scholar.google.com › citations
Mar 15, 2019 · In this paper, we focus on and quantify the limitations of the current learning-assisted grammar-based fuzzing, ie, how ineffective it is at generating ...
The limitations of the current learning-assisted grammar-based fuzzing are focused on, i.e, how ineffective it is at generating instruction sequences ...
Fuzzing is the process of finding security vulnerabilities in code by creating inputs that will activate the exploits. Grammar-based fuzzing uses a grammar, ...
Missing: Quantifying | Show results with:Quantifying
A systematic review of fuzzing based on machine learning techniques
www.ncbi.nlm.nih.gov › PMC7433880
This paper reviews the research progress of using machine learning techniques for fuzz testing in recent years, analyzes how machine learning improves the ...
This chapter introduces grammars as a simple means to specify input languages, and to use them for testing programs with syntactically valid inputs.
Missing: Quantifying Assisted
We discuss (and measure) the tension between conflicting learning and fuzzing goals: learning wants to capture the structure of well-formed inputs, while ...
People also search for
This approach allows for the learning of a generative model for instruction sequences by training a hybrid character/token-level recursive neural network, ...
Missing: Limitations | Show results with:Limitations
In this paper, we study how to improve the coverage and effectiveness of grammar-based fuzzers for network proto- cols through automated learning of protocol ...
Missing: Quantifying Limitations
People also ask
What are the disadvantages of fuzzing?
What is grammar-based fuzzing?
Specifically, this review discusses successful applications of ML to fuzzing, briefly explores challenges encountered, and motivates future research to address ...
Our study highlights the transformative role of ML-based methods in seed selection, message generation for system fuzzing, and fuzzing grammar optimisation.
Missing: Quantifying | Show results with:Quantifying