Fuzzing: A Survey and Reflection

PhD Qualifying Examination


Title: "Fuzzing: A Survey and Reflection"

by

Mr. Heqing HUANG


Abstract:

Fuzzing is known to be one of the most efficient methods to detect
real-world vulnerabilities. It repeatably running the target programs with
enormous malformed inputs generated automatically. Unlike heavyweight
analysis, fuzzing requires less knowledge of the targets so that it can be
easily scaled up to for large-size real-world programs. Its effectiveness
has also been proved in detecting server vulnerabilities such as
Heartbleed.

Nowadays, there are lots of studies related to improving the fuzzing
technique. Moreover, the increasing software's scale and usages are urged
for ensuring its qualities. Therefore, to help understand the methodology
of the state-of-the-art fuzzing techniques and its vast applications, we
conduct a thorough survey related to the existing literature and details
comparison among the different techniques.

Since fuzzing aims to detect the program flaws, the key problem is to
improve the quality of the generated inputs. Therefore, we first introduce
the conventional input generation approach. Afterward, we divide the
existing solutions into two categories. The first category relates to the
sophisticated input generation method.
With different optimization, fuzzing can generate inputs both efficiently
and effectively. The second category focuses on prioritizing the inputs
for fuzzing. This type of method makes fuzzing capable to tackle the path
explosion problem.

After conducting a thorough survey of the existing researches, we also
provide advice for potential future directions. We believe our survey will
shed light on our future work on fuzzing.


Date:                   Tuesday, 14 April 2020

Time:                   10:00am - 12:00noon

Zoom Meeting:           https://hkust.zoom.us/j/4348622853

Committee Members:      Dr. Charles Zhang (Supervisor)
                        Prof. Shing-Chi Cheung (Chairperson)
                        Dr. Dimitris Papadopoulos
                        Dr. Shuai Wang


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