Personal Data Disposal Policy

Technical and Administrative Measures Taken for the Legal Disposal of Personal Data

Secure Deletion from Software: While deleting data processed by fully or partially automated means and stored in digital media; Methods for deleting the data from the relevant software are used so that it cannot be accessed and reused in any way for the relevant users.
Deletion of Related Data in the Cloud System by Giving the Delete Command: Removing the access rights of the relevant user on the file or the directory where the file is located on the central server; Deleting the relevant rows in databases with database commands or deleting the data in portable media, ie flash media, by using appropriate software can be counted within this scope.
However, if the deletion of personal data will result in the inaccessibility of other data within the system and the inability to use this data, the personal data will be deemed deleted if the personal data is archived in a way that it cannot be associated with the data subject, provided that the following conditions are met.
Being closed to the access of any other institution, organization or person,
Taking all necessary technical and administrative measures to ensure that personal data can only be accessed by authorized persons.
Secure Deletion by Expert: In some cases, Ulusal Elektronik Teknolojileri San. ve Tic. Inc. You can agree with a specialist. In this case, the personal data will be securely deleted by the person who is an expert in this field, in a way that will be inaccessible and unusable for the Relevant Users in any way.
Blackening of Personal Data in Paper Media: It is a method of physically cutting and removing the relevant personal data from the document in order to prevent the unintended use of personal data or to delete the data requested to be deleted, or to make them invisible by using fixed ink, which cannot be recovered and read with technological solutions.
De-magnetization: It is the method of corrupting the data on it in an unreadable way by passing the magnetic media through special devices where it will be exposed to high magnetic fields.
Physical Destruction: Personal data can also be processed by non-automatic means, provided that they are part of any data recording system. When such data is destroyed, a system of physical destruction of personal data is applied so that it cannot be used later. The destruction of data in paper and microfiche media is also carried out in this way, since it is not possible to destroy them in any other way.
Overwriting: The overwriting method is to write random data consisting of 0s and 1s at least seven times over magnetic media and rewritable optical media by means of special software.
Anonymization Methods That Do Not Provide Value Irregularity: Without any change or addition/removal of the personal data stored with anonymization methods that do not provide value irregularity; is the generalization, replacement of any personal data group or the removal of a certain data or sub-data group from the group.
Variable Extraction: It is the anonymization of the existing data set by removing the “high-degree descriptive” variables from the variables in the data set created after the data collected by the method of extracting the descriptive data.
Removing Records: The data line that contains singularity among the data is removed from the records, and the stored data is anonymized.
Regional Concealment: Anonymization is provided by concealing the relevant data, if it has a determinative nature, since a single data creates a very rarely visible combination.
Lower and Upper Bound Coding: It is the anonymization of the values ​​in a data group containing predefined categories with the lower and upper bound coding method by combining them by determining a certain criterion.
Generalization: With the data aggregation method, many data are aggregated and personal data is rendered incapable of being associated with any person.
Global Coding: With the data derivation method, a more general content is created than the content of personal data and it is ensured that personal data cannot be associated with any person.
Anonymization Methods That Provide Value Irregularity: Contrary to the anonymization methods that provide value irregularity, corruption is created by changing some data in personal data groups, unlike those that do not provide value irregularity.
Adding Noise: The method of adding noise to the data is anonymized by adding some positive or negative deviations at the determined rate to the existing data, especially in a data set where numerical data are predominant.
Micro-Aggregation: In the micro-joining method, all data is first separated into groups by arranging them in a meaningful order, and the value obtained by taking the average of the groups is written in place of the relevant data in the current group, thereby providing anonymization.
Data Exchange: In the data exchange method, the values of a variable are exchanged between the pairs selected from the stored data.
During the realization of the above-mentioned situations, full compliance with the provisions of the PDPL, the Regulation and other relevant legislation is ensured in order to ensure data security and all necessary administrative and technical measures are taken.