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On the Effectiveness of NX, SSP, RenewSSP, and ASLR against Stack Buffer Overflows

Authors: Hector Marco Gisbert; Ismael Ripoll;

On the Effectiveness of NX, SSP, RenewSSP, and ASLR against Stack Buffer Overflows

Abstract

Stack Smashing Protector (SSP), Address-Space Layout Randomization (ASLR) and Non-executable (NX) are techniques for defending systems against buffer overflow attacks but not limited to them. These mechanism are available in modern operating systems like Android, GNU/Linux and Windows. Unfortunately, to keep up with the rapidly evolving landscape of cyber-security it is necessary to reassess the effectiveness of these protection techniques to avoid a false sense of security. This paper assess the effectiveness of these techniques against stack buffer overflow exploitation. Our study indicates that the SSP technique is the most effective against stack buffer overflows. On forking servers, the ASLR technique is almost useless on 32-bit architectures due to the limited entropy provided by the size of the address space. The recently proposed technique Renew SSP, which is an improvement of the well known SSP, outperforms the original SSP in all the cases, it is highly effective against the dangerous byte-for-byte attack and on systems with low secret entropy as x86 and ARM.

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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!
22
Top 10%
Top 10%
Top 10%
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