Results 21 to 30 of about 1,434 (227)
Aparecium: understanding and detecting scam behaviors on Ethereum via biased random walk
Cybersecurity, 2023 Ethereum’s high attention, rich business, certain anonymity, and untraceability have attracted a group of attackers. Cybercrime on it has become increasingly rampant, among which scam behavior is convenient, cryptic, antagonistic and resulting in large ...
Chuyi Yan +7 more
doaj +1 more source
M-ISDS: A Mobilized Intrusion and Spam Detection System [PDF]
SHS Web of Conferences, 2022 As the world strides into the digital world, cybersecurity has become an indispensable part of connected devices. Although we have developed cybersecurity measures that can effectively defend against malicious software, we don’t have an accurate solution
Li Yuyang
doaj +1 more source
Image-Based Scam Detection Method Using an Attention Capsule Network
IEEE Access, 2021 In recent years, the rapid development of blockchain technology has attracted much attention from people around the world. Scammers take advantage of the pseudo-anonymity of blockchain to implement financial fraud.
Lingyu Bian +4 more
doaj +1 more source
Trigonometric words ranking model for spam message classification
IET Networks, EarlyView., 2022 Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi +7 more
wiley +1 more source
Computers in Human Behavior Reports, 2023 Background: Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion.
Michelle Walther +3 more
doaj +1 more source
An Empirical Analysis of SMS Scam Detection Systems
CoRR, 2022 The short message service (SMS) was introduced a generation ago to the mobile phone users. They make up the world's oldest large-scale network, with billions of users and therefore attracts a lot of fraud. Due to the convergence of mobile network with internet, SMS based scams can potentially compromise the security of internet services as well.
Muhammad Salman +2 more
openaire +2 more sources
Classification of Language Interactions [PDF]
, 2013 Context: the presence of several languages interacting each other within the same project is an almost universal feature in software development. Earlier work shows that this interaction might be source of problems.
Federico Tomassetti +5 more
core +1 more source
Management and reduction of fraud by analysis of the insurer’s internal and external vulnerabilities and contributions [PDF]
Revista de Studii Financiare, 2021 Fraud is a dynamic phenomenon: when the industry discovers a „scam” – a specific pattern of fraud – and sets up barriers to prevent it from recurring, another scam takes place – a new pattern is developed by fraudsters.
Mihai Ovidiu Vădean
doaj
Credit Card Fraud Detection Methods: A Review [PDF]
E3S Web of Conferences, 2023 In today’s context, the term “fraud” has become closely intertwined with credit card-related deceit. Recent years have witnessed a notable surge in both credit card utilization and fraudulent activities.
Pundkar Sumedh N., Zubei Mohd
doaj +1 more source
How Experts Detect Phishing Scam Emails [PDF]
Proceedings of the ACM on Human-Computer Interaction, 2020 Phishing scam emails are emails that pretend to be something they are not in order to get the recipient of the email to undertake some action they normally would not. While technical protections against phishing reduce the number of phishing emails received, they are not perfect and phishing remains one of the largest sources of security risk in ...
openaire +1 more source