[PDF][PDF] Improving of fingerprint segmentation images based on K-means and DBSCAN clustering
E Mehdi Cherrat, R Alaoui, H Bouzahir - International Journal of …, 2019 - academia.edu
Nowadays, the fingerprint identification system is the most exploited sector of biometric.
Fingerprint image segmentation is considered one of its first processing stage. Thus, this …
Fingerprint image segmentation is considered one of its first processing stage. Thus, this …
[PDF][PDF] Real-time phishing detection using deep learning methods by extensions
Phishing is an attack method that relies on a user's insufficient vigilance and understanding
of the internet. For example, an attacker creates an online transaction website and tricks …
of the internet. For example, an attacker creates an online transaction website and tricks …
[PDF][PDF] Federated learning for scam classification in small Indonesian language dataset: an initial study
M Chen, DK Halim - Indonesian Journal of Electrical Engineering and …, 2023 - academia.edu
Most digital phishing or scam trick users into fraudulent links and is more effective against
users with low technology literacy, like in Indonesia. Machine learning is widely used for …
users with low technology literacy, like in Indonesia. Machine learning is widely used for …
[PDF][PDF] Vote algorithm based probabilistic model for phishing website detection
MSI Prottasha, MZ Rahman, ABMK Hossain… - Indonesian Journal of …, 2022 - academia.edu
Internet scams have been a major concern for everyone over the past decade. With the
advancement of technology, attackers have formulated different kinds of contemporary …
advancement of technology, attackers have formulated different kinds of contemporary …
Phishing Email Detection: Survey
RS MohamedAli, RA Abduhameed - International Conference on …, 2024 - Springer
Phishing emails pose a significant contemporary challenge on the Internet, resulting in
financial losses for organizations and causing frustration for users. Phishing is a deceptive …
financial losses for organizations and causing frustration for users. Phishing is a deceptive …
Impact Analysis of Filter and Wrapper-Based Feature Selection Techniques for Webpages Phishing Attacks Identification
Phishing, which involves fraudulently gaining access to sensitive assets of unsuspecting
individuals through deceptive and malicious emails, is a major global threat to internet …
individuals through deceptive and malicious emails, is a major global threat to internet …
[图书][B] One Click from Disaster: An Exploratory Study of the Impact of Employees' Perception of Email Protection on Phishing Susceptibility
D Castillo - 2021 - search.proquest.com
Phishing scam emails have become severe threats to organizations because they are the
preferred method by hackers to deploy malicious software. Many solutions have been …
preferred method by hackers to deploy malicious software. Many solutions have been …
Phishing Detection Using Hybrid Machine learning Techniques
RGM Helali - Zhongguo Kuangye Daxue Xuebao, 2024 - zkdx.ch
Cyber security has become a crucial component of the new digital age with more than 820
million users of internet in year 2023 and social media users are expected to reach 82.3 …
million users of internet in year 2023 and social media users are expected to reach 82.3 …
Machine Learning Methods for Phishing Attacks: Survey
M Medelbekov, M Nurtas - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
The basis of cybersecurity is an understanding of the mechanisms of social engineering.
This increases the effectiveness in combating this type of manipulation. One of them is …
This increases the effectiveness in combating this type of manipulation. One of them is …
K-NN supervised learning algorithm in the predictive analysis of the quality of the university administrative service in the virtual environment
CR Palacios Huaraca, OF Chamorro Atalaya… - 2022 - repositorio.utp.edu.pe
The objective of this study is to analyze and discuss the metrics of the predictive model using
the K-nearest neighbor (K-NN) learning algorithm, which will be applied to the data on the …
the K-nearest neighbor (K-NN) learning algorithm, which will be applied to the data on the …