Malware detection issues, challenges, and future directions: A survey

FA Aboaoja, A Zainal, FA Ghaleb, BAS Al-Rimy… - Applied Sciences, 2022 - mdpi.com
The evolution of recent malicious software with the rising use of digital services has
increased the probability of corrupting data, stealing information, or other cybercrimes by …

A survey of the recent trends in deep learning based malware detection

UH Tayyab, FB Khan, MH Durad, A Khan… - Journal of Cybersecurity …, 2022 - mdpi.com
Monitoring Indicators of Compromise (IOC) leads to malware detection for identifying
malicious activity. Malicious activities potentially lead to a system breach or data …

A deep recurrent neural network based approach for internet of things malware threat hunting

H HaddadPajouh, A Dehghantanha, R Khayami… - Future Generation …, 2018 - Elsevier
Abstract Internet of Things (IoT) devices are increasingly deployed in different industries and
for different purposes (eg sensing/collecting of environmental data in both civilian and …

Opcode sequences as representation of executables for data-mining-based unknown malware detection

I Santos, F Brezo, X Ugarte-Pedrero, PG Bringas - information Sciences, 2013 - Elsevier
Malware can be defined as any type of malicious code that has the potential to harm a
computer or network. The volume of malware is growing faster every year and poses a …

Fuzzy pattern tree for edge malware detection and categorization in IoT

EM Dovom, A Azmoodeh, A Dehghantanha… - Journal of Systems …, 2019 - Elsevier
The surging pace of Internet of Things (IoT) development and its applications has resulted in
significantly large amounts of data (commonly known as big data) being communicated and …

A survey on heuristic malware detection techniques

Z Bazrafshan, H Hashemi, SMH Fard… - The 5th conference on …, 2013 - ieeexplore.ieee.org
Malware is a malicious code which is developed to harm a computer or network. The
number of malwares is growing so fast and this amount of growth makes the computer …

A survey of binary code similarity

IU Haq, J Caballero - Acm computing surveys (csur), 2021 - dl.acm.org
Binary code similarityapproaches compare two or more pieces of binary code to identify their
similarities and differences. The ability to compare binary code enables many real-world …

Detecting cryptomining malware: a deep learning approach for static and dynamic analysis

H Darabian, S Homayounoot, A Dehghantanha… - Journal of Grid …, 2020 - Springer
Cryptomining malware (also referred to as cryptojacking) has changed the cyber threat
landscape. Such malware exploits the victim's CPU or GPU resources with the aim of …

An improved two-hidden-layer extreme learning machine for malware hunting

AN Jahromi, S Hashemi, A Dehghantanha… - Computers & …, 2020 - Elsevier
Detecting unknown malware and their variants remains both an operational challenge and a
research challenge. In recent years, there have been attempts to design machine learning …

Semantics-based online malware detection: Towards efficient real-time protection against malware

S Das, Y Liu, W Zhang… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Recently, malware has increasingly become a critical threat to embedded systems, while the
conventional software solutions, such as antivirus and patches, have not been so successful …