Data Security Management - Data Analytics

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1. Data Security Management Lecture 8

2. Lecture 8 LO3 Explore the tools and technologies associated with data science and how it supports business processes

3. D ata security Data security  is the practice of protecting sensitive, confidential, or otherwise important information from unauthorised access and digital corruption.  Data security management  is the planning, oversight, and deployment of processes and systems that strengthen data security.

4. D ata security management The practice of ensuring that data, no matter its form, is protected while in your possession and use from unauthorized access or corruption . The blending of both digital (cyber) and physical processes to protect data.

5. Why is data security important? Because if your organisation’s data falls into the wrong hands, there can be dire consequences—employee embarrassment, customer identity theft, legal action against your company, and so on.

6. 6 Best Practices For Data Security Management 1. Use strong passwords. 2. Keep software up to date. 3. Make use of cloud services. 4. Establish internal controls to mitigate employee fraud. 5. Train employees on security protocols. 6. Back up your data.

7. Data security threats Malware  DDoS attack   Phishing scams   Hackers  Third parties   Malicious insiders   Mistakes

8. Data protection best practices To build a layered defense strategy, it’s critical to understand your cybersecurity risks and how you intend to reduce them. It’s also important to have a way to measure the business impact of your efforts, so you can ensure you are making appropriate security investments. Use compliance requirements as cybersecurity basics.    Have a clear cybersecurity policy.  Build and test a backup and recovery plan.  Have a bring-your-own-device (BYOD) policy.  Provide regular security training.  Make cybersecurity talent retention a priority. 

9. Technical best practices Classify data based on its value and sensitivity Conduct regular entitlement reviews.  Run vulnerability assessments . Enforce a strong password policy.  

10. Data security tools Firewalls  — Firewalls prevent undesirable traffic from entering the network. Depending on the organization’s firewall policy, the firewall might completely disallow some traffic or all traffic, or it might perform a verification on some or all of the traffic. Backup and recovery  — As noted earlier, you need reliable backup and recovery in case data is altered or deleted accidentally or deliberately. Antivirus software  — This provides a critical first line of defense by detecting and blocking trojans, rootkits and viruses that can steal, modify or damage your sensitive data. IT auditing  — Auditing all changes in your systems and attempts to access critical data enables you proactively spot issues, promptly investigate incidents and ensure individual accountability.

11. Advanced security tools Data discovery and classification  — Data discovery technology scans data repositories to locate all data. Data classification uses  the discovery findings and tags sensitive data  with specific labels so you can protect enterprise data in accordance with its value to the organization and reduce the risk of improper data exposure. Data encryption  — Encryption makes data useless for malicious actors. Software-based data encryption secures data before it is written to the SSD. In hardware-based encryption, a separate processor is dedicated to encryption and decryption in order to safeguard sensitive data on a portable device, such as a laptop or USB drive. Data loss prevention (DLP)  — These data security products and techniques help prevent sensitive or critical information from leaving the corporate network, thereby helping to protect it from being lost, misused or accessed by unauthorized people.

12. Dynamic data masking (DDM)  — DDM supports real-time masking of data in order to limit exposure of sensitive content to non-privileged users without changing the original data. Interest in DDM is especially high in big data projects. User and entity behaviour analytics (UEBA)  — UEBA is a complex technology for  baselining normal activity and spotting suspicious deviations  before they impact security or business continuity. UEBA can help you detect multiple types of threats, including  insider threats , hackers, malware and ransomware.