Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Mega events attract mega crowds, and many data exchange transactions are involved among organizers, stakeholders, and individuals, which increase the risk of covert eavesdropping. Data hiding is essential for safeguarding the security, confidentiality, and integrity of information during mega events. It plays a vital role in reducing cyber risks and ensuring the seamless execution of these extensive gatherings. In this paper, a steganographic approach suitable for mega events communication is proposed. The proposed method utilizes the characteristics of Arabic letters and invisible Unicode characters to hide secret data, where each Arabic letter can hide two secret bits. The secret messages hidden using the proposed technique can be exchanged emails, text messages, and social media, as these are the main communication channels in mega events. The proposed technique demonstrated notable performance with a high-capacity ratio averaging 178% and a perfect imperceptibility ratio of 100%, outperforming most of the previous work. In addition, it proves a performance of security comparable to previous approaches, with an average ratio of 72%. Furthermore, it is better in robustness than all related work, with a robustness against 70% of the possible attacks.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11419608 | PMC |
http://dx.doi.org/10.7717/peerj-cs.2236 | DOI Listing |
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