Work place: Isparta University of Applied Sciences, Uluborlu Vocational School, Department of Computer Technologies, TÜRKİYE
E-mail: osmanceylan@isparta.edu.tr
Website: https://orcid.org/0000-0002-6060-0134
Research Interests:
Biography
Osman Ceylan is currently employed as a Lecturer in the Department of Computer Technologies at Isparta University of Applied Sciences. He completed his master in computer engineering. His main research areas are AI Modelling and cyber security.
By Ahmet Ali Suzen Osman Ceylan
DOI: https://doi.org/10.5815/ijeme.2025.02.01, Pub. Date: 8 Apr. 2025
Data leakage is the deliberate or accidental transfer of data of institutions or individuals to a different source. Especially, with the increasing use of IT assets after the pandemic, data leaks are more common. Firewalls, anti-virus software, Intrusion Prevention Systems (IPS), or Intrusion Detection Systems (IDS) products are preferred within the network to ensure the security of data sources. However, this type of security software works server-based and often protects the network from outside attacks. It is seen that the main source of data leaks experienced recently is internal vulnerabilities. Data Loss Prevention (DLP), which is the right choice for preventing data leaks, is a system developed to identify, monitor, and protect data in motion or stored in a database. DLPs are preferred to prevent unauthorized distribution of data at the source. DLP software is recommended for technical measures against data security, especially the Personal Data Protection Law (KVKK) in Turkey and General Data Protection Regulation (GDPR) in the European Union.
Test virtual machines were set up for implementation in real-world scenarios and using personal and corporate data, the behavior and durability of DLP software in cases of unauthorized data upload to USB, CD/DVD, cloud resources, office software, e-mail or ftp server were evaluated. It was observed that potential leaks and risks occur in data discovery, data masking, data hiding and data encryption according to the data density in data leakage prevention.
Subscribe to receive issue release notifications and newsletters from MECS Press journals