[HTML][HTML] Deep residual learning for image recognition: A survey

M Shafiq, Z Gu - Applied Sciences, 2022 - mdpi.com
Deep Residual Networks have recently been shown to significantly improve the
performance of neural networks trained on ImageNet, with results beating all previous …

[HTML][HTML] Cyber security in iot-based cloud computing: A comprehensive survey

W Ahmad, A Rasool, AR Javed, T Baker, Z Jalil - Electronics, 2021 - mdpi.com
Cloud computing provides the flexible architecture where data and resources are dispersed
at various locations and are accessible from various industrial environments. Cloud …

Future smart cities: Requirements, emerging technologies, applications, challenges, and future aspects

AR Javed, F Shahzad, S ur Rehman, YB Zikria… - Cities, 2022 - Elsevier
Future smart cities are the key to fulfilling the ever-growing demands of citizens. Information
and communication advancements will empower better administration of accessible …

Explainable artificial intelligence in cybersecurity: A survey

N Capuano, G Fenza, V Loia, C Stanzione - IEEE Access, 2022 - ieeexplore.ieee.org
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …

[HTML][HTML] A comprehensive review of cyber security vulnerabilities, threats, attacks, and solutions

Ö Aslan, SS Aktuğ, M Ozkan-Okay, AA Yilmaz, E Akin - Electronics, 2023 - mdpi.com
Internet usage has grown exponentially, with individuals and companies performing multiple
daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) …

A comprehensive survey on computer forensics: State-of-the-art, tools, techniques, challenges, and future directions

AR Javed, W Ahmed, M Alazab, Z Jalil, K Kifayat… - IEEE …, 2022 - ieeexplore.ieee.org
With the alarmingly increasing rate of cybercrimes worldwide, there is a dire need to combat
cybercrimes timely and effectively. Cyberattacks on computing machines leave certain …

Deep learning for phishing detection: Taxonomy, current challenges and future directions

NQ Do, A Selamat, O Krejcar, E Herrera-Viedma… - Ieee …, 2022 - ieeexplore.ieee.org
Phishing has become an increasing concern and captured the attention of end-users as well
as security experts. Existing phishing detection techniques still suffer from the deficiency in …

[HTML][HTML] A survey of machine learning-based solutions for phishing website detection

L Tang, QH Mahmoud - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
With the development of the Internet, network security has aroused people's attention. It can
be said that a secure network environment is a basis for the rapid and sound development of …

[HTML][HTML] Applications of deep learning for phishing detection: a systematic literature review

C Catal, G Giray, B Tekinerdogan, S Kumar… - … and Information Systems, 2022 - Springer
Phishing attacks aim to steal confidential information using sophisticated methods,
techniques, and tools such as phishing through content injection, social engineering, online …

DIDDOS: An approach for detection and identification of Distributed Denial of Service (DDoS) cyberattacks using Gated Recurrent Units (GRU)

S ur Rehman, M Khaliq, SI Imtiaz, A Rasool… - Future Generation …, 2021 - Elsevier
Abstract Distributed Denial of Service (DDoS) attacks can put the communication networks
in instability by throwing malicious traffic and requests in bulk over the network. Computer …