Next-generation antivirus endowed with web-server Sandbox applied to audit fileless attack

Almost all malwares running on web-server are php codes. Then, the present paper creates a next generation antivirus (NGAV) expert in auditing threats web-based, specifically from files, real time. In our methodology, malicious behaviors, of personal computer, serve as input attributes statistical learning machines. all, dynamic feature extraction monitors 11,777 behaviors that web fileless attack can do when launched directly to listening service computer. Our NGAV achieves an average 99.95% accuracy distinction between benign and malware scripts. Distinct initial conditions kernels neural networks classifiers investigated order maximize NGAV. supply limitations commercial antiviruses for detection Web attack. opposition analysis individual events, engine employs authorial Web-server Sandbox, machine learning, artificial intelligence identify Web-sites.