A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions

A Thakkar, R Lohiya - Artificial Intelligence Review, 2022 - Springer
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …

Detecting and preventing cyber insider threats: A survey

L Liu, O De Vel, QL Han, J Zhang… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Information communications technology systems are facing an increasing number of cyber
security threats, the majority of which are originated by insiders. As insiders reside behind …

Drishti: an integrated indoor/outdoor blind navigation system and service

L Ran, S Helal, S Moore - Second IEEE annual conference on …, 2004 - ieeexplore.ieee.org
There are many navigation systems for visually impaired people but few can provide
dynamic interactions and adaptability to changes. None of these systems work seamlessly …

A feature-hybrid malware variants detection using CNN based opcode embedding and BPNN based API embedding

J Zhang, Z Qin, H Yin, L Ou, K Zhang - Computers & Security, 2019 - Elsevier
Being able to detect malware variants is a critical problem due to the potential damages and
the fast paces of new malware variations. According to surveys from McAfee and Symantec …

MDCHD: A novel malware detection method in cloud using hardware trace and deep learning

D Tian, Q Ying, X Jia, R Ma, C Hu, W Liu - Computer Networks, 2021 - Elsevier
With the development of cloud computing, more and more enterprises and institutes have
deployed important computing tasks and data into virtualization environments. Virtualization …

[PDF][PDF] A multi-level ransomware detection framework using natural language processing and machine learning

S Poudyal, D Dasgupta, Z Akhtar… - … Conference on Malicious …, 2019 - researchgate.net
Ransomware attacks in recent years have proved expensive due to significant damages and
obstructions these caused in various sectors such as health, insurance, business, and …

Analysis of crypto-ransomware using ML-based multi-level profiling

S Poudyal, D Dasgupta - Ieee Access, 2021 - ieeexplore.ieee.org
Crypto-ransomware is the most prevalent form of modern malware, has affected various
industries, demanding a significant amount of ransom. Mainly, small businesses, healthcare …

API call-based malware classification using recurrent neural networks

C Li, J Zheng - Journal of Cyber Security and Mobility, 2021 - journals.riverpublishers.com
Malicious software, called malware, can perform harmful actions on computer systems,
which may cause economic damage and information leakage. Therefore, malware …

AI-powered ransomware detection framework

S Poudyal, D Dasgupta - 2020 IEEE Symposium Series on …, 2020 - ieeexplore.ieee.org
Ransomware attacks are taking advantage of the ongoing pandemics and attacking the
vulnerable systems in business, health sector, education, insurance, bank, and government …

MDGraph: A novel malware detection method based on memory dump and graph neural network

Q Li, B Zhang, D Tian, X Jia, C Hu - Expert Systems with Applications, 2024 - Elsevier
Malware detection is of great importance to computer security. Although the malware
detection approaches have made great progress in recent years, these methods are still …