# Features Engineering to Differentiate between Malware and Legitimate Software
## 5 API Call Visualisation
(2013) [PERSON]; [PERSON]; [PERSON]; [PERSON] Analyzing malware by abstracting the frequent itemsets in API call sequences. In Proceedings of the 2013 12 th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, IEEE, Melbourne, Australia, 16-18 July 2013; pp. 265-270. * [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON] An approach for detection and family classification of malware based on behavioral analysis. In Proceedings of the 2016 International Conference on Computing, Networking and Communications (ICNC), IEEE, Kauai, HI, USA, 15-18 February 2016; pp. 1-5. * [PERSON] and [PERSON] (2021) [PERSON]; [PERSON] API call-based malware classification using recurrent neural networks. _J. Cyber Secur. Mobil._**2021**, _10_, 617-640. [CrossRef]
* [PERSON] et al. (2012) [PERSON]; [PERSON]; [PERSON] To incorporate sequential dynamic features in malware detection engines. In Proceedings of the 2012 European Intelligence and Security Informatics Conference, IEEE, Odense, Denmark, 22-24 August 2012; pp. 46-52. * [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] [PERSON] Behavioral malware detection using deep graph convolutional neural networks. _TechRxiv_**2019**, preprint. [CrossRef]
* [PERSON] and [PERSON] (2019) [PERSON]; [PERSON] Dynamic API call sequence visualisation for malware classification. _IET Inf. Secur._**2019**, _13_, 367-377. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Convolutional neural network for malware classification based on API call sequence. In Proceedings of the 8 th International Conference on Artificial Intelligence and Applications (AIAP 2021), Zurich, Switzerland, 23-24 January 2021. * [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] MALGRA: Machine learning and N-gram malware feature extraction and detection system. _Electronics_**2020**, \(9\), 1777. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] Comparing Deep Learning and Shallow Learning Techniques for API Calls Malware Prediction: A Study. _Appl. Sci._**2022**, _12_, 1645. [CrossRef]
* [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON] Features Engineering for Malware Family Classification Based API Call. _Computers_**2022**, _11_, 160. [CrossRef]
* [PERSON] (2022) [PERSON] Malware Analysis Datasets: API Call Sequences. 2022. Available online: [[https://ieee-dataport.org/open-access/malware-analysis-datasets-api-call-sequences](https://ieee-dataport.org/open-access/malware-analysis-datasets-api-call-sequences)]([https://ieee-dataport.org/open-access/malware-analysis-datasets-api-call-sequences](https://ieee-dataport.org/open-access/malware-analysis-datasets-api-call-sequences)) (accessed on 10 July 2022). * [PERSON] (2018) [PERSON] _Data Science and Analytics with Python_; Chapman and Hall/CRC: Boca Raton, FL, USA, 2018. * [PERSON] (2018) [PERSON]; [PERSON] _Malware Data Science: Attack Detection and Attribution_; No Starch Press: San Francisco, CA, USA, 2018. * Networkx (2022) Networkx. Networkx Networkx Analysis in Python. 2022. Available online: [[https://networkx.org/](https://networkx.org/)]([https://networkx.org/](https://networkx.org/)) (accessed on 15 October 2022). * [46] Graphviz. What is Graphviz? 2022. Available online: [[https://graphviz.org/](https://graphviz.org/)]([https://graphviz.org/](https://graphviz.org/)) (accessed on 20 October 2022). * [47] VirusTotal. VirusTotal API v3 Overview. 2022. Available online: [[https://developers.virustotal.com/reference/overview](https://developers.virustotal.com/reference/overview)]([https://developers.virustotal.com/reference/overview](https://developers.virustotal.com/reference/overview)) (accessed on 16 October 2022). **Disclaimer/Publisher's Note**: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s).