The COVID‐19 scamdemic: A survey of phishing attacks and their countermeasures during COVID‐19

AF Al‐Qahtani, S Cresci - IET Information Security, 2022 - Wiley Online Library
The COVID‐19 pandemic coincided with an equally‐threatening scamdemic: a global
epidemic of scams and frauds. The unprecedented cybersecurity concerns emerged during …

Malicious URL detection using machine learning: A survey

D Sahoo, C Liu, SCH Hoi - arXiv preprint arXiv:1701.07179, 2017 - arxiv.org
Malicious URL, aka malicious website, is a common and serious threat to cybersecurity.
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …

Cyber threat intelligence-based malicious URL detection model using ensemble learning

M Alsaedi, FA Ghaleb, F Saeed, J Ahmad, M Alasli - Sensors, 2022 - mdpi.com
Web applications have become ubiquitous for many business sectors due to their platform
independence and low operation cost. Billions of users are visiting these applications to …

Significance of machine learning for detection of malicious websites on an unbalanced dataset

I Ul Hassan, RH Ali, Z Ul Abideen, TA Khan, R Kouatly - Digital, 2022 - mdpi.com
It is hard to trust any data entry on online websites as some websites may be malicious, and
gather data for illegal or unintended use. For example, bank login and credit card …

CatchPhish: detection of phishing websites by inspecting URLs

RS Rao, T Vaishnavi, AR Pais - Journal of Ambient Intelligence and …, 2020 - Springer
There exists many anti-phishing techniques which use source code-based features and third
party services to detect the phishing sites. These techniques have some limitations and one …

[HTML][HTML] The development of phishing during the COVID-19 pandemic: An analysis of over 1100 targeted domains

R Hoheisel, G van Capelleveen, DK Sarmah… - Computers & …, 2023 - Elsevier
To design preventive policy measures for email phishing, it is helpful to be aware of the
phishing schemes and trends that are currently applied. How phishing schemes and …

Detection of malicious social bots using learning automata with url features in twitter network

RR Rout, G Lingam… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Malicious social bots generate fake tweets and automate their social relationships either by
pretending like a follower or by creating multiple fake accounts with malicious activities …

An effective cost-sensitive XGBoost method for malicious URLs detection in imbalanced dataset

S He, B Li, H Peng, J Xin, E Zhang - IEEE Access, 2021 - ieeexplore.ieee.org
Imbalanced class has been a common problem encountered in the modeling process, and
has attracted more and more attention from scholars. Biased classifiers, which limit the …

A review on privacy requirements and application layer security in internet of things (IoT)

KS Sudha, N Jeyanthi - Cybernetics and Information Technologies, 2021 - sciendo.com
Internet of Things (IoT) is the predominant emerging technology that targets on facilitating
interconnection of internet-enabled resources. IoT applications concentrate on automating …

[PDF][PDF] Understanding and analyzing appraisal systems in the underground marketplaces

Z Li, X Liao - NDSS, 2024 - xiaojingliao.com
An appraisal system is a feedback mechanism that has gained popularity in underground
marketplaces. This system allows appraisers, who receive free samples from vendors, to …