Accurate and Efficient Security Authentication of IoT Devices using Machine Learning Algorithms DOI Open Access

Ilham Alghamdi,

Mohammad Eid Alzahrani

Published: March 16, 2024

The rapid proliferation of Internet Things (IoT) devices has led to an increase in botnet attacks targeting these devices. A attack is a cyber-attack which network compromised devices, referred as "bots" or "zombies," utilized execute synchronized attack. These can result substantial harm both the and they are connected. This study investigates deployment security authentication protocols verify identity IoT prior connection. also evaluates classification accuracy four distinct supervised machine learning algorithms: Random Forest (RF), Naïve Bayes (NB), DecisionTree (DT), eXtreme Gradient Boosting (XGBoost). It was foundXGBoost best performing classifier among various algorithms tested, terms detecting networks using Bot-IoT dataset.

Language: Английский

A Survey on Formal Verification and Validation Techniques for Internet of Things DOI Creative Commons
Moez Krichen

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(14), P. 8122 - 8122

Published: July 12, 2023

The Internet of Things (IoT) has brought about a new era connected devices and systems, with applications ranging from healthcare to transportation. However, the reliability security these systems are critical concerns that must be addressed ensure their safe effective operation. This paper presents survey formal verification validation (FV&V) techniques for IoT focus on challenges open issues in this field. We provide an overview methods testing discuss state explosion problem address it. also examined use AI software describe examples tools context. Finally, we FV&V present possible future directions research. aimed comprehensive understanding current highlight areas further research development.

Language: Английский

Citations

43
Digital post-disaster risk management twinning: A review and improved conceptual framework DOI Creative Commons
Umut Lagap, Saman Ghaffarian

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 110, P. 104629 - 104629

Published: June 24, 2024

Digital Twins (DT) is the real-time virtual representation of systems, communities, cities, or even human beings with substantial potential to revolutionize post-disaster risk management efforts and achieve resilient communities against adverse effects disasters. However, this remains largely unrecognized poorly understood in disaster management. This study explores current achievements, existing challenges, untapped DT management, accordingly, proposes an improved twin-based framework. paper employs a systematic literature review approach focusing on digital twinning (DPRMT) derived from two databases: Scopus Web Science. After screening process exclusion criteria, final analysis synthesizes findings selected set 96 papers. The results revealed that previous studies are not beyond only providing general statements about DT. There need for diverse data collection methods, considering demographic financial aspects, understanding social dynamics, employing dynamic models, recognizing interconnected giving due attention often-neglected recovery phase. comprehensive DPRMT concept framework leveraging decision-makers holistic efficient offers real-time, detailed, data-driven modeling solutions insights into disaster-affected areas communities. It also helpful optimize response planning, resource allocation, scenario testing by capturing complex behaviors systems entities often overlooked studies.

Language: Английский

Citations

17
A Survey on Key Management and Authentication Approaches in Smart Metering Systems DOI Creative Commons
Mohamed S. Abdalzaher, Mostafa M. Fouda, Ahmed A. Emran

et al.

Energies, Journal Year: 2023, Volume and Issue: 16(5), P. 2355 - 2355

Published: March 1, 2023

The implementation of the smart grid (SG) and cyber-physical systems (CPS) greatly enhances safety, reliability, efficiency energy production distribution. Smart grids rely on meters (SMs) in converting power (PGs) a reliable way. However, proper operation these needs to protect them against attack attempts unauthorized entities. In this regard, key-management authentication mechanisms can play significant role. paper, we shed light importance mechanisms, clarifying main efforts presented context literature. First, address intelligent attacks affecting SGs. Secondly, terms cryptography are addressed. Thirdly, summarize common proposed techniques with suitable critique showing their pros cons. Fourth, introduce effective paradigms state art. Fifth, two tools for verifying security integrity protocols presented. Sixth, relevant research challenges addressed achieve trusted SMs manipulations entities future vision. Accordingly, survey facilitate exerted by interested researchers regard.

Language: Английский

Citations

37
Distributed intelligence for IoT-based smart cities: a survey DOI
Mohamed Hashem, Aisha Siddiqa, Fadele Ayotunde Alaba

et al.

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(27), P. 16621 - 16656

Published: July 22, 2024

Language: Английский

Citations

10
An efficient convolutional neural network based attack detection for smart grid in 5G-IOT DOI

Sheeja Rani S,

Mostafa F. Shaaban, Abdelfatah Ali

et al.

International Journal of Critical Infrastructure Protection, Journal Year: 2025, Volume and Issue: unknown, P. 100738 - 100738

Published: Jan. 1, 2025

Language: Английский

Citations

1
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
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
A Novel Intelligence System for Hybrid Crop Suitable Landform Prediction Using Machine Learning Techniques and IoT DOI

Senthil G. A,

R. Prabha,

S. Sridevi

et al.

Algorithms for intelligent systems, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Jan. 1, 2024

Language: Английский

Citations

4
Optimizing Smart Home Intrusion Detection With Harmony-Enhanced Extra Trees DOI Creative Commons
Akmalbek Abdusalomov, Dusmurod Kilichev, Rashid Nasimov

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 117761 - 117786

Published: Jan. 1, 2024

In this study, we present an innovative network intrusion detection system (IDS) tailored for Internet of Things (IoT)-based smart home environments, offering a novel deployment scheme that addresses the full spectrum security challenges. Distinct from existing approaches, our comprehensive strategy not only proposes model but also incorporates IoT devices as potential vectors in cyber threat landscape, consideration often neglected previous research. Utilizing harmony search algorithm (HSA), refined extra trees classifier (ETC) by optimizing extensive array hyperparameters, achieving level sophistication and performance enhancement surpasses typical methodologies. Our was rigorously evaluated using robust real-time dataset, uniquely gathered 105 devices, reflecting more authentic complex scenario compared to simulated or limited datasets prevalent literature. commitment collaborative progress cybersecurity is demonstrated through public release source code. The underwent exhaustive testing 2-class, 8-class, 34-class configurations, showcasing superior accuracy (99.87%, 99.51%, 99.49%), precision (97.41%, 96.02%, 96.07%), recall (98.45%, 87.14%, 87.1%), f1-scores (97.92%, 90.65%, 90.61%) firmly establish its efficacy. Thiswork marks significant advancement security, providing scalable effective IDS solution adaptable intricate dynamics modern networks. findings pave way future endeavors realm defense, ensuring homes remain safe havens era digital vulnerability.

Language: Английский

Citations

4
Anomaly Detection of Distributed Denial of Service (DDoS) in IoT Network Using Machine Learning DOI
Baydaa Hashim Mohammed, Hasimi Sallehudin, Nurhizam Safie Mohd Satar

et al.

Studies in systems, decision and control, Journal Year: 2025, Volume and Issue: unknown, P. 41 - 64

Published: Jan. 1, 2025

Language: Английский

Citations

0