniques are used on observed network traffic to infer a state machine of the protocol used by a botnet.”
- TaintScope: A Checksum-Aware Directed Fuzzing Tool for Automatic Software Vulnerability Detection (2010, methodology): “Recently, several protocol reverse engineering techniques [26], [47], [34], [31] are proposed to automatically extract 2010 IEEE Symposium on Security and Privacy”
- The Art, Science, and Engineering of Fuzzing: A Survey (2018, background): “Although there is an abundance of published research on the topic of automated input format and protocol reverse engineering [69], [48], [146], [66], [31], only a few fuzzers leverage these techniques.”
- Automatic Reverse Engineering of Data Structures from Binary Execution (2010, background): “64 -9416 int 4 bfffd164 67 45 8b 6b -8227 char[28] 28 bfffd609 00 .”