A PHP Error was encountered

Severity: Warning

Message: fopen(/var/lib/php/sessions/ci_sessiont5o6nujqmfvkan5vks71lkad24bs7ik3): Failed to open stream: No space left on device

Filename: drivers/Session_files_driver.php

Line Number: 177

Backtrace:

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: session_start(): Failed to read session data: user (path: /var/lib/php/sessions)

Filename: Session/Session.php

Line Number: 137

Backtrace:

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Undefined array key "choices"

Filename: controllers/Detail.php

Line Number: 249

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 249

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 249

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 249

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: 8192

Message: strpos(): Passing null to parameter #1 ($haystack) of type string is deprecated

Filename: models/Detail_model.php

Line Number: 71

Backtrace:

File: /var/www/html/application/models/Detail_model.php
Line: 71
Function: strpos

File: /var/www/html/application/controllers/Detail.php
Line: 252
Function: insertAPISummary

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: 8192

Message: str_replace(): Passing null to parameter #3 ($subject) of type array|string is deprecated

Filename: helpers/my_audit_helper.php

Line Number: 8919

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 8919
Function: str_replace

File: /var/www/html/application/controllers/Detail.php
Line: 255
Function: formatAIDetailSummary

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Undefined array key "choices"

Filename: controllers/Detail.php

Line Number: 256

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 256

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 256

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Undefined array key "usage"

Filename: controllers/Detail.php

Line Number: 257

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 257
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 257

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 257
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Undefined array key "usage"

Filename: controllers/Detail.php

Line Number: 258

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 258
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 258

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 258
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Undefined array key "usage"

Filename: controllers/Detail.php

Line Number: 259

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 259
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 259

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 259
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Undefined array key "usage"

Filename: controllers/Detail.php

Line Number: 260

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 260
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 260

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 260
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Trying to access array offset on value of type null

Filename: controllers/Detail.php

Line Number: 260

Backtrace:

File: /var/www/html/application/controllers/Detail.php
Line: 260
Function: _error_handler

File: /var/www/html/index.php
Line: 316
Function: require_once

A Hybrid Approach for Alluring Ads Phishing Attack Detection Using Machine Learning. | LitMetric

A Hybrid Approach for Alluring Ads Phishing Attack Detection Using Machine Learning.

Sensors (Basel)

Department of Electrical and Computer Engineering, The University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, USA.

Published: September 2023

AI Article Synopsis

Article Abstract

Phishing attacks are evolving with more sophisticated techniques, posing significant threats. Considering the potential of machine-learning-based approaches, our research presents a similar modern approach for web phishing detection by applying powerful machine learning algorithms. An efficient layered classification model is proposed to detect websites based on their URL structure, text, and image features. Previously, similar studies have used machine learning techniques for URL features with a limited dataset. In our research, we have used a large dataset of 20,000 website URLs, and 22 salient features from each URL are extracted to prepare a comprehensive dataset. Along with this, another dataset containing website text is also prepared for NLP-based text evaluation. It is seen that many phishing websites contain text as images, and to handle this, the text from images is extracted to classify it as spam or legitimate. The experimental evaluation demonstrated efficient and accurate phishing detection. Our layered classification model uses support vector machine (SVM), XGBoost, random forest, multilayer perceptron, linear regression, decision tree, naïve Bayes, and SVC algorithms. The performance evaluation revealed that the XGBoost algorithm outperformed other applied models with maximum accuracy and precision of 94% in the training phase and 91% in the testing phase. Multilayer perceptron also worked well with an accuracy of 91% in the testing phase. The accuracy results for random forest and decision tree were 91% and 90%, respectively. Logistic regression and SVM algorithms were used in the text-based classification, and the accuracy was found to be 87% and 88%, respectively. With these precision values, the models classified phishing and legitimate websites very well, based on URL, text, and image features. This research contributes to early detection of sophisticated phishing attacks, enhancing internet user security.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575062PMC
http://dx.doi.org/10.3390/s23198070DOI Listing

Publication Analysis

Top Keywords

machine learning
12
phishing attacks
8
phishing detection
8
layered classification
8
classification model
8
based url
8
text image
8
image features
8
text images
8
random forest
8

Similar Publications

Background: Corona virus disease 2019 (COVID-19) reinfection, particularly short-term reinfection, poses challenges to the management of rheumatic diseases and may increase adverse clinical outcomes. This study aims to develop machine learning models to predict and identify the risk of short-term COVID-19 reinfection in patients with rheumatic diseases.

Methods: We developed four prediction models using explainable machine learning to assess the risk of short-term COVID-19 reinfection in 543 patients with rheumatic diseases.

View Article and Find Full Text PDF

3-Dimensional morphological characterization of neuroretinal microglia in Alzheimer's disease via machine learning.

Acta Neuropathol Commun

December 2024

Department of Ophthalmology and Visual Sciences, The University of British Columbia, 2550 Willow St. Room 375, Vancouver, BC, V5Z 3N9, Canada.

Alzheimer's Disease (AD) is a debilitating neurodegenerative disease that affects 47.5 million people worldwide. AD is characterised by the formation of plaques containing extracellular amyloid-β (Aβ) and neurofibrillary tangles composed of hyper-phosphorylated tau proteins (pTau).

View Article and Find Full Text PDF

Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions.

BMC Bioinformatics

December 2024

Albert Szent-Györgyi Health Centre, University of Szeged, Korányi fasor 14-15, Szeged, H-6725, Csongrád-Csanád, Hungary.

Background: Accurate prediction of copy number variations (CNVs) from targeted capture next-generation sequencing (NGS) data relies on effective normalization of read coverage profiles. The normalization process is particularly challenging due to hidden systemic biases such as GC bias, which can significantly affect the sensitivity and specificity of CNV detection. In many cases, the kit manifests provide only the genome coordinates of the targeted regions, and the exact bait design of the oligo capture baits is not available.

View Article and Find Full Text PDF

Background: Periodontitis is among the most prevalent inflammatory conditions and greatly impacts oral health. This study aimed to elucidate the role of basement membrane-related genes in the pathogenesis and diagnosis of periodontitis.

Methods: GSE10334 was used for identification of hub genes via the differential analysis, protein-protein interaction network, MCC and DMNC algorithms, and evaluation via LASSO regression and support vector machine analysis to identify basement membrane-related markers in patients with periodontitis.

View Article and Find Full Text PDF

A nomogram to distinguish noncardiac chest pain based on cardiopulmonary exercise testing in cardiology clinic.

BMC Med Inform Decis Mak

December 2024

Department of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Background: Psychological disorders, such as anxiety and depression, are considered to be one of the causes of noncardiac chest pain (NCCP). And these patients can be challenging to differentiate from coronary artery disease (CAD), leading to a considerable number of patients still undergoing angiography. We aim to develop a practical prediction model and nomogram using cardiopulmonary exercise testing (CPET), to help identify these patients.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!