Protecting sensitive information is currently an increasingly difficult task. Brute-force attacks (BFA) consist on an attacker testing sequentially the possible values of a protected information until the correct one is discovered. BFA has shown to be one of the major threats to network security and prevalent despite the computational burden on the attacker side. A machine compromised by a brute force attack can cause serious damages such as distributing sensitive information and participating in distributed attacks. Protection against BFA is based on enhancing the set of possible values of the protected information or limiting the number of queries. The latter is circumvented by using massive botnets, each bot querying potential passwords. On the other hand, when the secret range increases, BFA becomes by definition a harder task. In Smart Grids (SG), security has always been a primary concern. According to, large quantities of data are collected from various applications in SG, such as smart metering substation state monitoring, electric energy data acquisition and smart home, where practically all data are sensitive.

Papers:

S. Salamatian, W. Huleihel, A. Beirami, A. Cohen, and M. Medard, ´ “Why Botnets Work: Distributed Brute-Force Attacks Need No Synchronization”, IEEE Transactions on Information Forensics and Security, Vol. 14, No. 9, September 2019, DOI: 10.1109/TIFS.2019.2895955.

T. Liu, Y. Liu, Y. Mao, Y. Sun, X. Guan, W. Gong, and S. Xiao, “A Dynamic Secret-Based Encryption Scheme for Smart Grid Wireless Communication”, IEEE Transactions on Smart Grid Vol. 5, Issue 3, pp. 1175-1182, 2014, DOI: 10.1109/TSG.2013.2264537.

Z. Guan, G. Si, X. Du, P. Liu, Z. Zhang, and Z. Zhou, “Protecting user privacy based on secret sharing with fault tolerance for big data in smart grid”, 2017 IEEE International Conference on Communications (ICC), 2017, DOI: 10.1109/ICC.2017.7997371.

X. Li, H. Liang, and X.-G. Xia, “A Robust Chinese Remainder Theorem with its applications in frequency estimation from undersampled waveforms”, IEEE Transactions on Signal Processing, Vol. 57, Issue 11, pp. 4314-4322, 2009, DOI: 10.1109/TSP.2009.2025079.