Malware Attack Forecasting by Using Exponential Smoothing

Author:

Abas Mohd Nizamuddin,Jalil Siti Zura A.,Aris Siti Armiza Mohd

Publisher

Springer Singapore

Reference19 articles.

1. Panker T, Nissim N (2021) Leveraging malicious behavior traces from volatile memory using machine learning methods for trusted unknown malware detection in Linux cloud environments. Knowl.-Based Syst 226:107095

2. Rhode M, Burnap P, Jones K (2019) Early-stage malware prediction using recurrent neural networks. In: Elsevier

3. M. C. E. R. T. (MYCERT): Malaysia botnet drones and malware infection (2020) In: Report

4. O. T. I. C. C. E. R. T. (OIC-CERT): Malware Trend Report H1 2019 (2019). In: Organisation of The Islamic Cooperation – Computer Emergency Response Teams (OIC-CERT), Report. https://www.oic-cert.org/en/malwarereport.html#.XgDLbvxS-Uk

5. Deli MSM, Ismail SA, Kama N, Yusop OM, Azmi A, Yahya Y (2017) Malware log files for Internet investigation using hadoop: a review. In: IEEE Conference on Big Data and Analytics (2017)

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