Power Theft Identification Using Embedded System

Today, power theft plays the key role in transmission losses of electricity from the generating station to the consumer end. About 30% of power produced is being theft. Though the electricity boards know that there is power theft in the area under their vigilance, they are not able to locate the area or location of theft. So, to identify the power theft and to communicate to the EB there needs a system to be developed. Here comes the system developed by us which will find the power theft if it happens and sends the information about the place of the theft to the nearby Electricity Board

Privacy-Friendly Mobility Analytics using Aggregate Location Data

Location data can be extremely useful to study commuting patterns and disruptions, as well as to predict real-time traffic volumes. At the same time, however, the fine-grained collection of user locations raises serious privacy concerns, as this can reveal sensitive information about the users, such as, life style, political and religious inclinations, or even identities. In this paper, we study the feasibility of crowd-sourced mobility analytics over aggregate location information: users periodically report their location, using a privacy-preserving aggregation protocol, so that the server can only recover aggregates -- i.e., how many, but not which, users are in a region at a given time. We experiment with real-world mobility datasets obtained from the Transport For London authority and the San Francisco Cabs network, and present a novel methodology based on time series modeling that is geared to forecast traffic volumes in regions of interest and to detect mobility anomalies in them. In the presence of anomalies, we also make enhanced traffic volume predictions by feeding our model with additional information from correlated regions. Finally, we present and evaluate a mobile app prototype, called Mobility Data Donors (MDD), in terms of computation, communication, and energy overhead, demonstrating the real-world deployability of our techniques.Comment: Published at ACM SIGSPATIAL 201

Still Wrong Use of Pairings in Cryptography

Several pairing-based cryptographic protocols are recently proposed with a wide variety of new novel applications including the ones in emerging technologies like cloud computing, internet of things (IoT), e-health systems and wearable technologies. There have been however a wide range of incorrect use of these primitives. The paper of Galbraith, Paterson, and Smart (2006) pointed out most of the issues related to the incorrect use of pairing-based cryptography. However, we noticed that some recently proposed applications still do not use these primitives correctly. This leads to unrealizable, insecure or too inefficient designs of pairing-based protocols. We observed that one reason is not being aware of the recent advancements on solving the discrete logarithm problems in some groups. The main purpose of this article is to give an understandable, informative, and the most up-to-date criteria for the correct use of pairing-based cryptography. We thereby deliberately avoid most of the technical details and rather give special emphasis on the importance of the correct use of bilinear maps by realizing secure cryptographic protocols. We list a collection of some recent papers having wrong security assumptions or realizability/efficiency issues. Finally, we give a compact and an up-to-date recipe of the correct use of pairings.Comment: 25 page

A game theory model for electricity theft detection and privacy-aware control in AMI systems

We introduce a model for the operational costs of an electric distribution utility. The model focuses on two of the new services that are enabled by the Advanced Metering Infrastructure (AMI): (1) the fine-grained anomaly detection that is possible thanks to the frequent smart meter sampling rates (e.g., 15 minute sampling intervals of some smart meter deployments versus monthly-readings from old meters), and (2) the ability to shape the load thanks to advanced demand-response mechanisms that leverage AMI networks, such as direct-load control. We then study two security problems in this context. (1) In the first part of the paper we formulate the problem of electricity theft detection (one of the use-cases of anomaly detection) as a game between the electric utility and the electricity thief. The goal of the electricity thief is to steal a predefined amount of electricity while minimizing the likelihood of being detected, while the electric utility wants to maximize the probability of detection and the degree of operational cost it will incur for managing this anomaly detection mechanism. (2) In the second part of the paper we formulate the problem of privacy-preserving demand response as a control theory problem, and show how to select the maximum sampling interval for smart meters in order to protect the privacy of consumers while maintaining the desired load shaping properties of demand-response programs

Het slimme elektriciteitsnetwerk en de noodzaak tot het uitwisselen van persoonsgegevens

Het slimme elektriciteitsnetwerk en de slimme meter zijn geen onomstreden onderwerpen en kennen vooral in Nederland een bewogen geschiedenis die zelfs in de internationale literatuur wordt aangehaald.2 In dit artikel wordt eerst kort ingegaan op de Nederlandse en EU regelgeving die ten grondslag ligt aan het slimme elektriciteitsnetwerk. Daarna wordt gekeken welke rol privacy hierin is toebedeeld. De kern van het artikel is een analyse van de verschillende functies van de slimme meter, alsmede de noodzaak om hierbij gedetailleerde gegevens3 te verwerken. Deze functies worden vervolgens getoetst aan de EU privacywetgeving en de ontwikkeling van het recht op gegevensbescherming wordt kritisch geëvalueerd. Tenslotte zal worden toegelicht welke benadering door de Commissie wordt gekozen in vraagstukken waar de implementatie van technologie leidt tot een spanningsveld tussen belangen van burgers bij privacy en belangen van de collectieven (industrie en overheid) bij het vrije verkeer van persoonsgegevens. Daarbij wordt gekeken of deze benadering recht doet aan de privacy van de Europese burger