Intrusion detection approach based on optimised artificial neural network

M Choraś, M Pawlicki - Neurocomputing, 2021 - Elsevier
Abstract Context and rationale Intrusion Detection, the ability to detect malware and other
attacks, is a crucial aspect to ensure cybersecurity. So is the ability to identify this myriad of …

Malware: An overview on threats, detection and evasion attacks

N Fleury, T Dubrunquez, I Alouani - arXiv preprint arXiv:2107.12873, 2021 - arxiv.org
In the recent years, Portable Document Format, commonly known as PDF, has become a
democratized standard for document exchange and dissemination. This trend has been due …

A comparative evaluation of ensemble classifiers for malicious webpage detection

A Subasi, M Balfaqih, Z Balfagih, K Alfawwaz - Procedia Computer Science, 2021 - Elsevier
Malicious webpage is developed or manipulated to be used as attack tool where it is
considered as one of the main reasons of Internet criminal activities. Thus, it is essential to …

Hardware-assisted malware detection using machine learning

Z Pan, J Sheldon, C Sudusinghe… - … , Automation & Test …, 2021 - ieeexplore.ieee.org
Malicious software, popularly known as malware, is a serious threat to modern computing
systems. A comprehensive cybercrime study by Ponemon Institute highlights that malware is …

[PDF][PDF] An Overview: Stochastic Gradient Descent Classifier, Linear Discriminant Analysis, Deep Learning and Naive Bayes Classifier Approaches to Network Intrusion …

O Osho, S Hong - International Journal of Engineering and Technical …, 2021 - academia.edu
The security of Network Systems is ravaged by attacks on Systems in a bid to gain
unauthorized access into the network system. The aim of Network Intrusion Detection …

Runtime malware detection using embedded trace buffers

R Elnaggar, K Basu, K Chakrabarty… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Anti-virus software (AVS) tools are used to detect malware in a system. However, AVS are
vulnerable to attacks. A malicious entity can exploit these vulnerabilities to subvert the AVS …

Malware detection system using ensemble learning: Tested using synthetic data

R Kaushik, M Dave - Data Engineering and Communication Technology …, 2021 - Springer
Malwares refer to the malicious programs that are used to exploit the target system's
vulnerabilities, such as a bug or a legitimate software. Malware infiltration can have …

[PDF][PDF] A Survey Paper on Machine Learning Approaches to Intrusion Detection

O Osho, S Hong - International Journal of Engineering Research & …, 2021 - academia.edu
This electronic document is a “live” template and already defines the components of your
paper [title, text, heads, etc.] in its style sheet. For any nation, government, or cities to …

[PDF][PDF] An Efficient Approach for Unknown Malware Detection Based on Opcode Analysis

F Manavi, A Hamzeh - Tabriz Journal of Electrical Engineering, 2021 - journals.tabrizu.ac.ir
Today, with the development of computer systems, malware has grown dramatically.
Malware is defined as a program that is developed with malicious purpose, such as …

Detection of worms over cloud environment: a literature survey

M Thangavel, B Jeyapriya, KS Suriya - Research Anthology on …, 2021 - igi-global.com
In recent years, computer worms are the remarkable difficulties found in the distributed
computing. The location of worms turns out to be more unpredictable since they are …