Exploring the impact of ai-based cyber security financial sector management

S Mishra - Applied Sciences, 2023 - mdpi.com
Cyber threats are attempts to secure unauthorized access to, change, or delete private
information, to demand money from victims, or to disrupt business. Cybercrime includes …

M-MultiSVM: An efficient feature selection assisted network intrusion detection system using machine learning

AV Turukmane, R Devendiran - Computers & Security, 2024 - Elsevier
The intrusions are increasing daily, so there is a huge amount of privacy violations, financial
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …

Blockchain and Machine Learning-Based Hybrid IDS to Protect Smart Networks and Preserve Privacy

S Mishra - Electronics, 2023 - mdpi.com
The cyberspace is a convenient platform for creative, intellectual, and accessible works that
provide a medium for expression and communication. Malware, phishing, ransomware, and …

Hierarchical LSTM-Based Network Intrusion Detection System Using Hybrid Classification

J Han, W Pak - Applied Sciences, 2023 - mdpi.com
Most existing network intrusion detection systems (NIDSs) perform intrusion detection using
only a partial packet data of fixed size, but they suffer to increase the detection rate. In this …

Towards an AI-Enhanced Cyber Threat Intelligence Processing Pipeline

L Alevizos, M Dekker - Electronics, 2024 - mdpi.com
Cyber threats continue to evolve in complexity, thereby traditional cyber threat intelligence
(CTI) methods struggle to keep pace. AI offers a potential solution, automating and …

AI-powered intrusion detection in large-scale traffic networks based on flow sensing strategy and parallel deep analysis

HV Vo, HP Du, HN Nguyen - Journal of Network and Computer …, 2023 - Elsevier
Current intrusion detection systems, which rely on signature-based detection using rules
derived from the inspection of past traffic flows and their signatures, are incapable of …

A Machine Learning-Based Framework with Enhanced Feature Selection and Resampling for Improved Intrusion Detection

F Malik, Q Waqas Khan, A Rizwan, R Alnashwan… - Mathematics, 2024 - mdpi.com
Intrusion Detection Systems (IDSs) play a crucial role in safeguarding network
infrastructures from cyber threats and ensuring the integrity of highly sensitive data …

Deep learning-empowered intrusion detection framework for the Internet of Medical Things environment

PG Shambharkar, N Sharma - Knowledge and Information Systems, 2024 - Springer
The fusion of Internet of Things (IoT) technology into healthcare, known as the Internet of
Medical Things (IoMT), has significantly enhanced medical treatment and operational …

A Novel Hybrid Feature Selection with Cascaded LSTM: Enhancing Security in IoT Networks

K Sundaram, Y Natarajan… - Wireless …, 2024 - Wiley Online Library
The rapid growth of the Internet of Things (IoT) has created a situation where a huge amount
of sensitive data is constantly being created and sent through many devices, making data …

Artificial Intelligence driven Intrusion Detection Framework for the Internet of Medical Things

PG Shambharkar, N Sharma - 2023 - researchsquare.com
The fusion of the internet of things (IoT) in the healthcare discipline has appreciably
improved the medical treatment and operations activities of patients. Using the Internet of …