相关论文: A Collusion-Resistance Privacy-Preserving Smart Me…

Smart-meters are a key component of energy transition. The large amount of data collected in near real-time allows grid operators to observe and simulate network states. However, privacy-preserving rules forbid the use of such data for any…

Data aggregation in intermediate nodes (called aggregator nodes) is an effective approach for optimizing consumption of scarce resources like bandwidth and energy in Wireless Sensor Networks (WSNs). However, in-network processing poses a…

This study investigates the optimal selection of parameters for collaborative clustering while ensuring data privacy. We focus on key clustering algorithms within a collaborative framework, where multiple data owners combine their data. A…

Frequent metering of electricity consumption is crucial for demand side management in smart grids. However, metered data can be processed fairly easily by employing well-established nonintrusive appliance load monitoring techniques to infer…

Smart meters enable improvements in electricity distribution system efficiency at some cost in customer privacy. Users with home batteries can mitigate this privacy loss by applying charging policies that mask their underlying energy use. A…

Design of an effective and reliable communication network supporting smart grid applications requires a selection of appropriate communication technologies and protocols. The objective of this paper is to study and quantify the capabilities…

Cloud computing has been a dominant paradigm for a variety of information processing platforms, particularly for enabling various popular applications of sharing economy. However, there is a major concern regarding data privacy on these…

With the increasing adoption of data-hungry machine learning algorithms, personal data privacy has emerged as one of the key concerns that could hinder the success of digital transformation. As such, Privacy-Preserving Machine Learning…

The modernization of the electrical grid and the installation of smart meters come with many advantages to control and monitoring. However, in the wrong hands, the data might pose a privacy threat. In this paper, we consider the tradeoff…

Outsourcing data storage to the remote cloud can be an economical solution to enhance data management in the smart grid ecosystem. To protect the privacy of data, the utility company may choose to encrypt the data before uploading them to…

Smart meters are of the basic elements in the so-called Smart Grid. These devices, connected to the Internet, keep bidirectional communication with other devices in the Smart Grid structure to allow remote readings and maintenance. As any…

Among existing privacy-preserving approaches, Differential Privacy (DP) is a powerful tool that can provide privacy-preserving noisy query answers over statistical databases and has been widely adopted in many practical fields. In…

Energy disaggregation techniques, which use smart meter data to infer appliance energy usage, can provide consumers and energy companies valuable insights into energy management. However, these techniques also present privacy risks, such as…

Privacy preservation is an important issue in today's context of extreme penetration of internet and mobile technologies. It is more important in the case of Wireless Sensor Networks (WSNs) where collected data often requires in-network…

Smart grids leverage data from smart meters to improve operations management and to achieve cost reductions. The fine-grained meter data also enable pricing schemes that simultaneously benefit electricity retailers and users. Our goal is to…

The amount of personal data collected in our everyday interactions with connected devices offers great opportunities for innovative services fueled by machine learning, as well as raises serious concerns for the privacy of individuals. In…

An important function of collaborative network intrusion detection is to analyze the network logs of the collaborators for joint IP addresses. However, sharing IP addresses in plain is sensitive and may be even subject to privacy…

Secure Multiparty Computation (MPC) can improve the security and privacy of data owners while allowing analysts to perform high quality analytics. Secure aggregation is a secure distributed mechanism to support federated deep learning…

Highly accurate profiles of consumers daily energy usage are reported to power grid via smart meters which enables smart grid to effectively regulate power demand and supply. However, consumers energy consumption pattern can reveal personal…

In this proposal paper we highlight the need for privacy preserving energy demand forecasting to allay a major concern consumers have about smart meter installations. High resolution smart meter data can expose many private aspects of a…