Mohamad Badra

Design and Performance Analysis of a Virtual Ring Architecture for Smart Grid Privacy

The traditional electrical grid has become inadequate in meeting the needs and demands of electricity users in the 21st century. To address this challenge, smart grid technologies have emerged, which promise more efficient production and usage of electricity through bidirectional interactions between the consumer and the utility provider. This two-way interaction allows electricity to be generated in real time based on the actual needs of the consumers. However, this two-way interaction also raises concerns related to the privacy and the personal habits of consumers. To protect sensitive energy usage information of consumers, we propose a virtual ring architecture that can provide a privacy protection solution using symmetric or asymmetric encryptions of customers requests belonging to the same group. We compare the efficiency of our proposed approach with two recently proposed smart grid privacy approaches namely, one based on blind signature and other based on a homomorphic encryption solution. We show that our approach maintains the privacy of customers while reducing the performance overhead of cryptographic computations by more than a factor of 2 when compared with the aforementioned past solutions. We further demonstrate that our smart grid privacy solution is simple, scalable, cost-effective, and incurs minimal computational processing overheads.

Towards Privacy Protection in Smart Grid

The smart grid is an electronically controlled electrical grid that connects power generation, transmission, distribution, and consumers using information communication technologies. One of the key characteristics of the smart grid is its support for bi-directional information flow between the consumer of electricity and the utility provider. This two-way interaction allows electricity to be generated in real-time based on consumers’ demands and power requests. As a result, consumer privacy becomes an important concern when collecting energy usage data with the deployment and adoption of smart grid technologies. To protect such sensitive information it is imperative that privacy protection mechanisms be used to protect the privacy of smart grid users. We present an analysis of recently proposed smart grid privacy solutions and identify their strengths and weaknesses in terms of their implementation complexity, efficiency, robustness, and simplicity.

Network layer inter-operation of Device-to-Device communication technologies in Internet of Things (IoT)

The goal of the Internet of Things (IoT) is to create an integrated ecosystem for devices to communicate over the Internet. To achieve this goal, efficient inter-operation is needed among Device to Device (D2D) communication technologies that make up the ecosystem. Currently, these technologies operate in vertical silos with different protocols. We explore the challenges associated with the integration and interoperability of these D2D technologies by focusing on network layer functions such as addressing, routing, mobility, security and resource optimization. We identify the limitations of the current TCP/IP architecture for D2D communication in the IoT environment. We also discuss some of the limitations of the 6LoWPAN architecture and describe how it has been adopted for D2D communication. Finally, we present solutions to address the limitations we have identified for the network layer functions as applicable to D2D communication in the IoT environment.

Mutual Authentication for SIP: A Semantic Meaning for the SIP Opaque Values

The session initiation protocol (SIP) is rapidly becoming the dominant signalling protocol for calls over the Internet. It has quickly made large inroads into the voice over IP (VoIP) market. SIP is an application-layer control operating on top of a transport protocol and allows to create, modify, and terminate sessions with one or more participants. With security considerations, these operations require authentication from participating end-points, confidentiality, data integrity, and protection against internal and external attacks. For authentication, SIP relies on HTTP Digest by default; the client is authenticated to the SIP proxy server. In order to have mutual authentication between client and server, SIP could be implemented over TLS (transport layer security) when TCP is supported by SIP architecture network. In this paper, we propose a mutual authentication mechanism within HTTP Digest since this later is implemented by default in all SIP environments. It consists in providing meaning and semantic to some of the parameters values generated by the participating end-points during SIP session establishment, especially to the nonce values. Our solution is backward-compatible with today implementations. Without being in opposition to security protocols like TLS, this approach helps in reducing DoS (denial of service) attacks, detects server identity spoofing and ensures basic mutual authentication with comparison to HTTP digest.

Internet of Things. IoT Infrastructures

This keynote paper establishes the framework for three introductory sessions at the Mobility and Smart Cities conference held in Roma 27–28 October 2014. In the light of the latest knowledge and scientific projects findings the authors present actual R&D trends in the field of smart solutions for sustainable mobility based on ICT. New ideas, cutting-edge innovations and technologies for mobility agenda are needed together with multidisciplinary perspective and holistic approach applied. However, the positive expectations of sustainable mobility growth might also have some negative effects on the life and behaviour of citizens and institutions. The paper indicates both positive and negative aspects of the smart city developments to open the floor for crossfertilization of critical and incentive ideas.

Techniques, Taxonomy, and Challenges of Privacy Protection in the Smart Grid

As the ease with which any data are collected and transmitted increases, more privacy concerns arise leading to an increasing need to protect and preserve it. Much of the recent high-profile coverage of data mishandling and public misleadings about various aspects of privacy exasperates the severity. The Smart Grid (SG) is no exception with its key characteristics aimed at supporting bi-directional information flow between the consumer of electricity and the utility provider. What makes the SG privacy even more challenging and intriguing is the fact that the very success of the initiative depends on the expanded data generation, sharing, and processing. In particular, the deployment of smart meters whereby energy consumption information can easily be collected leads to major public hesitations about the technology. Thus, to successfully transition from the traditional Power Grid to the SG of the future, public concerns about their privacy must be explicitly addressed and fears must be allayed. Along these lines, this chapter introduces some of the privacy issues and problems in the domain of the SG, develops a unique taxonomy of some of the recently proposed privacy protecting solutions as well as some if the future privacy challenges that must be addressed in the future.

Lightweight and Efficient Privacy-Preserving Data Aggregation Approach for the Smart Grid

Abstract Over the last few years, we have seen the emergence of a wide range of Smart Grid architectures, technologies, and applications made possible by the significant improvements in hardware, software, and networking technologies. One of the challenges that has emerged in the Smart Grid environment is the privacy of Smart Grid users. Although several privacy-preserving techniques have been proposed recently for the Smart Grid environment, many of them suffer from high computation and communication costs, different types of attacks, and the use of complex key management schemes. To address these drawbacks, we propose an efficient, lightweight privacy-preserving data aggregation approach that makes use of symmetric homomorphic encryption and Diffie–Hellman (DH) or Elliptic Curve Diffie–Hellman (ECDH) key exchange methods. In contrast to previously proposed privacy-preserving schemes for the Smart Grid, we demonstrate the superiority of our proposed approach in terms of its low transmission and message overheads, and resiliency against a wide range of session key attacks, and ability to maintain data integrity against unauthorized modification or data forgery and to ensure authenticity of smart meters’ data.

Agent-based framework for sensor-to-sensor personalization

Abstract In Wireless Sensor Networks, personalization has been seen by researchers as the process of tailoring services to fulfill requests of different users with different profiles. This vision ignores that individual sensors commonly have different profiles and contexts and therefore different needs. In this paper, we aim at extending personalization by allowing sensors to support each other with services that mutually fit their differences. To this end, we propose an agent-based framework where sensor nodes delegate software agents (static or mobile) to collect valuable data about the neighboring sensors and the spatial characteristics of their surrounding environments. We also show how this framework may be used to make the routing process more convenient for relying nodes in terms of energy consumption and security.

A Lightweight Security Protocol for NFC-based Mobile Payments

Abstract In this work, we describe a security solution that can be used to securely establish mobile payment transactions over the Near-Field Communication (NFC) radio interface. The proposed solution is very lightweight one; it uses symmetric cryptographic primitives on devices having memory and CPU resources limitations. We show that our approach maintains the security of NFC communications and we further demonstrate that our solution is simple, scalable, cost-effective, and incurs minimal computational processing overheads.

Agent-based Framework for Sensor-to-Sensor Personalization☆

In Wireless Sensor Networks, personalization has been seen by researchers as the process of tailoring services to fulfill requests of different users with different profiles. This vision ignores that individual sensors commonly have different profiles and contexts and therefore different needs. In this paper, we aim at extending personalization by allowing sensors to support each other with services that mutually fit their differences. To this end, we propose an agent-based framework where sensor nodes delegate software agents (static or mobile) to collect valuable data about the neighboring sensors and the spatial characteristics of their surrounding environments. We also show how this framework may be used to make the routing and relocation processes more personalized.