Activities per year
Abstract
Throughout the COVID-19 outbreak, malicious attacks have become more pervasive and damaging than ever. Malicious intruders have been responsible for most of the cybercrimes committed recently and are the cause for a growing number of cyber threats, including identity and IP thefts, financial crimes, and cyber-attacks to critical infrastructures. Machine learning (ML) has proven itself as a prominent field of study over the past decade due to solving highly complex and sophisticated realworld problems. This paper proposes an ML-based classification technique to detect the growing number of malicious URLs, due to the COVID-19 pandemic, which is currently considered a threat to IT users. We have used a large volume of Open Source data and preprocessed it using our developed tool to generate feature vectors and trained the ML model using an apprehensive malicious threat weight. Our ML model has been tested, with and without entropy to forecast the threatening factors of COVID-19 URLs. The empirical evidence proves our methods to be a promising mechanism to mitigate COVID-19 related threats early in the attack lifecycle.
Original language | English |
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Title of host publication | 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021 |
Place of Publication | United States |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 718-723 |
Number of pages | 6 |
ISBN (Electronic) | 9781665404242 |
ISBN (Print) | 9781665447249 (Print on demand) |
DOIs | |
Publication status | Published - 22 Mar 2021 |
Event | PerCom 2021: The 19th International Conference on Pervasive Computing and Communications 2021 - Virtual, Germany Duration: 22 Mar 2021 → 26 Mar 2021 https://drive.google.com/file/d/1nLj_2g3UsnjgIS-zUJXxi70K8VbkH3HO/view (SPT-IoT 2021: The Fifth Workshop on Security, Privacy and Trust in the Internet of Things (part of PerCom 2021) program) https://web.archive.org/web/20220307181306/http://percom.uta.edu/ (Conference website) https://ieeexplore.ieee.org/xpl/conhome/9430855/proceeding (Proceedings) |
Publication series
Name | 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021 |
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Conference
Conference | PerCom 2021 |
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Country/Territory | Germany |
Period | 22/03/21 → 26/03/21 |
Other | IEEE PerCom is the premier conference for presenting scholarly research in pervasive computing and communications. Advances in this field are leading to innovative platforms, protocols, systems, and applications for always-on, always-connected services. In 2021, PerCom will visit Kassel, situated at the geographic center of Germany and a dynamic industrial and cultural city. It is known for its UNESCO World Heritage site 'Bergpark Wilhemshöhe' and famous for a leading exhibition of contemporary art 'documenta'. In the light of the international situation of the CoVID-19 pandemic, the PerCom General Chairs and Steering Committee have decided that PerCom 2021 will be virtual (synchronous zoom meeting). |
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Dive into the research topics of 'Detecting malicious COVID-19 URLs using machine learning techniques'. Together they form a unique fingerprint.Activities
- 2 Peer reviewed publication reflection
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L&T Scholarship Reflection
Islam, R. (Speaker)
01 Jan 2022 → 31 Dec 2022Activity: Scholarly activities in Learning and Teaching reflection › Peer reviewed publication reflection
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L&T Scholarship Reflection
Islam, R. (Speaker)
12 Jan 2021 → 10 Jan 2022Activity: Scholarly activities in Learning and Teaching reflection › Peer reviewed publication reflection