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2017-02-14
L. Rivière, J. Bringer, T. H. Le, H. Chabanne.  2015.  "A novel simulation approach for fault injection resistance evaluation on smart cards". 2015 IEEE Eighth International Conference on Software Testing, Verification and Validation Workshops (ICSTW). :1-8.

Physical perturbations are performed against embedded systems that can contain valuable data. Such devices and in particular smart cards are targeted because potential attackers hold them. The embedded system security must hold against intentional hardware failures that can result in software errors. In a malicious purpose, an attacker could exploit such errors to find out secret data or disrupt a transaction. Simulation techniques help to point out fault injection vulnerabilities and come at an early stage in the development process. This paper proposes a generic fault injection simulation tool that has the particularity to embed the injection mechanism into the smart card source code. By its embedded nature, the Embedded Fault Simulator (EFS) allows us to perform fault injection simulations and side-channel analyses simultaneously. It makes it possible to achieve combined attacks, multiple fault attacks and to perform backward analyses. We appraise our approach on real, modern and complex smart card systems under data and control flow fault models. We illustrate the EFS capacities by performing a practical combined attack on an Advanced Encryption Standard (AES) implementation.

2015-05-06
Kundu, S., Jha, A., Chattopadhyay, S., Sengupta, I., Kapur, R..  2014.  Framework for Multiple-Fault Diagnosis Based on Multiple Fault Simulation Using Particle Swarm Optimization. Very Large Scale Integration (VLSI) Systems, IEEE Transactions on. 22:696-700.

This brief proposes a framework to analyze multiple faults based on multiple fault simulation in a particle swarm optimization environment. Experimentation shows that up to ten faults can be diagnosed in a reasonable time. However, the scheme does not put any restriction on the number of simultaneous faults.

2015-05-01
Xuezhong Guan, Jinlong Liu, Zhe Gao, Di Yu, Miao Cai.  2014.  Power grids vulnerability analysis based on combination of degree and betweenness. Control and Decision Conference (2014 CCDC), The 26th Chinese. :4829-4833.

This paper proposes an analysis method of power grids vulnerability based on complex networks. The method effectively combines the degree and betweenness of nodes or lines into a new index. Through combination of the two indexes, the new index can help to analyze the vulnerability of power grids. Attacking the line of the new index can obtain a smaller size of the largest cluster and global efficiency than that of the pure degree index or betweenness index. Finally, the fault simulation results of IEEE 118 bus system show that the new index can reveal the vulnerability of power grids more effectively.