A framework for zero-day vulnerabilities detection and prioritization

摘要: Abstract Nowadays highly-skilled attackers can find the vulnerabilities of many networked applications. Meanwhile, risk a data breach increases dramatically as software or application vulnerability always remains without patch. By exploiting such (called zero-day), hackers gain entry to target network and steal sensitive data. It is challenging detect zero-day with traditional defenses because signature information in attacks unknown. Consequently, novel security solution required that will discover estimate severity identified vulnerability. In this paper, we propose framework constitutes an integrated approach for detection prioritization (based on likelihood) attacks. The proposed follows probabilistic identification attack path further rank hybrid detection-based technique detects unknown flaws present are not detected yet. To evaluate performance framework, adopted it environment Vikram university campus, India. very promising experimental results showed rate 96% 0.3% false positive rate.