Cristina Rottondi

Privacy-preserving smart metering with multiple data Consumers

The increasing diffusion of Automatic Meter Reading (AMR) and the possibility to open the system to third party services has raised many concerns about the protection of personal data related to energy, water or gas consumption, from which details about the habits of the users can be inferred. This paper proposes an infrastructure and a communication protocol for allowing utilities and third parties (data Consumers) to collect measurement data with different levels of spatial and temporal aggregation from smart meters without revealing the individual measurements to any single node of the architecture. The proposed infrastructure introduces a set of functional nodes in the smart grid, namely the Privacy Preserving Nodes (PPNs), which collect customer data encrypted by means of Shamirs Secret Sharing Scheme, and are supposed to be controlled by independent parties. By exploiting the homomorphic properties of the sharing scheme, the measurements can be aggregated directly in the encrypted domain. Therefore, an honest-but-curious attacker can obtain neither disaggregated nor aggregated data. The PPNs perform different spatial and temporal aggregation for each Consumer according to its needs and access rights. The information Consumers recover the aggregated data by collecting multiple shares from the PPNs. The paper also discusses the problem of deploying the information flows from the customers to the PPNs and, then, to the information Consumers in a resource constrained environment. We prove that minimizing the number of PPNs is a NP-hard problem and propose a fast greedy algorithm. The scalability of the infrastructure is first analyzed under the assumption that the communication network is reliable and timely, then in presence of communication errors and node failures. The paper also evaluates the anonymity of external attackers.

Routing, modulation level, and spectrum assignment in optical metro ring networks using elastic transceivers

For decades, optical networks have provided larger bandwidths than could be utilized, but with the increasing growth of the global Internet traffic demand, new optical transmission technologies are required to provide a much higher data rate per channel and to enable more flexibility in the allocation of traffic flow. Currently, researchers are investigating innovative transceiver architectures capable of dynamically adapting the modulation format to the transmission link properties. These transceivers are referred to as elastic and enable flexible allocation of optical bandwidth resources. To exploit their capabilities, the conventional fixed spectrum grid has to evolve to provide a more scalable and flexible system that can provide the spectral resources requireded to serve the client demand. The benefits of elastic transceivers with distance-adaptive data rates have been evaluated in optical core networks, but their application to metro ring networks has still not been addressed. This paper proposes methods based on integer linear programs and heuristic approaches to solve the routing, modulation level, and spectrum assignment problem in optical rings with elastic transceivers and rate-adaptive modulation formats. Moreover, we discuss how to analytically compute feasible solutions that provide useful upper bounds. Results show a significant reduction in terms of transceiver utilization and spectrum occupation.

Optical ring metro networks with flexible Grid and distance-adaptive optical coherent transceivers

The utilization of distance-adaptive coherent optical transceivers in combination with a flexible finer-grained Wavelength Division Multiplexing (WDM) grid has been proposed in optical core networks to enable higher spectral efficiency and flexibility in the allocation of traffic flows. However, the application of distance-adaptive transceivers in metro networks, which are typically based on ring topologies and characterized by shorter distances and lower traffic volumes, is still an open research area both in terms of network resource savings and coherent technology requirements. This paper discusses and analyzes an optical metro ring network architecture with distance-adaptive coherent transceivers and formalizes the routing, modulation level, and spectrum assignment (RMLSA) optimization problem over such a network in order to evaluate the possible benefits introduced by the use of coherent technologies and of a spectrum grid of finer granularity in metro scenarios. Comparisons with legacy WDM systems show significant savings in terms of spectrum occupation and transceiver utilization.

Evaluation of the Precision-Privacy Tradeoff of Data Perturbation for Smart Metering

Smart grid users and standardization committees require that utilities and third parties collecting metering data employ techniques for limiting the level of precision of the gathered household measurements to a granularity no finer than what is required for providing the expected service. Data aggregation and data perturbation are two such techniques. This paper provides quantitative means to identify a tradeoff between the aggregation set size, the precision on the aggregated measurements, and the privacy level. This is achieved by formally defining an attack to the privacy of an individual user and calculating how much its success probability is reduced by applying data perturbation. Under the assumption of time-correlation of the measurements, colored noise can be used to even further reduce the success probability. The tightness of the analytical results is evaluated by comparing them to experimental data.

A security framework for smart metering with multiple data consumers

The increasing diffusion of Automatic Meter Reading (AMR) has raised many concerns about the protection of personal data related to energy, water or gas consumption, from which details about the habits of the users can be inferred. On the other hand, aggregated measurements about consumption are crucial for several goals, including resource provisioning, forecasting, and monitoring. This paper proposes a framework for allowing information Consumers, such as utilities and third parties, to collect data with different levels of spatial and temporal aggregation from smart meters without revealing information about individual customers. The proposed infrastructure introduces a new set of functional nodes, namely the Privacy Preserving Nodes (PPNs), which collect customer data masked by means of a secret sharing scheme with homomorphic properties, and aggregate them directly in the masked domain, according to the Consumers needs and access rights. The information Consumers can recover the aggregated data by collecting multiple shares from the PPNs. The paper describes an Integer Linear Programming formulation and a greedy algorithm to address the problem of deploying the information flows between the information Producers (i.e. the customers), the PPNs, and the Consumers and evaluates the scalability of the infrastructure both under the assumption that the communication network is reliable and timely and in presence of communication errors.

On the complexity of routing and spectrum assignment in flexible-grid ring networks [Invited]

The adoption of a flexible grid will benefit the network design and control plane of future optical networks by providing increased adaptability of spectral resources to heterogeneous network conditions. Unfortunately, this flexibility is gained at the cost of significant additional complexity in the network design and control. In this paper, we consider the optimization of routing and spectrum allocation in flexi-grid ring networks and explore the trade-off between network cost (in terms of spectrum and transponder utilization) and problem complexity (in terms of the number of variables/constraints and computational time). Such trade-offs are investigated under multiple assumptions in terms of traffic grooming, regeneration, and modulation/baud rate assignment capabilities and contrasted with the case of fixed grid.We show how in the presence of traffic grooming the additional complexity due to the flexible grid has a minor impact on problem complexity. Similarly, in all the considered scenarios, regeneration and modulation/baud rate assignment do not relevantly impact on problem complexity. We also consider two possible alternative integer linear programming (ILP) models: the slicebased and channel-based approaches. The former handles each slice individually, whereas the latter uses precomputed subsets of contiguous slices of different bandwidths. Both models are solved under several different network settings. Complexity comparison of the ILP models shows that the slice-based approach provides better performance than the channel-based approach and that the performance gap between the two models increases with the introduction of additional flexibility and dimensions.

Traffic Grooming and Spectrum Assignment for Coherent Transceivers in Metro-Flexible Networks

Novel distance-adaptive optical transmission technologies have been proposed to boost transceiver datarates and to enable more flexibility in the allocation of traffic flows. The application of this new class of transceivers is being widely investigated in core networks, while their suitability in the metro area is still an open issue. On one hand, the short metro distances enable the utilization of higher spectrally efficient modulation formats, on the other hand, the lower bitrate suggests to employ lower baud rate with respect to core networks. In this letter, we perform traffic grooming and spectrum assignment using transceivers with fixed baud rate of 28 and 14 GBd and distance-adaptive modulation formats in optical metro networks. Comparisons with the wavelength-division multiplexing systems running over a fixed grid show that 1) significant savings in terms of spectrum occupation can be achieved, and that 2) such savings can be effectively achieved also using lower baud rate transceivers (e.g., 14 GBd).

Enabling Privacy in a Distributed Game-Theoretical Scheduling System for Domestic Appliances

Demand side management (DSM) makes it possible to adjust the load experienced by the power grid while reducing the consumers’ bill. Game-theoretic DSM is an appealing decentralized approach for collaboratively scheduling the usage of domestic electrical appliances within a set of households while meeting the users’ preferences about the usage time. The drawback of distributed DSM protocols is that they require each user to communicate his/her own energy consumption patterns, which may leak sensitive information regarding private habits. This paper proposes a distributed privacy-friendly DSM system that preserves users’ privacy by integrating data aggregation and perturbation techniques: users decide their schedule according to aggregated consumption measurements perturbed by means of additive white Gaussian noise. We evaluate the noise power and the number of users required to achieve a given privacy level, quantified by means of the increase of the information entropy of the aggregated energy consumption pattern. The performance of our proposed DSM system is compared to the one of a benchmark system that does not support privacy preservation in terms of total bill, peak demand, and convergence time. Results show that privacy can be improved at the cost of increasing the peak demand and the number of game iterations, whereas the total bill is only marginally incremented.

A protocol for metering data pseudonymization in smart grids

A tradeoff between data collection needs and user privacy is of paramount importance in the Smart Grid. This paper proposes a pseudonymization protocol for data gathered by the Smart Metres, which relies on a network infrastructure and a dedicated set of nodes, called privacy preserving nodes. The network privacy is enforced by a separation of duties; the privacy preserving nodes perform data pseudonymization without having access to the measurements, which are masked by means of a secret sharing scheme, while the entities accessing the data recover and relate the plain measurements generated by the same metre along a time window of finite duration but have no access to the metre identities. The paper also provides an evaluation of the security and of the performance of the protocol, comparing it to the two alternative encryption techniques, which mask the measurements by means of the Chaum mixing scheme or of an identity-based proxy re-encryption scheme. Copyright

A decisional attack to privacy-friendly data aggregation in Smart Grids

The privacy-preserving management of energy consumption measurements gathered by Smart Meters plays a pivotal role in the Automatic Metering Infrastructure of Smart Grids. Grid users and standardization committees are requiring that utilities and third parties collecting aggregated metering data are prevented from accessing measurements at the household granularity, and data perturbation is a technique used to provide a trade-off between the privacy of individual users and the precision of the aggregated measurements. In this paper, we discuss a decisional attack to aggregation with data-perturbation, showing that a curious entity can exploit the temporal correlation of Smart Grid measurements to detect the presence or absence of individual data generated by a given user inside an aggregate. We also propose a countermeasure to such attack and show its effectiveness using both synthetic and real home energy consumption measurement traces.