454 research outputs found
Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions
In recent years, low-carbon transportation has become an indispensable part
as sustainable development strategies of various countries, and plays a very
important responsibility in promoting low-carbon cities. However, the security
of low-carbon transportation has been threatened from various ways. For
example, denial of service attacks pose a great threat to the electric vehicles
and vehicle-to-grid networks. To minimize these threats, several methods have
been proposed to defense against them. Yet, these methods are only for certain
types of scenarios or attacks. Therefore, this review addresses security aspect
from holistic view, provides the overview, challenges and future directions of
cyber security technologies in low-carbon transportation. Firstly, based on the
concept and importance of low-carbon transportation, this review positions the
low-carbon transportation services. Then, with the perspective of network
architecture and communication mode, this review classifies its typical attack
risks. The corresponding defense technologies and relevant security suggestions
are further reviewed from perspective of data security, network management
security and network application security. Finally, in view of the long term
development of low-carbon transportation, future research directions have been
concerned.Comment: 34 pages, 6 figures, accepted by journal Renewable and Sustainable
Energy Review
Fog based Secure Framework for Personal Health Records Systems
The rapid development of personal health records (PHR) systems enables an
individual to collect, create, store and share his PHR to authorized entities.
Health care systems within the smart city environment require a patient to
share his PRH data with a multitude of institutions' repositories located in
the cloud. The cloud computing paradigm cannot meet such a massive
transformative healthcare systems due to drawbacks including network latency,
scalability and bandwidth. Fog computing relieves the burden of conventional
cloud computing by availing intermediate fog nodes between the end users and
the remote servers. Aiming at a massive demand of PHR data within a ubiquitous
smart city, we propose a secure and fog assisted framework for PHR systems to
address security, access control and privacy concerns. Built under a fog-based
architecture, the proposed framework makes use of efficient key exchange
protocol coupled with ciphertext attribute based encryption (CP-ABE) to
guarantee confidentiality and fine-grained access control within the system
respectively. We also make use of digital signature combined with CP-ABE to
ensure the system authentication and users privacy. We provide the analysis of
the proposed framework in terms of security and performance.Comment: 12 pages (CMC Journal, Tech Science Press
Advance Vehicle and Driver Profile Management Using Cloud Frameworks
Advancements in semiconductor technology, embedded automotive computing, AI/ML computing and cloud computing has recently helped automotive industry to reach to provide the next generation vehicular experience such as self-driving cars, advanced safety features, cloud-based fleet management, highly efficient automotive manufacturing, connected cars, telematics and many more. Automotive or vehicular industry also started focus on providing better driving experience, in vehicle connectivity, entertainment, remote vehicle diagnostics and driver assistance, etc. Automotive cloud computing is one such domain which helped automotive industry to scale itself to connect the vehicles to cloud and remotely manage and control the vehicles, provide emergency assistance, data science and analytics services to dealers, insurance companies, car manufacturers, fleet management, etc. In this paper we present the research of recent advancements of automotive industry especially using cloud computing and how the cloud computing frameworks are making huge impact on auto industry such as advance driver’s profiles management using cloud framework. This paper also discusses the implementation approach for electronically managing the vehicle and driver’s preferences for their next generation electric and hybrid vehicles. And the paper proposes the smartphone’s NFC or BLE based driver’s profiles management approach
Running Big Data Privacy Preservation in the Hybrid Cloud Platform
Now a day’s cloud computing has been used all over the industry, due to rapid growth in information technology and mobile device technology. It is more important task, user’s data privacy preservation in the cloud environment. Big data platform is collection of sensitive and non-sensitive data. To provide solution of big data security in the cloud environment, organization comes with hybrid cloud approach. There are many small scale industries arising and making business with other organization. Any organization data owner or customers never want to scan or expose their private data by the cloud service provider. To improve security performance, cloud uses data encryption technique on original data in public cloud. Proposed system work is carried out how to improve image data privacy preserving in hybrid cloud. For that we are implementing image encryption algorithm based on Rubik’s cube principle improves the image cryptography for the public cloud data securit
Message sharing scheme based on edge computing in IoV
With the rapid development of 5G wireless communication and sensing technology, the Internet of Vehicles (IoV) will establish a widespread network between vehicles and roadside infrastructure. The collected road information is transferred to the cloud server with the assistance of roadside infrastructure, where it is stored and made available to other vehicles as a resource. However, in an open cloud environment, message confidentiality and vehicle identity privacy are severely compromised, and current attribute-based encryption algorithms still burden vehicles with large computational costs. In order to resolve these issues, we propose a message-sharing scheme in IoV based on edge computing. To start, we utilize attribute-based encryption techniques to protect the communications being delivered. We introduce edge computing, in which the vehicle outsources some operations in encryption and decryption to roadside units to reduce the vehicle's computational load. Second, to guarantee the integrity of the message and the security of the vehicle identity, we utilize anonymous identity-based signature technology. At the same time, we can batch verify the message, which further reduces the time and transmission of verifying a large number of message signatures. Based on the computational Diffie-Hellman problem, it is demonstrated that the proposed scheme is secure under the random oracle model. Finally, the performance analysis results show that our work is more computationally efficient compared to existing schemes and is more suitable for actual vehicle networking
Outsourced Analysis of Encrypted Graphs in the Cloud with Privacy Protection
Huge diagrams have unique properties for organizations and research, such as
client linkages in informal organizations and customer evaluation lattices in
social channels. They necessitate a lot of financial assets to maintain because
they are large and frequently continue to expand. Owners of large diagrams may
need to use cloud resources due to the extensive arrangement of open cloud
resources to increase capacity and computation flexibility. However, the
cloud's accountability and protection of schematics have become a significant
issue. In this study, we consider calculations for security savings for
essential graph examination practices: schematic extraterrestrial examination
for outsourcing graphs in the cloud server. We create the security-protecting
variants of the two proposed Eigen decay computations. They are using two
cryptographic algorithms: additional substance homomorphic encryption (ASHE)
strategies and some degree homomorphic encryption (SDHE) methods. Inadequate
networks also feature a distinctively confidential info adaptation convention
to allow the trade-off between secrecy and data sparseness. Both dense and
sparse structures are investigated. According to test results, calculations
with sparse encoding can drastically reduce information. SDHE-based strategies
have reduced computing time, while ASHE-based methods have reduced stockpiling
expenses
An extensive research survey on data integrity and deduplication towards privacy in cloud storage
Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well as data deduplication is such associated phenomena which influence data privacy. Therefore, this manuscript discusses the explicit research contribution toward data integrity, data privacy, and data deduplication. The manuscript also contributes towards highlighting the potential open research issues followed by a discussion of the possible future direction of work towards addressing the existing problems
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