Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization S Kaur, LK Awasthi, AL Sangal, G Dhiman Engineering Applications of Artificial Intelligence 90, 103541, 2020 | 976 | 2020 |
MLDroid—framework for Android malware detection using machine learning techniques A Mahindru, AL Sangal Neural Computing and Applications 33 (10), 5183-5240, 2021 | 149 | 2021 |
Performance evaluation of two reactive routing protocols of MANET using group mobility model HS Bindra, SK Maakar, AL Sangal International Journal of Computer Science 7 (3), 38-43, 2010 | 109 | 2010 |
Characterizing flash events and distributed denial‐of‐service attacks: an empirical investigation A Bhandari, AL Sangal, K Kumar Security and Communication Networks 9 (13), 2222-2239, 2016 | 77 | 2016 |
FSDroid:-A feature selection technique to detect malware from Android using Machine Learning Techniques: FSDroid A Mahindru, AL Sangal Multimedia Tools and Applications 80, 13271-13323, 2021 | 55 | 2021 |
Simulation modeling of cloud computing for smart grid using CloudSim S Mehmi, HK Verma, AL Sangal Journal of Electrical Systems and Information Technology 4 (1), 159-172, 2017 | 51 | 2017 |
Quantitative measurement and comparison of effects of various search engine optimization parameters on Alexa Traffic Rank A Thakur, AL Sangal, H Bindra International Journal of Computer Applications 26 (5), 15-23, 2011 | 37 | 2011 |
SemiDroid: a behavioral malware detector based on unsupervised machine learning techniques using feature selection approaches A Mahindru, AL Sangal International Journal of Machine Learning and Cybernetics 12 (5), 1369-1411, 2021 | 35 | 2021 |
Community detection in social networks based on fire propagation HS Pattanayak, AL Sangal, HK Verma Swarm and evolutionary computation 44, 31-48, 2019 | 32 | 2019 |
Destination address entropy based detection and traceback approach against distributed denial of service attacks A Bhandari, AL Sangal, K Kumar International Journal of Computer Network and Information Security 7 (8), 9, 2015 | 32 | 2015 |
Building a hierarchical structure model of enablers that affect the software process improvement in software SMEs—A mixed method approach P Sharma, AL Sangal Computer Standards & Interfaces 66, 103350, 2019 | 29 | 2019 |
Traceback techniques against DDOS attacks: a comprehensive review K Kumar, AL Sangal, A Bhandari 2011 2nd International Conference on Computer and Communication Technology …, 2011 | 28 | 2011 |
SOMDROID: Android malware detection by artificial neural network trained using unsupervised learning A Mahindru, AL Sangal Evolutionary Intelligence 15 (1), 407-437, 2022 | 27 | 2022 |
HMOSHSSA: a hybrid meta-heuristic approach for solving constrained optimization problems S Kaur, LK Awasthi, AL Sangal Engineering with Computers 37 (4), 3167-3203, 2021 | 26 | 2021 |
Deepdroid: feature selection approach to detect android malware using deep learning A Mahindru, AL Sangal 2019 IEEE 10th International Conference on Software Engineering and Service …, 2019 | 24 | 2019 |
Modeling and simulation of adaptive neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks R Kaur, AL Sangal, K Kumar Engineering Science and Technology, an International Journal 20 (1), 310-320, 2017 | 23 | 2017 |
Performance metrics for defense framework against distributed denial of service attacks A Bhandari, AL Sangal, K Kumar International Journal on Network Security 5 (2), 38, 2014 | 23 | 2014 |
Considerations and open issues in delay tolerant network'S (DTNs) security HS Bindra, AL Sangal Wireless Sensor Network 2 (8), 645, 2010 | 23 | 2010 |
Performance comparison of RAPID, epidemic and prophet routing protocols for delay tolerant networks HS Bindra, AL Sangal International Journal of Computer Theory and Engineering 4 (2), 314, 2012 | 21 | 2012 |
Security attacks & prerequisite for wireless sensor networks S Gupta, HK Verma, AL Sangal Intl journal of engineering and advanced technology (Ijeat) 2 (5), 558-566, 2013 | 19 | 2013 |