Analyzing the impact of cyber security related attributes for intrusion detection systems

A Alharbi, AH Seh, W Alosaimi, H Alyami, A Agrawal… - Sustainability, 2021 - mdpi.com
Machine learning (ML) is one of the dominating technologies practiced in both the industrial
and academic domains throughout the world. ML algorithms can examine the threats and …

[PDF][PDF] Cyber security analysis and evaluation for intrusion detection systems

YB Abushark, AI Khan, F Alsolami… - Comput. Mater …, 2022 - cdn.techscience.cn
Machine learning is a technique that is widely employed in both the academic and industrial
sectors all over the world. Machine learning algorithms that are intuitive can analyse risks …

[PDF][PDF] Multi-level hesitant fuzzy based model for usable-security assessment

M Nadeem, JF Al-Amri, AF Subahi… - … Automation & Soft …, 2022 - researchgate.net
Present day healthcare sector is frequently victimized by the intruders. Healthcare data
industry has borne the brunt of the highest number of data breach episodes in the last few …

Performance comparison and current challenges of using machine learning techniques in cybersecurity

K Shaukat, S Luo, V Varadharajan, IA Hameed, S Chen… - Energies, 2020 - mdpi.com
Cyberspace has become an indispensable factor for all areas of the modern world. The
world is becoming more and more dependent on the internet for everyday living. The …

A fuzzy based mcdm methodology for risk evaluation of cyber security technologies

M Erdoğan, A Karaşan, İ Kaya, A Budak… - Intelligent and Fuzzy …, 2020 - Springer
Cyber security that also known as information technology security is to protect computers,
mobile devices, servers, electronic systems and networks from malicious digital attacks. In …

Achieving organizational effectiveness through machine learning based approaches for malware analysis and detection

MA Haque, S Ahmad, D Sonal, HAM Abdeljaber… - Data and …, 2023 - dm.ageditor.ar
Introduction: as technology usage grows at an exponential rate, cybersecurity has become a
primary concern. Cyber threats have become increasingly advanced and specific, posing a …

[PDF][PDF] Towards Robust IDSs: An Integrated Approach of Hybrid Feature Selection and Machine Learning

M Al-Omari, QA Al-Haija - Journal of Internet Services and Information …, 2024 - jisis.org
Due to the rapid growth of technology, the urgency for effective cybersecurity systems has
become increasingly critical, notably within the paradigm of the Internet of Things (IoT) and …

[PDF][PDF] Automated Machine Learning Enabled Cybersecurity Threat Detection in Internet of Things Environment.

F Alrowais, S Althahabi, SS Alotaibi… - … Systems Science & …, 2023 - academia.edu
Recently, Internet of Things (IoT) devices produces massive quantity of data from distinct
sources that get transmitted over public networks. Cybersecurity becomes a challenging …

Application of machine learning (ML) to address cybersecurity threats

M Omar - Machine Learning for Cybersecurity: Innovative Deep …, 2022 - Springer
As cybersecurity threats keep growing exponentially in scale, frequency, and impact, legacy-
based threat detection systems have proven inadequate. This has prompted the use of …

Cyber intrusion detection using machine learning classification techniques

H Alqahtani, IH Sarker, A Kalim… - … and Security: First …, 2020 - Springer
As the alarming growth of connectivity of computers and the significant number of computer-
related applications increase in recent years, the challenge of fulfilling cyber-security is …