TY - JOUR
T1 - EPIC
T2 - Efficient privacy-preserving scheme with EtoE data integrity and authenticity for AMI networks
AU - Alsharif, Ahmad
AU - Nabil, Mahmoud
AU - Tonyali, Samet
AU - Mohammed, Hawzhin
AU - Mahmoud, Mohamed
AU - Akkaya, Kemal
N1 - Funding Information:
Manuscript received August 28, 2018; revised October 25, 2018; accepted November 12, 2018. Date of publication November 21, 2018; date of current version May 8, 2019. This work was supported by the U.S. National Science Foundation under Grant CNS-1619250. (Corresponding author: Ahmad Alsharif.) A. Alsharif is with the Department of Computer Science, University of Central Arkansas, Conway, AR 72035 USA, and also with the Department of Electrical and Computer Engineering, Tennessee Tech University, Cookeville, TN 38505 USA (e-mail: aalsharif@uca.edu).
Publisher Copyright:
© 2014 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - In this paper, we propose EPIC, an efficient and privacy-preserving data collection scheme with EtoE data integrity verification for advanced metering infrastructure networks. Using efficient cryptographic operations, each meter should send a masked reading to the utility such that all the masks are canceled after aggregating all meters' masked readings, and thus the utility can only obtain an aggregated reading to preserve consumers' privacy. The utility can verify the aggregated reading integrity without accessing the individual readings to preserve privacy. It can also identify the attackers and compute electricity bills efficiently by using the fine-grained readings without violating privacy. Furthermore, EPIC can resist collusion attacks in which the utility colludes with a relay node to extract the meters' readings. A formal proof and probabilistic analysis are used to evaluate the security of EPIC, and ns-3 is used to implement EPIC and evaluate the network performance. In addition, we compare EPIC to existing data collection schemes in terms of overhead and security/privacy features.
AB - In this paper, we propose EPIC, an efficient and privacy-preserving data collection scheme with EtoE data integrity verification for advanced metering infrastructure networks. Using efficient cryptographic operations, each meter should send a masked reading to the utility such that all the masks are canceled after aggregating all meters' masked readings, and thus the utility can only obtain an aggregated reading to preserve consumers' privacy. The utility can verify the aggregated reading integrity without accessing the individual readings to preserve privacy. It can also identify the attackers and compute electricity bills efficiently by using the fine-grained readings without violating privacy. Furthermore, EPIC can resist collusion attacks in which the utility colludes with a relay node to extract the meters' readings. A formal proof and probabilistic analysis are used to evaluate the security of EPIC, and ns-3 is used to implement EPIC and evaluate the network performance. In addition, we compare EPIC to existing data collection schemes in terms of overhead and security/privacy features.
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U2 - 10.1109/JIOT.2018.2882566
DO - 10.1109/JIOT.2018.2882566
M3 - Article
AN - SCOPUS:85057150979
SN - 2327-4662
VL - 6
SP - 3309
EP - 3321
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 2
M1 - 8542715
ER -