A comprehensive review on malware detection approaches

ÖA Aslan, R Samet - IEEE access, 2020 - ieeexplore.ieee.org
According to the recent studies, malicious software (malware) is increasing at an alarming
rate, and some malware can hide in the system by using different obfuscation techniques. In …

A survey on machine learning-based malware detection in executable files

J Singh, J Singh - Journal of Systems Architecture, 2021 - Elsevier
In last decade, a proliferation growth in the development of computer malware has been
done. Nowadays, cybercriminals (attacker) use malware as a weapon to carry out the …

A survey on encrypted network traffic analysis applications, techniques, and countermeasures

E Papadogiannaki, S Ioannidis - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The adoption of network traffic encryption is continually growing. Popular applications use
encryption protocols to secure communications and protect the privacy of users. In addition …

Knowing your enemy: understanding and detecting malicious web advertising

Z Li, K Zhang, Y Xie, F Yu, XF Wang - … of the 2012 ACM conference on …, 2012 - dl.acm.org
With the Internet becoming the dominant channel for marketing and promotion, online
advertisements are also increasingly used for illegal purposes such as propagating …

Intelligent behavior-based malware detection system on cloud computing environment

Ö Aslan, M Ozkan-Okay, D Gupta - IEEE Access, 2021 - ieeexplore.ieee.org
These days, cloud computing is one of the most promising technologies to store information
and provide services online efficiently. Using this rapidly developing technology to protect …

DroidEncoder: Malware detection using auto-encoder based feature extractor and machine learning algorithms

H Bakır, R Bakır - Computers and Electrical Engineering, 2023 - Elsevier
Android Malware detection became a hot topic over the last several years. Although
considerable studies have been conducted utilizing machine learning-based methods, little …

Ubl: Unsupervised behavior learning for predicting performance anomalies in virtualized cloud systems

DJ Dean, H Nguyen, X Gu - … of the 9th international conference on …, 2012 - dl.acm.org
Infrastructure-as-a-Service (IaaS) clouds are prone to performance anomalies due to their
complex nature. Although previous work has shown the effectiveness of using statistical …

CloudEyes: Cloud‐based malware detection with reversible sketch for resource‐constrained internet of things (IoT) devices

H Sun, X Wang, R Buyya, J Su - Software: Practice and …, 2017 - Wiley Online Library
Because of the rapid increasing of malware attacks on the Internet of Things in recent years,
it is critical for resource‐constrained devices to guard against potential risks. The traditional …

Bitav: Fast anti-malware by distributed blockchain consensus and feedforward scanning

C Noyes - arXiv preprint arXiv:1601.01405, 2016 - arxiv.org
I present the design and implementation of a novel anti-malware environment called BitAV.
BitAV allows for the decentralization of the update and maintenance mechanisms of the …

Challenges and pitfalls in malware research

M Botacin, F Ceschin, R Sun, D Oliveira, A Grégio - Computers & Security, 2021 - Elsevier
As the malware research field became more established over the last two decades, new
research questions arose, such as how to make malware research reproducible, how to …