Results 11 to 20 of about 707,343 (186)

Biserial Miyaguchi–Preneel Blockchain-Based Ruzicka-Indexed Deep Perceptive Learning for Malware Detection in IoMT

Sensors, 2021
Detection of unknown malware and its variants remains both an operational and a research challenge in the Internet of Things (IoT). The Internet of Medical Things (IoMT) is a particular type of IoT network which deals with communication through smart ...
Abdullah Shawan Alotaibi
doaj   +1 more source

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

Evaluation of Survivability of the Automatically Obfuscated Android Malware

Applied Sciences, 2022
Malware is a growing threat to all mobile platforms and hundreds of new malicious applications are being detected every day. At the same time, the development of automated software obfuscation techniques allows for the easy production of new malware ...
Himanshu Patel, Deep Patel, Jaspreet Ahluwalia, Vaishali Kapoor, Karthik Narasimhan, Harmanpreet Singh, Harmanjot Kaur, Gadi Harshitha Reddy, Sai Sushma Peruboina, Sergey Butakov   +9 more
doaj   +1 more source

A Proposed Artificial Intelligence Model for Android-Malware Detection

Informatics, 2023
There are a variety of reasons why smartphones have grown so pervasive in our daily lives. While their benefits are undeniable, Android users must be vigilant against malicious apps.
Fatma Taher, Omar Al Fandi, Mousa Al Kfairy, Hussam Al Hamadi, Saed Alrabaee   +4 more
doaj   +1 more source

IoT malware detection architecture using a novel channel boosted and squeezed CNN

Scientific Reports, 2022
Interaction between devices, people, and the Internet has given birth to a new digital communication model, the internet of things (IoT). The integration of smart devices to constitute a network introduces many security challenges.
Muhammad Asam, Saddam Hussain Khan, Altaf Akbar, Sameena Bibi, Tauseef Jamal, Asifullah Khan, Usman Ghafoor, Muhammad Raheel Bhutta   +7 more
doaj   +1 more source

Toward Hardware-Assisted Malware Detection Utilizing Explainable Machine Learning: A Survey

IEEE Access, 2023
Hardware joined the battle against malware by introducing secure boot architectures, malware-aware processors, and trusted platform modules. Hardware performance indicators, power profiles, and side channel information can be leveraged at run-time via ...
Yehya Nasser, Mohamad Nassar
doaj   +1 more source

Application of Distance Metric Learning to Automated Malware Detection

IEEE Access, 2021
Distance metric learning aims to find the most appropriate distance metric parameters to improve similarity-based models such as $k$ -Nearest Neighbors or $k$ -Means. In this paper, we apply distance metric learning to the problem of malware detection.
Martin Jurecek, Robert Lorencz
doaj   +1 more source

A Two-Layer Deep Learning Method for Android Malware Detection Using Network Traffic

IEEE Access, 2020
Because of the characteristic of openness and flexibility, Android has become the most popular mobile platform. However, it has also become the most targeted system by mobile malware.
Jiayin Feng, Limin Shen, Zhen Chen, Yuying Wang, Hui Li   +4 more
doaj   +1 more source

A Novel Neural Network Architecture Using Automated Correlated Feature Layer to Detect Android Malware Applications

Mathematics, 2023
Android OS devices are the most widely used mobile devices globally. The open-source nature and less restricted nature of the Android application store welcome malicious apps, which present risks for such devices.
Amerah Alabrah
doaj   +1 more source

MACoMal: A Multi-Agent Based Collaborative Mechanism for Anti-Malware Assistance

IEEE Access, 2020
Anti-malware tools remain the primary line of defense against malicious software. There is a wide variety of commercial anti-malware tools in the IT security market.
Mohamed Belaoued, Abdelouahid Derhab, Smaine Mazouzi, Farrukh Aslam Khan   +3 more
doaj   +1 more source