Smart grid (SG) is an agenda of interest to governments and researchers, as a successful cyberattack against smart grids (e.g. compromise of smart meters) can have devastating real-world consequences, ranging from financial loss to fatalities. In this paper, we present a novel and secure message authentication scheme, which provides mutual authentication and key establishment for smart grid. The scheme is also designed to preserve the identities of the gateways during message transmission. We then prove the security of the scheme, as well as verifying the security properties using Proverif and demonstrating the utility of the scheme using simulations. © 2017 Elsevier Inc.

Arun Kumar S

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Li X

Wu F

Kumari S

Xu L

Choo K.K.R.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Journal of Parallel and Distributed Computing

IEEE Systems Journal

A Lightweight and Provably Secure Key Agreement System for a Smart Grid With Elliptic Curve Cryptography

With the prevalent use of mobile cameras to capture images, the demands for efficient and effective methods for indexing and retrieval of personal image collections on mobile devices have also risen. In this paper, we propose to represent images with hash codes, which is a compressed representation of deep convolutional features using deep auto-encoder on the cloud. To ensure user's privacy, the image is first encrypted using a light-weight encryption algorithm on mobile device prior to offloading it to the cloud for features extraction. This approach eliminates the computationally expensive process of features extraction on resource constrained devices. A pre-trained convolutional neural network (CNN) is used to extract features which are then transformed to compact binary codes using a deep auto-encoder. The hash codes are then sent back to the mobile device where they are stored in a hash table along with image location. Approximate nearest neighbor (ANN) search approach is utilized to efficiently retrieve the desired images without exhaustive searching of the entire image collection. The proposed method is evaluated against three different publicly available image datasets namely Corel-10K, GHIM-10K, and Product image dataset. Experimental results demonstrate that features representation using CNN and auto-encoder shows much better results than several state-of-the-art hashing schemes for image retrieval on mobile devices. © 2018 Elsevier B.V.

Computer Communications

Privacy-preserving image retrieval for mobile devices with deep features on the cloud

Wireless body area networks (WBANs) are used to collect and exchange vital and sensitive information about the physical conditions of patients. Due to the openness and mobility of such networks, even without knowing the context of the exchanged data or linking traffic to the identities of involved sensors, criminals are able to gain useful information about the severe conditions of patients and carry effective undetectable physical attacks. Therefore, confidentiality and mutual authentication services are essential for WBANs, and the transmission must be anonymous and unlinkable as well. Given the limitations of the resources available for these sensors, a lightweight anonymous mutual authentication and key agreement scheme for centralized two-hop WBANs is proposed in this paper, which allows sensor nodes attached to the patient's body to authenticate with the local server/hub node and establish a session key in an anonymous and unlinkable manner. The security of our scheme is proved by rigorous formal proof using BAN logic and also through informal analysis. Besides, the security of our scheme is evaluated by using the Automated Validation of Internet Security Protocols and Applications (AVISPA) as well. Finally, we compare our proposed scheme with other related schemes and the comparison results show that our scheme outperforms previously related schemes. © 2017 Elsevier B.V.

Computer Networks

Anonymous mutual authentication and key agreement scheme for wearable sensors in wireless body area networks

Fulltext

Security and Communication Networks

A novel and provably secure authentication and key agreement scheme with user anonymity for global mobility networks

Future Generation Computer Systems

A robust biometrics based three-factor authentication scheme for Global Mobility Networks in smart city

A lightweight multi-layer authentication protocol for wireless body area networks

Pervasive and Mobile Computing

A secure cloud-assisted urban data sharing framework for ubiquitous-cities

A provably secure and anonymous message authentication scheme for smart grids

Journal	Data powered by TypesetJournal of Parallel and Distributed Computing
Publisher	Data powered by TypesetElsevier BV
ISSN	0743-7315
Open Access	0