Application security focuses on protecting software applications from security threats, addressing vulnerabilities like SQL injection and XSS, which can lead to data breaches and reputational harm. Data security involves safeguarding digital data from unauthorized access and corruption, while data privacy emphasizes the protection of personal information through methods like data minimization and encryption. Effective strategies include strict access controls, regular backups, and employee training to enhance overall data protection.

2. APPLICATION, DATA SECURITY AND
PRIVACY
Application security refers to measures and practices
designed to protect software applications from security
threats and vulnerabilities.

3. WHY IS IT IMPORTANT?
Applications often handle sensitive data, so an insecure app
can lead to severe data breaches, financial losses, and
reputational damage.
Examples of application vulnerabilities include SQL injection,
cross-site scripting (XSS), and insecure API calls.

4. APPLICATIO
N
DATA
SECURITY
PRIVACY

5. WHAT IS DATA SECURITY VS PRIVACY
• Data Security refers to the practice of protecting digital
data from unauthorized access, corruption, or theft
throughout its lifecycle.
• Data Privacy refers to the protection of personal and
sensitive information from unauthorized access, use, or

6. POSSIBLE VULNERABILITIES - OWASP
• SQL Injection - Injection: Flaws like SQL, NoSQL, or OS command injections
enabling attackers to manipulate queries.
• Inadequate restrictions on authenticated users, allowing unauthorized actions.
• Cryptographic Failures: Weak or improper cryptography leading to data exposure.
• Insecure Design: Lack of security controls in the design phase, leading to
exploitable weaknesses.

7. POSSIBLE VULNERABILITIES - OWASP
• Identification and Authentication Failures: Weak authentication mechanisms allowing
unauthorized access.
• Software and Data Integrity Failures: Inadequate integrity checks leading to unauthorized data
modifications.
• Security Logging and Monitoring Failures: Insufficient logging and monitoring hindering threat
detection.
• Server-Side Request Forgery (SSRF): Attackers tricking servers into making unintended requests.

8. DATA PRIVACY METHODS
• Data Minimization: Collect only the data necessary for a specific purpose to reduce exposure.
• User Consent Management: Obtain and manage user consent for data collection and processing
activities.
• Data Anonymization: Remove personally identifiable information from data sets to prevent
identification of individuals.
• Data Masking: Obscure specific data within a database to protect it from unauthorized access, ensuring
that sensitive information is not exposed to unauthorized personnel.
• Data Tokenization: Replace sensitive data elements with unique identifiers (tokens) that have no
exploitable value, reducing the risk of data breaches.

9. DATA SECURITY METHODS
• Data Encryption: Convert data into a coded format that can only be deciphered by authorized users possessing
the decryption key. This method secures data both at rest and during transmission.
• Access Control: Implement strict policies and mechanisms to ensure that only authorized individuals can access
or manipulate sensitive data. This includes role-based access controls and multi-factor authentication.
• Regular Backups: Maintain up-to-date copies of critical data to ensure recovery in case of data loss or corruption.
• Data Integrity Checks: Implement mechanisms to ensure that data remains accurate and unaltered during
storage and transmission.
• Employee Training: Educate staff on data security best practices and the importance of safeguarding sensitive
information.