Results 11 to 20 of about 81,305 (190)

MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware

2023 IEEE International Conference on Intelligence and Security Informatics (ISI), 2023
Malware is one of the most dangerous and costly cyber threats to national security and a crucial factor in modern cyber-space. However, the adoption of machine learning (ML) based solutions against malware threats has been relatively slow. Shortcomings in the existing ML approaches are likely contributing to this problem.
Eren, Maksim E., Bhattarai, Manish, Rasmussen, Kim, Alexandrov, Boian S., Nicholas, Charles   +4 more
openaire   +2 more sources

Adaptive secure malware efficient machine learning algorithm for healthcare data

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed, Abdullah Lakhan, Dilovan Asaad Zebari, Karrar Hameed Abdulkareem, Jan Nedoma, Radek Martinek, Usman Tariq, Majed Alhaisoni, Prayag Tiwari   +8 more
wiley   +1 more source

A multilabel fuzzy relevance clustering system for malware attack attribution in the edge layer of cyber-physical networks [PDF]

, 2020
The rapid increase in the number of malicious programs has made malware forensics a daunting task and caused users’ systems to become in danger. Timely identification of malware characteristics including its origin and the malware sample family would ...
Alaeiyan, M, Conti, M, Dargahi, T, Dehghantanha, A, Parsa, S   +4 more
core   +2 more sources

Binary and Multi-Class Malware Threads Classification

Applied Sciences, 2022
The security of a computer system can be harmed by specific applications, such as malware. Malware comprises unwanted, dangerous enemies that aim to compromise the security and generate significant loss.
Ismail Taha Ahmed, Norziana Jamil, Marina Md. Din, Baraa Tareq Hammad   +3 more
doaj   +1 more source

Robust Malware Family Classification Using Effective Features and Classifiers

Applied Sciences, 2022
Malware development has significantly increased recently, posing a serious security risk to both consumers and businesses. Malware developers continually find new ways to circumvent security research’s ongoing efforts to guard against malware attacks ...
Baraa Tareq Hammad, Norziana Jamil, Ismail Taha Ahmed, Zuhaira Muhammad Zain, Shakila Basheer   +4 more
doaj   +1 more source

Intensive Malware Detection Approach based on Data Mining

Journal of Applied Engineering and Technological Science, 2023
Malicious software, sometimes known as malware, is software designed to harm a computer, network, or any of the connected resources. Without the user's knowledge, malware can spread throughout their computer system. Malware is typically disseminated via
Israa Ezzat Salem, Karim Hashim Al-Saedi
doaj   +1 more source

SoK: Cryptojacking Malware [PDF]

2021 IEEE European Symposium on Security and Privacy (EuroS&P), 2021
Emerging blockchain and cryptocurrency-based technologies are redefining the way we conduct business in cyberspace. Today, a myriad of blockchain and cryptocurrency systems, applications, and technologies are widely available to companies, end-users, and even malicious actors who want to exploit the computational resources of regular users through ...
Tekiner, Ege, Acar, Aktan, Uluagac, A. Selçuk, Kırda, E., Selçuk, Ali Aydın   +4 more
openaire   +3 more sources

Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework

IEEE Access, 2019
Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern.
Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles   +6 more
doaj   +1 more source

A Comprehensive Review on Malware Detection Approaches

IEEE Access, 2020
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.
Omer Aslan, Refik Samet
doaj   +1 more source

A Hybrid Approach for Android Malware Detection and Family Classification.

International Journal of Interactive Multimedia and Artificial Intelligence, 2021
With the increase in the popularity of mobile devices, malicious applications targeting Android platform have greatly increased. Malware is coded so prudently that it has become very complicated to identify.
Meghna Dhalaria, Ekta Gandotra
doaj   +1 more source