Date of Award

Fall 12-2018

Degree Type


Degree Name


Degree Program

Computer Science


Computer Science

Major Professor

Vassil Roussev

Second Advisor

Joe Sylve

Third Advisor

Christopher Summa

Sixth Advisor



In this paper, we present a working research prototype codeid-elf for ELF binaries based on its Windows counterpart codeid, which can identify kernels through relocation entries extracted from the binaries. We show that relocation-based signatures are unique and distinct and thus, can be used to accurately determine Linux kernel versions and derandomize the base address of the kernel in memory (when kernel Address Space Layout Randomization is enabled). We evaluate the effectiveness of codeid-elf on a subset of Linux kernels and find that the relocations in kernel code have nearly 100\% code coverage and low similarity (uniqueness) across various kernels. Finally, we show that codeid-elf, which leverages relocations in kernel code, can detect all kernel versions in the test set with almost 100% page hit rate and nearly zero false negatives.


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Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License