Related papers: Statistical-Based Privacy-Preserving Scheme with M…
More and more conventional electromechanical meters are being replaced with smart meters because of their substantial benefits such as providing faster bi-directional communication between utility services and end users, enabling direct…
We propose a privacy-preserving billing protocol for local energy markets (PBP-LEM) that takes into account market participants' energy volume deviations from their bids. PBP-LEM enables a group of market entities to jointly compute…
There are now several large scale deployments of differential privacy used to collect statistical information about users. However, these deployments periodically recollect the data and recompute the statistics using algorithms designed for…
In Advanced Metering Infrastructure (AMI) networks, smart meters should send fine-grained power consumption readings to electric utilities to perform real-time monitoring and energy management. However, these readings can leak sensitive…
In this paper a new class of cyber attacks against state estimation in the electric power grid is considered. This class of attacks is named false data injection attacks. We show that with the knowledge of the system configuration an…
The ability to preserve user privacy and anonymity is important. One of the safest ways to maintain privacy is to avoid storing personally identifiable information (PII), which poses a challenge for maintaining useful user statistics.…
The increasing adoption of smart meters introduces growing concerns about consumer privacy risks stemming from high resolution metering data. To counter these risks, there have been various works in actively shaping the grid-visible energy…
Advances in sensing and communication capabilities as well as power industry deregulation are driving the need for distributed state estimation in the smart grid at the level of the regional transmission organizations (RTOs). This leads to…
In smart grid, malicious customers may compromise their smart meters (SMs) to report false readings to achieve financial gains illegally. Reporting false readings not only causes hefty financial losses to the utility but may also degrade…
Data analytics (such as association rule mining and decision tree mining) can discover useful statistical knowledge from a big data set. But protecting the privacy of the data provider and the data user in the process of analytics is a…
Companies that have an online presence-in particular, companies that are exclusively digital-often subscribe to this business model: collect data from the user base, then expose the data to advertisement agencies in order to turn a profit.…
This paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life…
The proliferation of smart meters has resulted in a large amount of data being generated. It is increasingly apparent that methods are required for allowing a variety of stakeholders to leverage the data in a manner that preserves the…
Smart meters (SMs) play a pivotal rule in the smart grid by being able to report the electricity usage of consumers to the utility provider (UP) almost in real-time. However, this could leak sensitive information about the consumers to the…
Distribution grids across the world are undergoing profound changes due to advances in energy technologies. Electrification of the transportation sector and the integration of Distributed Energy Resources (DERs), such as photo-voltaic…
In advanced metering infrastructure (AMI), smart meters (SMs), which are installed at the consumer side, send fine-grained power consumption readings periodically to the electricity utility for load monitoring and energy management. Change…
The increasing deployment of distributed Battery Energy Storage Systems (BESSs) in modern power grids necessitates effective coordination strategies to ensure state-of-charge (SoC) balancing and accurate power delivery. While distributed…
Dynamic models of power systems are critical for analyzing grid response to disturbances and blackouts, but the release of real-world dynamic models is hindered by privacy and cybersecurity concerns, as such models carry sensitive…
Meter measurements in the power grid are susceptible to manipulation by adversaries, that can lead to errors in state estimation. This paper presents a general framework to study attacks on state estimation by adversaries capable of…
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…