The Fun in Fuzzing

The Evolving Art of Fuzzing

H-Fuzzing: A New Heuristic Method for Fuzzing Data Generation

How to efficiently reduce the fuzzing data scale while assuring high fuzzing veracity and vulnerability coverage is a pivotal issue in program fuzz test. This paper proposes a new heuristic method for fuzzing data generation named with H-Fuzzing. H-Fuzzing achieves a high program execution path coverage by retrieving the static information and dynamic property from the program. Our experiments ...

Deep Reinforcement Fuzzing

Fuzzing is the process of finding security vulnerabilities in input-processing code by repeatedly testing the code with modified inputs. In this paper, we formalize fuzzing as a reinforcement learning problem using the concept of Markov decision processes. This in turn allows us to apply state-of-theart deep Q-learning algorithms that optimize rewards, which we define from runtime properties of...

examining the fun factors and age differences in attitudes toward workplace fun in modern companies

this paper aims to examine the fun concept and age differences in attitudes toward workplace fun. the authors review the literature on workplace fun and generational theory. the fun in workplace was measured with karl et al.’s (2005) and generational cohort was measured by the respondents’ birth year using a sample of 296 workers at a industrial company in south west of tehran. according to res...

Fuzzing: The State of the Art)

Fuzzing is an approach to software testing where the system being tested is bombarded with test cases generated by another program. The system is then monitored for any flaws exposed by the processing of this input. While the fundamental principles of fuzzing have not changed since the term was first coined, the complexity of the mechanisms used to drive the fuzzing process have undergone signi...