Using Low-Level Architectural Features for Configuration InfoSec in a General-Purpose Self-Configurable System

Unique characteristics of biological systems are described, and similarities are made to certain computing architectures. The security challenges posed by these characteristics are discussed. A method of securely isolating portions of a design using introspective capabilities of a fine-grain self-configurable device is presented. Experimental results are discussed, and plans for future work are given.

[1]  Nicholas J. Macias,et al.  Self-assembling circuits with autonomous fault handling , 2002, Proceedings 2002 NASA/DoD Conference on Evolvable Hardware.

[2]  Chris Dwyer,et al.  Design tools for a DNA-guided self-assembling carbon nanotube technology , 2004 .

[3]  M.H. Zarifi,et al.  Design and implementation of MP3 decoder using partial dynamic reconfiguration on Virtex-4 FPGAs , 2008, 2008 International Conference on Computer and Communication Engineering.

[4]  Sorin Hintea,et al.  Bio-Inspired Computational Intelligence for the Hardware of Adaptive Systems , 2009 .

[5]  Peter M. Athanas,et al.  Application of Self-Configurability for Autonomous, Highly-Localized Self-Regulation , 2007, Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007).

[6]  P. D. Tougaw,et al.  Logical devices implemented using quantum cellular automata , 1994 .

[7]  Sorin Hintea,et al.  Bio-Inspired Technologies for the Hardware of Adaptive Systems - Real-World Implementations and Applications , 2009, Studies in Computational Intelligence.

[8]  Nicholas J. Macias,et al.  Obtaining quadrillion-transistor logic systems despite imperfect manufacture, hardware failure, and incomplete system specification , 2004 .

[9]  Nicholas J. Macias,et al.  Defect-tolerant, fine-grained parallel testing of a Cell Matrix , 2002, SPIE ITCom.

[10]  Adam C. Cabe,et al.  Designing CMOS/molecular memories while considering device parameter variations , 2007, JETC.

[11]  Joos Vandewalle,et al.  Hardware architectures for public key cryptography , 2003, Integr..

[12]  A. Roli Artificial Neural Networks , 2012, Lecture Notes in Computer Science.

[13]  Enrico Petraglio Fault Tolerant Self-Replicating Systems , 2004 .

[14]  Clive ldMax rd Maxfield,et al.  The design warrior's guide to FPGAs , 2004 .

[15]  Kenji Toda,et al.  Bitstream encryption and authentication with AES-GCM in dynamically reconfigurable systems , 2008, 2008 International Conference on Field Programmable Logic and Applications.

[16]  Jürgen Becker,et al.  Exploitation of the External JTAG Interface for Internally Controlled Configuration Readback and Self-Reconfiguration of Spartan 3 FPGAs , 2008, 2008 IEEE Computer Society Annual Symposium on VLSI.

[17]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[18]  Nicholas J. Macias,et al.  The PIG paradigm: the design and use of a massively parallel fine grained self-reconfigurable infinitely scalable architecture , 1999, Proceedings of the First NASA/DoD Workshop on Evolvable Hardware.

[19]  B. Yegnanarayana,et al.  Artificial Neural Networks , 2004 .

[20]  L. Durbeck,et al.  The Cell Matrix: an architecture for nanocomputing , 2001 .