SCI/SCIE Indexed Articles 

1. Arvind Mahindru and A.L. Sangal.  (2020). MLDroid—framework for Android malware detection using machine learning techniques. Neural Computing and Applications. [IF: 5.102] [DOI: https://doi.org/10.1007/s00521-020-05309-4]

2. Arvind Mahindru and A.L. Sangal. (2020). SemiDroid: a behavioral malware detector based on unsupervised machine learning techniques using feature selection approaches. International Journal of Machine Learning and Cybernetics. [IF: 4.377] [DOI: https://doi.org/10.1007/s13042-020-01238-9]

3. Arvind Mahindru and A.L. Sangal. (2021). FSDroid: - A feature selection technique to detect malware from Android using Machine Learning Techniques. Multimedia Tools and Applications. [IF: 2.577] [DOI: https://doi.org/10.1007/s11042-020-10367-w]

4. Arvind Mahindru and A.L. Sangal. (2021). HybriDroid:  An Empirical Analysis on Effective Malware Detection Model Developed using Ensemble Methods. The Journal of Supercomputing. [IF: 2.557] [DOI: https://doi.org/10.1007/s11227-020-03569-4]

Scopus/Emerging Sources Citation Indexed Articles 

1. Arvind Mahindru and A.L. Sangal.  (2020). SOMDROID: android malware detection by artificial neural network trained using unsupervised learning. Evolutionary Intelligence. [DOI: https://doi.org/10.1007/s12065-020-00518-1]

2. Arvind Mahindru and A.L. Sangal.  (2020). Dldroid: feature selection based malware detection framework for android apps developed during covid-19. International Journal on Emerging Technologies.

3.  Arvind Mahindru and A.L. Sangal.  (2020). Gadroid: a framework for malware detection from android by using genetic algorithm as feature selection approach. International Journal of Advanced Science and Technology.