Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Abstract
The efficient and structured analysis of unknown CMOS integrated circuits (ICs) has become a topic of great relevance in recent years. Up until now, different invasive [1], [2] and non-invasive [3], [4] strategies have been developed for procedure of analysis. However, invasive procedures always lead to the destruction of system under investigation. The non-invasive approaches published so far have the disadvantage that ICs are analysed by using complex algorithms. Here, no subdivision exists to avoid extensive analysis times in the case that only simple structures are investigated. Moreover, traditional procedures cannot automatically distinguish between input and output pin types, which is usually required in the investigation of real unknown integrated circuits. This paper presents an efficient non-invasive procedure to determine binary multi-input multi-output (MIMO) ICs by its input-output behaviour. It was implemented into analysis environment described in [5] and classifies unknown ICs by means of automata theory. A novel separation procedure is proposed in this paper to further minimise the IC analysis. All sections of the classification procedure are simulated and fully tested on ISCAS-85, ISCAS-89 and ISCAS-99 benchmark models of real ICs [6], [7] and the results are presented in this paper.
DOI
https://doi.org/10.21427/821p-5873
Recommended Citation
Brutscheck, M., Berger, S., Franke, M., Schwarzbacher, A., Becker, S.: Structural Division Procedure for Efficient IC Analysis. IET Irish Signals and Systems Conference, (ISSC 2008), pp.18-23. Galway, Ireland, 18-19 June, 2008. doi:10.21427/821p-5873
Publication Details
In IET Irish Signals and Systems Conference, 2008. (ISSC 2008),Galway, Ireland, 18-19 June 2008, pp.18-23. Available from http://0-ieeexplore.ieee.org.ditlib.dit.ie/search/srchabstract.jsp?arnumber=4780923&isnumber=4780919&punumber=4768732&k2dockey=4780923@ieecnfs&query=((dublin+institute+of+technology)%3Cin%3Emetadata)&pos=13&access=no