Security and Privacy Preservation for Future Vehicular Transportation Systems: A Survey DOI

Abdulazeiz Almarshoodi,

James Keenan,

Ivan Campbell

et al.

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Journal Year: 2023, Volume and Issue: unknown, P. 728 - 734

Published: April 8, 2023

Electric Vehicles (EVs) with numerous optimized features are becoming more popular in today's world of vehicle technology. This is especially these days when climate change a concern, and the usage renewable energy promoted. These EVs require frequent charging for daily use, different stations would store sensitive data about EVs, e.g., location, driver's license, etc. leads to significant privacy security concerns. In this paper, we will investigate existing solutions proposed literature address Some implementing framework that depends on cryptography Matching Market, where plays vital role securing user information privacy. Other include secure privacy-preserving physical layer-assisted scheme improve authentication preserve Finally, provide comprehensive comparison works, followed by our recommendations future research directions enhance level electric transportation systems.

Language: Английский

Privacy and security of advanced metering infrastructure (AMI) data and network: a comprehensive review DOI Creative Commons
Priscilla Oyeladun Ajiboye, Kwame Opuni-Boachie Obour Agyekum, Emmanuel Asuming Frimpong

et al.

Journal of Engineering and Applied Science, Journal Year: 2024, Volume and Issue: 71(1)

Published: April 12, 2024

Abstract The traditional electrical grid has to be digitally improved as digitalization and effective integration of renewable energy bring better efficiency, intelligence, safety into the grid; hence, transition from a smart grid. A is modernized digitalized standard infrastructure that key component known advanced metering (AMI). AMI, also metering, technological enabler allows automatic collection reporting power-consumed data via two-way communication networks. However, collected power consumption confidential; its privacy must maintained. Similarly, for benefit consistently maximized, AMI network security always intact despite evolving threats attacks targeted at it. This paper provides comprehensive review existing vulnerabilities/attacks, challenges associated with system, open issues, future direction. major contributions this lie in vulnerabilities, state-of-the-art schemes their pros cons, protocols analysis, emerging measures. gave enumerated recommendations efficiency improvement terms latency reduction while implementing efficient measures work.

Language: Английский

Citations

7
Emerging technologies and supporting tools for earthquake disaster management: A perspective, challenges, and future directions DOI Creative Commons
Mohamed S. Abdalzaher, Moez Krichen, Francisco Falcone

et al.

Progress in Disaster Science, Journal Year: 2024, Volume and Issue: 23, P. 100347 - 100347

Published: July 3, 2024

Seismology is among the ancient sciences that concentrate on earthquake disaster management (EQDM), which directly impact human life and infrastructure resilience. Such a pivot has made use of contemporary technologies. Nevertheless, there need for more reliable insightful solutions to tackle daily challenges intricacies natural stakeholders must confront. To consolidate substantial endeavors in this field, we undertake comprehensive survey interconnected More particularly, analyze data communication networks (DCNs) Internet Things (IoT), are main infrastructures seismic networks. In accordance, present conventional innovative signal-processing techniques seismology. Then, shed light evolution EQ sensors including acoustic based optical fibers. Furthermore, address role remote sensing (RS), robots, drones EQDM. Afterward, highlight social media contribution. Subsequently, elucidation diverse optimization employed seismology prolonging presented. Besides, paper analyzes important functions artificial intelligence (AI) can fulfill several areas Lastly, guide how prevent disasters preserve lives.

Language: Английский

Citations

7
Linear Programming-Based Power Management for a Multi-Feeder Ultra-Fast DC Charging Station DOI Creative Commons
Luigi Rubino, Guido Rubino, Raffaele Esempio

et al.

Energies, Journal Year: 2023, Volume and Issue: 16(3), P. 1213 - 1213

Published: Jan. 22, 2023

The growing number of electric vehicles (EVs) affects the national electricity system in terms power demand and load variation. Turning our attention to Italy, on road is 39 million; this represents a major challenge, as they will need be recharged constantly when transition technology complete. If we consider that average 55 GW installed can produce 120 peak power, calculate with only 5% recharging mode, increases 126 GW, which approximately 140% power. integration renewable energy sources help grid, but solution less useful for handling large variations negatively affect grid. In addition, some committed public utility must have reduced stop time considered higher priority. introduction priorities implies absorption limit cannot easily introduced by limiting charging vehicles, rather computing flow respects constraints integrates local storage contributions. problem formulated manner does not unique solution; study, linear programming method used optimise resources, storage, EVs mitigate their effects Simulations are performed verify proposed method.

Language: Английский

Citations

15
Performance enhancement of artificial intelligence: A survey DOI
Moez Krichen, Mohamed S. Abdalzaher

Journal of Network and Computer Applications, Journal Year: 2024, Volume and Issue: unknown, P. 104034 - 104034

Published: Sept. 1, 2024

Language: Английский

Citations

5
Machine Learning Benchmarking for Secured IoT Smart Systems DOI
Mohamed S. Abdalzaher, Mahmoud M. Salim, Hussein A. Elsayed

et al.

Published: Nov. 24, 2022

Smartness and IoT along with machine learning (ML) lead the research directions nowadays. Smart city, smart campus, home, vehicle, etc; or if we call it "Smart x" will change how world entities interact among themselves. This paper provides an ML benchmarking as well a taxonomy that divides its models into linear non-linear ones based on problem type (classification regression), targeted security issue, kind of network, used evaluation measure. On other hand, algorithms enhanced play significant role to govern new era communication. also case study apply methods campus (SC) model reach secured system for data collection manipulation guided directions.

Language: Английский

Citations

19
Real-Time Energy Quality Issues Detection Related to Distribution Networks that Incorporates Smart Meters DOI
Adrian Gligor, Cristian-Dragoş Dumitru,

Catalin-Eugen Moldovan

et al.

Lecture notes in networks and systems, Journal Year: 2025, Volume and Issue: unknown, P. 454 - 466

Published: Jan. 1, 2025

Language: Английский

Citations

0
A comprehensive survey on privacy-preserving technologies for Smart Grids DOI Creative Commons
Hafsa Bibi, Mehran Abolhasan, Justin Lipman

et al.

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 124, P. 110371 - 110371

Published: May 1, 2025

Language: Английский

Citations

0
Privacy Preservation in Smart Meters: Current Status, Challenges and Future Directions DOI Creative Commons
Jonathan Kua, Mohammad Belayet Hossain, Iynkaran Natgunanathan

et al.

Sensors, Journal Year: 2023, Volume and Issue: 23(7), P. 3697 - 3697

Published: April 3, 2023

Recent years have seen the rapid development of technologies in Smart Grids (SGs) to enhance electricity networks with digital and data communication technologies. SGs can proactively detect, react, respond dynamic changes network. also efficiency reliability supplies promote integration renewable energy sources. Meters (SMs) are often as first step a successful implementation SGs. While SMs enable Utility Providers consumers obtain near real-time information consumption, they be exploited infer sensitive consumer data. Therefore, privacy preservation is paramount ensuring widespread deployment In this paper, we present comprehensive survey state-of-the-art SM privacy-preserving techniques published literature over past decade. We categorize these based on attack types their objectives. aim offer unique perspective article through lens preservation, cross-cutting wide range presented literature. conclude by identifying challenges highlighting key future research directions field.

Language: Английский

Citations

9
Detection of DDoS attacks in SDN with Siberian Tiger Optimization algorithm and deep learning DOI Creative Commons

Naseer Hameed Saadoon Al-Sarray,

Javad Rahebi, Ayşe Demi̇rhan

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: March 19, 2024

Abstract The Software-defined Networking (SDN) system plays a crucial role in efficiently overseeing the Internet network by segregating control and data planes. In SDN, controller manages determines policy sending setting SDN switches. Despite significant advantages, has security challenges. DDoS attacks are main challenge networks. primarily target to disrupt performance. Intrusion detection systems networks need confidential methods for message exchange coordination of controllers so that they can blacklist attacking addresses with each other. this manuscript, we introduce an approach utilizing 1D CNN LSTM detecting network, incorporating information hidden images. first stage, game theory deep learning based on GAN used increase attack accuracy balance set. second uses extract primary features, Siberian tiger optimization (STO) algorithm is applied enhance efficiency network. third step, STO selects optimal features. Finally, classifies traffic receiving selected use image encryption privacy exchanging sharing blacklists. tests performed Python datasets UNSW-NB15, CIC-IDS2017, NSL-KDD 99.49%, 99.86%, 99.91%. proposed method GAN-CL-STO demonstrates higher compared CNN-LSTM, HODNN+CRF, CNN, PSO-1D CNN+BiLSTM methods. suggested identifying more accurate than WOA, HHO, COA feature selection

Language: Английский

Citations

3
Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey DOI Creative Commons
Lea Demelius, Roman Kern, Andreas Trügler

et al.

ACM Computing Surveys, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 21, 2025

Differential Privacy has become a widely popular method for data protection in machine learning, especially since it allows formulating strict mathematical privacy guarantees. This survey provides an overview of the state-of-the-art differentially private centralized deep thorough analyses recent advances and open problems, as well discussion potential future developments field. Based on systematic literature review, following topics are addressed: emerging application domains, generative models, auditing evaluation methods against broad range threats attacks, improvements privacy-utility trade-offs.

Language: Английский

Citations

0