Paper Info
Title
TaintHLS: High-Level Synthesis For Dynamic Information Flow Tracking
Abstract
Dynamic information flow tracking (DIFT) is a technique to track potential security vulnerabilities in software and hardware systems at run time. Untrusted data are marked with tags (tainted), which are propagated through the system and their potential for unsafe use is analyzed to prevent them. DIFT is not supported in heterogeneous systems especially hardware accelerators. Currently, DIFT is manually generated and integrated into the accelerators. This process is error-prone, potentially hurting the process of identifying security violations in heterogeneous systems. We present TaintHLS, to automatically generate a micro-architecture to support baseline operations and a shadow microarchitecture for intrinsic DIFT support in hardware accelerators while providing variable granularity of taint tags. TaintHLS offers a companion high-level synthesis (HLS) methodology to automatically generate such DIFT-enabled accelerators from a high-level specification. We extended a state-of-the-art HLS tool to generate DIFT-enhanced accelerators and demonstrated the approach on numerous benchmarks. The DIFT-enabled accelerators have negligible performance and no more than 30% hardware overhead.
Year
DOI
Venue
2019
10.1109/tcad.2018.2834421
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Keywords
Field
DocType
Hardware,Software,Security,Computer architecture,Random access memory,Registers,Central Processing Unit
Information flow (information theory),Central processing unit,Hardware security module,Computer science,High-level synthesis,Real-time computing,Software,Granularity,Microarchitecture,Embedded system
Journal
Volume
Issue
ISSN
38
5
0278-0070
Citations 
PageRank 
References 
4
0.43
0
Authors
5
Name
Order
Citations
PageRank
Christian Pilato132932.19
Kaijie Wu272456.35
Siddharth Garg367555.14
Ramesh Karri42968224.90
Francesco Regazzoni560362.00