At the cross roads of lattice-based and homomorphic encryption to secure data aggregation in smart grid

Author(s):  
Rihem Ben Romdhane ◽  
Hamza Hammami ◽  
Mohamed Hamdi ◽  
Tai-Hoon Kim
2011 ◽  
Vol 181 (16) ◽  
pp. 3308-3322 ◽  
Author(s):  
Licheng Wang ◽  
Lihua Wang ◽  
Yun Pan ◽  
Zonghua Zhang ◽  
Yixian Yang

2020 ◽  
Vol 7 (7) ◽  
pp. 6132-6142 ◽  
Author(s):  
Ahsan Saleem ◽  
Abid Khan ◽  
Saif Ur Rehman Malik ◽  
Haris Pervaiz ◽  
Hassan Malik ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Faris A. Almalki ◽  
Ben Othman Soufiene

Nowadays, IoT technology is used in various application domains, including the healthcare, where sensors and IoT enabled medical devices exchange data without human interaction to securely transmit collected sensitive healthcare data towards healthcare professionals to be reviewed and take proper actions if needed. The IoT devices are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range. In healthcare applications, many miniaturized devices are exploited for healthcare data collection and transmission. Thus, there is a need for secure data aggregation while preserving the data integrity and privacy of the patient. For that, the security, privacy, and aggregation of health data are very important aspects to be considered. This paper proposes a novel secure data aggregation scheme called “An Efficient and Privacy-Preserving Data Aggregation Scheme with authentication for IoT-Based Healthcare applications” (EPPDA). EPPDA is based to verification and authorization phase to verify the legitimacy of the nodes that need to join the process of aggregation. EPPDA, also, uses additive homomorphic encryption to protect data privacy and combines it with homomorphic MAC to check the data integrity. The major advantage of homomorphic encryption is allowing complex mathematical operations to be performed on encrypted data without knowing the contents of the original plain data. The proposed system is developed using MySignals HW V2 platform. Security analysis and experimental results show that our proposed scheme guarantees data privacy, messages authenticity, and integrity, with lightweight communication overhead and computation.


Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2085 ◽  
Author(s):  
An Braeken ◽  
Pardeep Kumar ◽  
Andrew Martin

The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can reveal life patterns of the customers. Recently, several methods in different groups (e.g., secure data aggregation, etc.) have been proposed to collect the consumption usage in a privacy-preserving manner. Nevertheless, most of the schemes either introduce computational complexities in data aggregation or fail to support privacy-preserving billing against the internal adversaries (e.g., malicious data concentrators). In this paper, we propose an efficient and privacy-preserving data aggregation scheme that supports dynamic billing and provides security against internal adversaries in the smart grid. The proposed scheme actively includes the customer in the registration process, leading to end-to-end secure data aggregation, together with accurate and dynamic billing offering privacy protection. Compared with the related work, the scheme provides a balanced trade-off between security and efficacy (i.e., low communication and computation overhead while providing robust security).


2013 ◽  
Vol 416-417 ◽  
pp. 1466-1469
Author(s):  
Fu Zhao Sun

Internet of Things has received more and more attention, due to a wide range of potential applications. In this paper, we propose a secure data aggregation framework for the Internet of Things. It is based on fully homomorphic encryption. Moreover, this is a form of encryption where any specific algebraic operation performed on the raw sensor data is equivalent to the same algebraic operation performed on the cryptographic sensor data.


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