[HTML][HTML] Evolving techniques in cyber threat hunting: A systematic review

A Mahboubi, K Luong, H Aboutorab, HT Bui… - Journal of Network and …, 2024 - Elsevier
In the rapidly changing cybersecurity landscape, threat hunting has become a critical
proactive defense against sophisticated cyber threats. While traditional security measures …

Machine learning algorithm for malware detection: Taxonomy, current challenges, and future directions

NZ Gorment, A Selamat, LK Cheng, O Krejcar - IEEE Access, 2023 - ieeexplore.ieee.org
Malware has emerged as a cyber security threat that continuously changes to target
computer systems, smart devices, and extensive networks with the development of …

Efficient and generalized image-based CNN algorithm for multi-class malware detection

Y Liu, H Fan, J Zhao, J Zhang, X Yin - IEEE Access, 2024 - ieeexplore.ieee.org
With the popularity of electronic devices, the number of malware has increased dramatically,
posing a serious threat to the digital world. Accurately identifying malware has become a …

Enhancing Cyber Security through Predictive Analytics: Real-Time Threat Detection and Response

M Danish - arxiv preprint arxiv:2407.10864, 2024 - arxiv.org
This research paper aims to examine the applicability of predictive analytics to improve the
real-time identification and response to cyber-attacks. Today, threats in cyberspace have …

A recent research on malware detection using machine learning algorithm: Current challenges and future works

NZ Gorment, A Selamat, O Krejcar - Advances in Visual Informatics: 7th …, 2021 - Springer
Each year, malware issues remain one of the cybersecurity concerns since malware's
complexity is constantly changing as the innovation rapidly grows. As a result, malware …

Математичні методи в кібербезпеці: кластерний аналіз та його застосування в інформаційній та кібернетичній безпеці

СМ Шевченко, ЮД Жданова… - Електронне …, 2024 - elibrary.kubg.edu.ua
Величезна кількість інформаційних загроз та їх складність спонукає до досліджень та
моделювання нових методологій та систем захисту інформації. Розробка та …

Selective targeted transfer learning for malware classification

P Aggarwal, SF Ahamed, S Shetty… - 2021 Third IEEE …, 2021 - ieeexplore.ieee.org
Data driven machine learning and deep neural models demand accessibility to high-quality,
clean, and enormous datasets. Obtaining a labeled dataset is an expensive, challenging …

[PDF][PDF] K-means Clustering of Honeynet Data with Unsupervised Representation Learning.

A Kashtalian, T Sochor - IntelITSIS, 2021 - academia.edu
Networks connected to the Internet are vulnerable to malicious activity that threaten the
stability of work. The types and characteristics of malicious actions are constantly changing …

Pola Pengelompokan dan Pencegahan Public Honeypot menggunakan Teknik K-Means dan Automation Shell-Script

HA DAMANIK, M ANGGRAENI - ELKOMIKA: Jurnal Teknik …, 2024 - ejurnal.itenas.ac.id
Makalah ini mengimplementasikan sistem log honeypot untuk menganalisis eksploitasi dari
global internet berupa kategori serangan Statistical Traffic Analysis, Top Targeted Attack …

[PDF][PDF] Malware detection method based on file and registry operations using machine learning

Ö Aslan, E Akin - Sakarya University Journal of Computer and …, 2022 - dergipark.org.tr
Abstract Malware (Malicious Software) is any software which performs malicious activities on
computer-based systems without the user's consent. The number, severity, and complexity of …