Secure File Sharing

It refers to a process that includes a set of measures and methods used to keep sensitive data or files safe and securely shared. It is a security practice that both individuals and organizations implement to increase their cybersecurity and protect their data from unauthorized access.

The basic elements of secure file sharing:

Encryption: Encrypting files protects files during transmission and where they are stored. Encrypting both data and files helps protect them from unauthorized access.

Authentication and Access Controls: Access to files should only be granted to authorized individuals. Authentication and access controls ensure that files are accessible only to specific users or groups of users.

One-time Links or Permissions: Secure file sharing platforms allow users to create one-time links or permissions valid for a specific period of time to access files. This prevents the file from remaining open indefinitely.

User Education: Users should be aware that they need to be careful and follow security rules when sharing files. This prevents accidental compromise of sensitive data.

File Monitoring and Auditing: File sharing platforms provide tools to monitor/record who accessed files, when they accessed them, and what kind of actions they took. This helps detect suspicious activity.

Secure File Sharing Platforms: Using dedicated platforms or services that provide secure file sharing ensures that data is safe and regularly updated.

Data Classification: Classifying and labeling sensitive data ensures that this data is protected and shared correctly.

File Duration Limitations: Limiting the duration of file sharing permissions prevents the file from remaining open and potentially compromised.

Secure File Sharing is especially important for organizations with sensitive or confidential information, but it is also important for individuals to use such applications to protect and share their personal files. These methods are used to protect privacy and increase data security.

Data Classification And Labeling

Data classification and labeling are operations performed to process, organize and transform large data sets into usable information. These two terms are generally used in the fields of data analysis, machine learning and artificial intelligence. Here are detailed explanations of these concepts:

Data Classification:

Data classification is the process of separating data sets into specific categories or classes. This process involves determining which category a data belongs to. Classification is widely used in supervised learning methods.
Data classification is done using different algorithms. For example, algorithms such as logistic regression, decision trees, support vector machines (SVM), artificial neural networks are used in classification processes.
Application areas: Email spam detection, customer segmentation, disease diagnosis, image recognition and more.
Data Labeling:

Data labeling is the marking of data sets with specific labels or descriptions according to their content. This process is especially critical when creating training data for supervised learning. Labels help algorithms understand data and use it in the training process.

Data labeling is usually done manually, but automatic labeling or semi-automatic labeling techniques can also be used on large data sets.

Application areas: Object recognition in images, audio analysis, language processing, text classification, and more..

Sensitive Data Discovery

It refers to a process that includes a set of measures and methods used to keep sensitive data or files safe and share them securely. It is a security practice that both individuals and organizations implement to increase their cybersecurity and protect their data from unauthorized access..

Data Deletion

Data deletion is the process of permanently removing data stored on a website or digital platform. In terms of cybersecurity, this process aims to completely clean sensitive or unwanted data from the system as part of privacy and security policies.

Here are the basic elements and importance of data deletion:

Protection of Privacy: Data deletion ensures that personal and sensitive information is protected against unauthorized access. It is especially critical for websites that process users’ personal data.

Legal Compliance: Various privacy laws such as GDPR and CCPA require that user data can be deleted at any time. Data deletion is necessary to comply with these legal requirements.

Data Privacy and Prevention of Second-Hand Risks: Data deletion prevents data from being recovered when old devices or systems are disposed of. This is important to prevent data breaches and unauthorized access.

Physical and Logical Deletion Methods: Data deletion can include methods such as physical destruction of hardware, software-based deletion, and data overwriting. Which method to use depends on the type of data and security needs.

Permanent and Irreversible: Data deletion involves making sure that the deleted data cannot be recovered. This ensures that sensitive data in particular is unrecoverable.

Website Security: Data deletion for a website also includes deleting old user accounts, temporary files, or old database records. This reduces potential security vulnerabilities while improving the performance of the site.

Proper Management of Deletion Processes: Data deletion should be carefully managed and monitored by authorized personnel. This prevents accidental deletion of important data or data falling into the wrong hands.

Ultimately, data deletion is a critical process for securing a website or digital platform, protecting privacy, and ensuring legal compliance. When implemented correctly, it increases security by reducing the risk of data leaks and breaches.