Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives

D Javaheri, S Gorgin, JA Lee, M Masdari - Information Sciences, 2023 - Elsevier
Nowadays, cybersecurity challenges and their ever-growing complexity are the main
concerns for various information technology-driven organizations and companies. Although …

Smart anomaly detection in sensor systems: A multi-perspective review

L Erhan, M Ndubuaku, M Di Mauro, W Song, M Chen… - Information …, 2021 - Elsevier
Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …

Deep anomaly detection for time-series data in industrial IoT: A communication-efficient on-device federated learning approach

Y Liu, S Garg, J Nie, Y Zhang, Z **ong… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Since edge device failures (ie, anomalies) seriously affect the production of industrial
products in Industrial IoT (IIoT), accurately and timely detecting anomalies are becoming …

Multiple cloud storage mechanism based on blockchain in smart homes

Y Ren, Y Leng, J Qi, PK Sharma, J Wang… - Future Generation …, 2021 - Elsevier
The emergence of the smart home has fundamentally changed the quality of human living
owing to its usefulness and convenience. However, it still has some serious problems that …

Security threats, defense mechanisms, challenges, and future directions in cloud computing

S El Kafhali, I El Mir, M Hanini - Archives of Computational Methods in …, 2022 - Springer
Several new technologies such as the smart cities, the Internet of Things (IoT), and 5G
Internet need services offered by cloud computing for processing and storing more …

MLEsIDSs: machine learning-based ensembles for intrusion detection systems—a review

G Kumar, K Thakur, MR Ayyagari - The Journal of Supercomputing, 2020 - Springer
Network security plays an essential role in secure communication and avoids financial loss
and crippled services due to network intrusions. Intruders generally exploit the flaws of …

Improving artificial bee colony algorithm using a new neighborhood selection mechanism

H Wang, W Wang, S **ao, Z Cui, M Xu, X Zhou - Information Sciences, 2020 - Elsevier
Artificial bee colony (ABC) and its most modifications use a probability method to select
good food sources (called solutions) in the onlooker bee search phase. However, the …

[HTML][HTML] Towards green innovation in smart cities: Leveraging traffic flow prediction with machine learning algorithms for sustainable transportation systems

X Tao, L Cheng, R Zhang, WK Chan, H Chao, J Qin - Sustainability, 2023 - mdpi.com
The emergence of smart cities has presented the prospect of transforming urban
transportation systems into more sustainable and environmentally friendly entities. A pivotal …

[HTML][HTML] A metaheuristic-based ensemble feature selection framework for cyber threat detection in IoT-enabled networks

AK Dey, GP Gupta, SP Sahu - Decision Analytics Journal, 2023 - Elsevier
Abstract Internet of Things (IoT) enabled networks are highly vulnerable to cyber threats due
to insecure wireless communication, resource constraint architecture, different types of IoT …

An attention‐based deep learning model for traffic flow prediction using spatiotemporal features towards sustainable smart city

B Vijayalakshmi, K Ramar, NZ Jhanjhi… - International Journal …, 2021 - Wiley Online Library
In the development of smart cities, the intelligent transportation system (ITS) plays a major
role. The dynamic and chaotic nature of the traffic information makes the accurate …