Degree Type

Thesis

Date of Award

2016

Degree Name

Master of Science

Department

Electrical and Computer Engineering

Major

Computer Engineering

First Advisor

Joseph Zambreno

Abstract

Software written in programming languages that permit manual memory management, such as C and C++, are often littered with exploitable memory errors. These memory bugs enable attackers to leak sensitive information, hijack program control flow, or otherwise compromise the system and are a critical concern for computer security. Many runtime monitoring and protection approaches have been proposed to detect memory errors in C and C++ applications, however, they require source code recompilation or binary instrumentation, creating compatibility challenges for applications using proprietary or closed source code, libraries, or plug-ins. This work introduces a new approach for detecting heap memory errors that does not require applications to be recompiled or instrumented. We show how to leverage the calling convention of a processor to track all dynamic memory allocations made by an application during runtime. We also present a transparent tracking and caching architecture to efficiently verify program heap memory accesses. Security analysis using a software prototype shows our architecture detects 98% of heap memory errors from selected test cases in the Juliet Test Suite and real-world exploits. Performance simulations of our architecture using SPEC benchmarks and real-world application workloads show our architecture achieves hit rates over 95% for a 256-entry cache, resulting in only 2.9% runtime overhead.

Copyright Owner

Alex Ross Grieve

Language

en

File Format

application/pdf

File Size

76 pages

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