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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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A heuristic fuzz test generator for Java native interface

Authors: Jinjing Zhao; Yan Wen 0001; Xiang Li 0078; Ling Pang; Xiaohui Kuang; Dongxia Wang 0001;

A heuristic fuzz test generator for Java native interface

Abstract

It is well known that once a Java application uses native C/C++ methods through the Java Native Interface (JNI), any security guarantees provided by Java might be invalidated by the native methods. So any vulnerability in this trusted native code can compromise the security of the Java program. Fuzzing test is an approach to software testing whereby the system being tested is bombarded with inputs generated by another program. When using fuzzer to test JNI programs, how to accurately reach the JNI functions and run through them to find the sensitive system APIs is the pre-condition of the test. In this paper, we present a heuristic fuzz generator method on JNI vulnerability detection based on the branch predication information of program. The result in the experiment shows our method can use less fuzzing times to reach more sensitive windows APIs in Java native code.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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