Results 221 to 230 of about 432 (243)

A Survey of Hybrid Fuzzing based on Symbolic Execution

Proceedings of the 2020 International Conference on Cyberspace Innovation of Advanced Technologies, 2020
Fuzzing has now developed into an efficient method of vulnerability mining. Symbolic execution is also a popular software vulnerability mining technology. Both are research hotspots in the field of network and information security. Hybrid fuzzing is the addition of symbolic execution technology on the basis of traditional fuzzing, and has now developed
Tao Zhang 0079, Yu Jiang, Runsheng Guo 0001, Xiaoran Zheng, Hui Lu 0005   +4 more
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FEFuzzer: Hybrid Files Fuzzing Tool

2021
Fuzzing is one of the most effective techniques for finding bugs and mining potential vulnerabilities in applications. In the fuzzing test, how to select test cases directly affects the result of the testing. In this paper, we propose a new method that can compute the effectiveness of test cases based on the genetic algorithm.
Tengfei Tu, Wei Zhang, Lu Rao, Zhao Li, Jiani Lu   +4 more
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PatchFuzz: An Efficient Way to Incorporate Patching With Hybrid Fuzzing

IEEE Transactions on Dependable and Secure Computing
Letian Sha, Yifei Huang, Fu Xiao
exaly   +2 more sources

A Hybrid Interface Recovery Method for Android Kernels Fuzzing

2020 IEEE 20th International Conference on Software Quality, Reliability and Security (QRS), 2020
Android kernel fuzzing is a research area of interest specifically for detecting kernel vulnerabilities which may allow attackers to obtain the root privilege. The number of Android mobile phones is increasing rapidly with the explosive growth of Android kernel drivers.
Shuaibing Lu, Xiaohui Kuang, Yuanping Nie, Zhechao Lin   +3 more
openaire   +1 more source

CherryPicker: A Parallel Solving and State Sharing Hybrid Fuzzing System [PDF]

IEEE Transactions on Dependable and Secure Computing
Hybrid testing, combining fuzz testing and concolic execution, has emerged as an effective technique for bug discovery. However, concolic execution becomes the performance bottleneck when applied to real-world software.
Qingyu Zhang 0005, Jiayi Lin 0007, Chenxin Sun, Chenxiong Qian, Xiapu Luo   +4 more
openaire   +2 more sources

Binary-oriented hybrid fuzz testing

2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS), 2015
In software security testing, fuzz testing and symbolic execution are two main testing techniques. Fuzz testing finds program bugs by executing the target program with random inputs it generates while monitoring the execution for abnormal behaviors. Though fuzz testing is able to explore deep into a program's state space efficiently, it usually cannot ...
Dong Fangquan, Dong Chaoqun, Zhang Yao, Lin Teng   +3 more
openaire   +1 more source

PBFuzz: Potential-aware Branch-oriented Hybrid Fuzzing

2024 4th International Symposium on Computer Technology and Information Science (ISCTIS)
Wensheng Guo
exaly   +2 more sources

Hybrid Way of Code Coverage Tracking in Fuzz

2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS), 2019
In software testing, code coverage can be one of the major metrics for evaluating the effectiveness of a test. Among all existing software testing methods, coverage-guided fuzzing is widely used nowadays, but the way it uses to obtain path coverage is mostly based on code instrumentation or emulation.
Hanyi Nie, Xu Zhou, Junnan Zhang
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A hybrid symbolic execution assisted fuzzing method

TENCON 2017 - 2017 IEEE Region 10 Conference, 2017
We present a new automated method for efficient detection of security vulnerabilities in binary programs. This method starts with a bounded symbolic execution of the target program so as to explore as many paths as possible. Constraints of the explored paths are collected and solved for inputs.
Li Zhang, Vrizlynn L. L. Thing
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Poster

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019
Hybrid fuzzers combine both fuzzing and concolic execution with the wish that the fuzzer will quickly explore input spaces and the concolic execution will solve the complex path conditions. However, existing hybrid fuzzers such as Driller cannot be effectively directed, for instance, towards unsafe system calls or suspicious locations, or towards ...
Juhwan Kim, Joobeom Yun
openaire   +1 more source