A Survey on Anomaly Based Malware Detection and Demolition in False Alarm Rate

Abstract

The term malware stands for malicious software. Malwares are malicious program which are installed by third party on a system without the knowledge of owner of the system with the intention of causing harm to the victim. As internet grow rapidly and numerous applications use it as a larger communication media. Many organizations are Internet dependent for their working methodology. This threat is increased with the flood of population with stable Internet access is just like honey pot for malware developers. Although anomaly detection has received significant attention, the automatic classification anomalies still remains an open problem. In our proposed method researcher are going to use combine two approaches like link anomaly detection and text anomaly detection. This model of anomaly detection will use data from application, files, text, words, etc. Bayesian model will be used for classification of event into anomaly or non-anomaly.