@inbook{898c5f904c44474a95f34446bcecbe5e,
title = "Artificial neural network and partial pattern recognition to detect malware",
abstract = "Cyber Security is a challenging research area nowadays because of the continuously increasing dependency of people on the Internet for day-to-day activities. Secure data transfer is a critical matter of concern for users while using the Internet. Secure data transfer demands that the data should be from a reliable and authenticated source. Secure data transfer is essential to avoid malicious code variants or software aka hidden malware. Detecting malware is a critical task as the current generation malware uses rapidly evolving techniques, and gets hidden in a genuine-looking file. However, malware detection can get a lot more progress if we deploy a machine learning technique, such as Deep learning for this purpose.",
author = "Aparna Gautam and Rajesh Gopakumar and G. Deepa",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2020.",
year = "2020",
doi = "10.1007/978-981-15-3125-5_1",
language = "English",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Gabler",
pages = "1--8",
booktitle = "Lecture Notes in Electrical Engineering",
address = "Germany",
}