Control-flow checking by software signatures

Abstract

This paper presents a new signature monitoring technique, CFCSS (Control Flow Checking by Software Signatures); CFCSS is a pure software method that checks the control flow of a program using assigned signatures. An algorithm assigns a unique signature to each node in the program graph and adds instructions for error detection. Signatures are embedded in the program during compilation time using the constant field of the instructions and compared with run-time signatures when the program is executed. Another algorithm reduces the code size and execution time overhead caused by checking instructions in CFCSS. A "branching fault injection experiment" was performed with benchmark programs. Without CFCSS, an average of 33.7% of the injected branching faults produced undetected incorrect outputs; however, with CFCSS, only 3.1% of branching faults produced undetected incorrect outputs. Thus it is possible to increase error detection coverage for control flow errors by an order of magnitude using CFCSS. The distinctive advantage of CFCSS over previous signature monitoring techniques is that CFCSS is a pure software method, i.e., it needs no dedicated hardware such as a watchdog processor for control flow checking. A watchdog task in multitasking environment also needs no extra hardware, but the advantage of CFCSS over a watchdog task is that CFCSS can be used even when the operating system does not support multitasking.

Application-Based Analysis of Register File Criticality for Reliability Assessment in Embedded Microprocessors

“…The first step in this approach consists on the application profiling (dynamic code analysis) to optimize the number of checkpoints introduced into the application code, which are inserted in the second step by means of the application of a well-known control flow technique such as CFCSS [28]. Unlike this controlflow protection technique, our metric is aimed at identifying the most critical registers from the microprocessor register file for a further application of data protection schemes (out of the scope of the present work).…”

Selective SWIFT-R

“…The so-called Software Implemented Hardware Fault Tolerance (SIHFT ) [25] techniques can be divided in two main categories according to the type of error they pretend to detect/correct: errors that may affect the control flow execution [26]; or errors that may affect the program data [27].…”

“…Some examples of these include ControlFlow Checking by Software Signatures (CFCSS ) [26], Assertions for Control Flow Checking (ACFC ) [28], Yet Another Control flow Checking Approach (YACCA) [29], and Control-flow Error Detection through Assertions (CEDA) [30]. Moreover, those approaches included in the second group are mainly based on the N-versions programming approach [31], which can be applied at different granularity levels: program [11,32], procedure [33], and the most commonly used, instruction level [27,[34][35][36].…”

“…Some of them apply redundancy to highlevel source code (e.g., C language) by means of automatic transformation rules [37], whereas others use instruction redundancy at a low level (assembly code) in order to reduce the code overhead and performance degradation, and improve detection rates [26,27,36]. Only a few of these techniques have been extended to allow system recovery, but they incur, as a consequence, in higher overheads in terms of code size and execution time [17,38].…”

A Tunable, Software-Based DRAM Error Detection and Correction Library for HPC

“…Control-flow checking is another area of research that attempts to detect the effects of SDCs in applications [5]. Unfortunately control-flow integrity verification does not necessarily protect against SDCs that only alter data without affecting the execution path of an application.…”