Year: 2023
Type: conference-paper
Abstract: Nowadays malware detection is a very important task in information security. Criminals are constantly looking for new ways to attack computer networks and systems, so it is important to have a reliable mechanism to detect and prevent these threats. Existing anti-virus programs are not always effective in detecting new types of viruses or malware, which can compromise your system and steal important information. Therefore, it is critically important to investigate and create new methods for detecting malicious software, especially using modern technologies like Blockchain. One of the ways to detect malicious software is to use deep learning algorithms. For this, a Deep Learning Algorithm using Blockchain technology was developed to detect malicious programs. The basic idea is to use the blockchain to ensure security and accuracy of malware detection. The algorithm proposed in this work is based on the subsystems and Proof-of-Action. The first mechanism provides parallel analysis of potentially dangerous software by different participants. The second mechanism is used to validate the results of analysis and increase the accuracy of detection. The application of the proposed approach allows to detect malicious software with an accuracy of from 98.81% to 99.33%, which is quite a high result.
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7166334378