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A blockchain model for fair data sharing in deregulated smart grids

- Samuel, Omaji, Javaid, Nadeem, Awais, Muhammad, Ahmed, Zeeshan, Imran, Muhammad, Guizani, Mohsen

  • Authors: Samuel, Omaji , Javaid, Nadeem , Awais, Muhammad , Ahmed, Zeeshan , Imran, Muhammad , Guizani, Mohsen
  • Date: 2019
  • Type: Text , Conference paper
  • Relation: 2019 IEEE Global Communications Conference, GLOBECOM 2019, Waikoloa 9-13 December 2019
  • Full Text: false
  • Reviewed:
  • Description: The emergence of smart home appliances has generated a high volume of data on smart meters belonging to different customers. However, customers can not share their data in deregulated smart grids due to privacy concern. Although, these data are important for the service provider in order to provide an efficient service. To encourage the customers' participation, this paper proposes an access control mechanism by fairly compensating customers for their participation in data sharing via blockchain using the concept of differential privacy. We addressed the computational issues of existing ethereum blockchain by proposing a proof of authority consensus protocol through the Pagerank mechanism in order to derive the reputation scores. Experimental results show the efficiency of the proposed model to minimize privacy risk, and maximize aggregator's profit. In addition, gas consumption, as well as the cost of the computational resources, is reduced. © 2019 IEEE.

An incentive scheme for VANETs based on traffic event validation using blockchain

- Iftikhar, Muhammad, Javaid, Nadeem, Samuel, Omaji, Shoaib, Muhammad, Imran, Muhammad

  • Authors: Iftikhar, Muhammad , Javaid, Nadeem , Samuel, Omaji , Shoaib, Muhammad , Imran, Muhammad
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 16th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2020, Limassol, Cyprus, 15 to 19 June 2020, 2020 International Wireless Communications and Mobile Computing, IWCMC 2020 p. 2133-2137
  • Full Text: false
  • Reviewed:
  • Description: A large amount of data is involved in an effective and timely exchange of traffic information between vehicles in Vehicular Ad-hoc Networks (VANETs), which ensures efficiency and reliability. VANETs assist in sharing traffic information effectively and timely to improve traffic efficiency and reliability. However, less storage capability and selfish behavior of the vehicles are important issues that need to be tackled. Moreover, traditional storage mechanisms require the involvement of third parties, which are insecure, untrustworthy, non-transparent, and unreliable. To overcome these issues, we proposed a blockchain-based data storage scheme for VANETs by exploiting the benefits of the Interplanetary File System (IPFS), which is deployed on Road Side Units (RSUs). Furthermore, RSUs are able to receive the aggregation packet comprising of the event information acquired from the vehicles. After receiving and verifying the aggregation packet, the RSU stores the event's information in IPFS and the reputation values of vehicles in blockchain. Moreover, we proposed an incentive mechanism in this work, in which monetary incentives are given to the repliers who agree with the vehicle regarding the event information. The incentives are given by the initiator after verifying the signatures of the repliers. All the transactions involved in the incentive process are stored in blockchain. The simulation results prove the efficiency of the proposed scheme in terms of transaction cost and storage savings in VANETs. © 2020 IEEE.

CNN and GRU based deep neural network for electricity theft detection to secure smart grid

- Ullah, Ashraf, Javaid, Nadeem, Samuel, Omaji, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Ullah, Ashraf , Javaid, Nadeem , Samuel, Omaji , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 16th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2020, Limassol, Cyprus, 15 to 19 June 2020, 2020 International Wireless Communications and Mobile Computing, IWCMC 2020 p. 1598-1602
  • Full Text: false
  • Reviewed:
  • Description: In this paper, a Hybrid Deep Neural Network (HDNN) is proposed in this work, which is the combination of Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Particle Swarm Optimization (PSO), termed as CNN-GRU-PSO HDNN. In this paper, real time electricity consumption data of consumers is used, which is taken from an easily available online source, named as State Grid Corporation of China (SGCC). The original dataset consists of actual values along with the erroneous and missing values. The pre-processing steps are performed initially to refine the data. After that, feature selection and extraction are performed using CNN, which reduce both the dimensionality and the redundancy present in the dataset. Furthermore, the classification of provided data into honest and fake consumers is done using GRU-PSO technique. The proposed HDNN model's performance is then compared with various benchmark techniques like Logistic Regression (LR), Support Vector Machine (SVM), Long Short Term Memory (LSTM) and GRU. The efficiency of the proposed model is validated using various performance parameters like Area Under the Curve (AUC), precision, accuracy, recall and F1-Score. The simulation results show that the proposed model outperforms the existing techniques in terms of ETD and class imbalanced issues. Moreover, the proposed model is also more robust and accurate than the existing methods. © 2020 IEEE.

Efficient data trading and storage in internet of vehicles using consortium blockchain

- Sadiq, Ayesha, Javaid, Nadeem, Samuel, Omaji, Khalid, Adia, Haider, Noman, Imran, Muhammad

A trust management system for multi-agent system in smart grids using blockchain technology

- Samuel, Omaji, Javaid, Nadeem, Khalid, Adia, Imrarn, Muhammad, Nasser, Nidal

  • Authors: Samuel, Omaji , Javaid, Nadeem , Khalid, Adia , Imrarn, Muhammad , Nasser, Nidal
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 2020 IEEE Global Communications Conference, GLOBECOM 2020, Virtual, Taipei China, 7 to 11 December 2020, 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings Vol. 2020-January
  • Full Text: false
  • Reviewed:
  • Description: In a multi-agent system (MAS), the trust of each agent has become hot research issues in the smart grids. The traditional trust systems that use access control and cryptography are not sufficient to handle the dynamic behavior of agents. Also, they are inefficient to solve the computational overhead of the cryptographic primitives. Based on these limitations, this paper proposes a blockchain-based trust management system for MAS. The proposed system consists of two layers: a lower layer that enables an agent to perform direct and indirect trust evaluations of other agents during interactions. Multi-source feedback from the interactions among different aggregators is feed to the blockchain. The upper layer is used to perform trust credibility of agents based on trust distortion, consistency and reliability. The credibility evaluation is used to determine the dynamic behavior of agents and also detect dishonest agents in the system. Trust model and security analysis of the proposed system are provided. Moreover, simulation results evaluate the effectiveness of the proposed trust system while the system is secure against bad-mouthing and on-off attacks. © 2020 IEEE.
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