PCP Framework to Expose Malware in Devices
Rahul Nigam, Rohit Kumar Pathak, Arun Kumar, Shiv Prakash · 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC) · 2020
Cybersecurity is the biggest threat to the world economy. Nowadays, the internet is the main cause of increase the cybercrime and help the attacker to act to harm the victim system. The attacks and exploits are becoming more sophisticated and harder to detect. The attacker uses new techniques and processes to steal important information from the system. A cyber attacker creates malware to damage system and gains unauthorized access. The signature-based and pattern analysis of malicious code is not effective and efficient for malware detection. In this paper, proposed a new framework to detect the malware in devices using the combination of blockchain technology and machine learning algorithm. The main objective of this research is to improve the false-positive and false-negative rate to increase the accuracy of malware detection in devices. The other significance of this paper is to identify the new type of malware which cannot be identified yet using the signature method and pattern method. The experimental result shows better accuracy, precision for detecting the malware.