Digital transformation has truly transformed every facet of how businesses operate and compete today. The colossal amount of data generated, processed, and stored by enterprises has grown aggressively, clearly illustrating the need for data management.
The computing ecosystems have also become more complex than ever, encompassing cloud infrastructure, data centers, and multiple edge devices like routers, integrated access devices, IoT sensors, robots, and many more. As a result, an attack surface has formed, which is more challenging to monitor & secure.
Over & above this, consumers have become prudent about data privacy. Developing trust among them has become momentous for enterprises, as there are more than 42% of consumers who have already stopped using the services of a company due to no legitimate data privacy policies in place, as per Cisco's report. It can also impact your future innovations & profitability. Having said so, the value of protecting data has never been more critical.
This blog walks you through data security and its importance, techniques to protect data, and the best practices to follow for better results.
What Is Data Security?
Data security means protecting digital data from unauthorized access, use, disclosure, alteration, and destruction. It aims at protecting data from accidental or intentional but unauthorized destruction or disclosure and modification through the use of logical controls, administrative controls, physical security, and other security measures to limit accessibility.
Amidst the pandemic in April 2020, when more people were signing up on the Zoom app, hackers breached 500,000 accounts & either sold or freely published them on the dark web.
Why Is Data Security Important?
Today, enterprises deal with enormous data in all forms and sizes. From banks handling financial and personal data to businesses storing their users' details on mobile phones or databases, data has become a key asset for big & small companies alike. If companies fail to protect the data, it can result in litigation, huge fines, and lawsuits, not to mention business decline and damage to their reputation. Additionally, it can result in financial loss, credibility loss, deterioration in customer confidence, and brand degradation.
Data Security Techniques For Protection Against Cyber Attacks
Data security techniques come in many ways to protect data from increasing cyber threats-
- Enterprise data protection
It provides a data-centric end-to-end approach to data protection for organizations. Payment security provides entire point-to-point encoding and payment tokenization to reduce PCI - DSS (Payment Card Industry Data Security Standard) scope.
2. Data encryption
Encryption is a process in which data gets stored in secret codes called ciphertext. While the original information is nothing but plain text encrypted in the ciphertext, the ciphertext can only be understood by experts.
3. Data masking
Data masking is a technique in which a data structure is created exactly like the original data to facilitate any testing or training. By doing this, the original data can be kept safe in any situation where the actual data is not needed.
4. Data erasure
When data is not in an active state, one can remove it from anywhere & everywhere in the system. For example - if a customer or user has requested to delete his/her email address from the mailing list, the company needs to delete it permanently from everywhere.
5. Data resilience
Organizations can recover corrupted, stolen, or accidentally lost data during a data breach by making backup copies of all the data.
6. Data archival
Data archiving is the process of moving data that is too old or no longer used to another storage space to keep it for the long term. The archival data can be helpful for future use.
7. Data anonymization
Data anonymization is a type of data sanitization. We can use tools to remove or encrypt personally identifiable data (PII) from the datasets to preserve the confidentiality of the data subject. However, it does not support tracing back to a specific individual as it helps maintain anonymity & yet evaluate and analyze the data.
8. Data separation
Data separation for encryption and decryption in public-key cryptography implies that many can encrypt a message that only one person can decrypt. Conversely, if a person encrypts a message, then multiple people can read it.
9. Cloud access security
Security platforms facilitate secure access to the cloud while keeping your data safe.
10. Personally identifiable info (PII)
PII is personal information used for uniquely identifying a particular person based on the information provided. (e.g., name, email id, credit card numbers, bank account, and passport number).
PII is classified into two categories -
- Linked information is more direct. It can include any personal detail, for instance-
- Full name
- Drivers' license number
- Passport number
- Email address
- Date of birth
- Home address
- Telephone number
- Internet Protocol (IP) address
- Credit card numbers
- (VIN) Vehicle identification number
- Login details (Eg. : username and password)
- Device IDs
- First name or Last name
- Country, state, city, zip code
- Job position and workplace
In April 2020, 300,000 Nintendo accounts were compromised and used for voluntary digital purchases. Information like account passwords, owner name, DOB, email address, & country of residence was exposed.
The 4 Aspects of Data Security
Data security aspects can provide you a concrete view on protecting your business against cyber threats-
- Data real-time security alert - Companies or organizations do not determine breaches through their IT department but instead from their users & third parties.
- Data auditing security - IT departments can gain the necessary visibility to potential breaches and stop unauthorized changes.
- Data risk assessment security - The method involves identifying sensitive data accessed through global clusters, old data, or inconsistent permissions.
- Data minimization security - The threat of a reputation-destroying data breach, damages within millions, or harsh regulatory fines all reinforce the thought that collecting anything beyond the minimum amount of sensitive data is extremely dangerous.
What Are The Regulations Covering Data Security?
Regulations such as GDPR, HIPAA, and SOX cover data security in detail-
- Track what kind of sensitive data they have
- Be able to produce that data on demand
- Inhibit authors about the appropriate measures taken for protecting the data
- Health Insurance Portability and Accountability Act (HIPAA)
HIPAA is a federal law that governs entities that handle Protected Health Information (PHI) concerning group health plans, health treatment, and claims payment. The Health Insurance Portability & Accountability Act of 1996 (HIPAA) was amended by the Health Information Technology for Economic & Clinical Health Act of 2009 (HITECH).
HIPAA covers several other critical aspects of health plan compliance, including but not limited to special enrollment rights, pre-existing conditions, portability of plans, administrative simplification, discrimination, and more.
Administered by Health & Human Services (HHS) and the Centers for Medicare & Medicaid Services (CMS), the HIPAA mandates are regulated by the Office of Civil Rights (OCR). Further, HITECH grants authority to state attorneys general for enforcing HIPAA violations.
- Data Classification
- Data Governance
- Continuous Monitoring
- Sarbanes-Oxley (SOX)
The Sarbanes-Oxley Act of 2002 was enacted on July 30, 2002, in response to several major corporate and accounting scandals involving multiple large companies within the US. These scandals led to a significant loss of public trust in corporate accounting and reporting practices.
- General Data Protection Regulation (GDPR)
The EU General Data Protection Regulation refers to protecting EU personal data, such as bank account numbers, dates of birth, IP addresses, social security numbers, email addresses, and phone or mobile numbers.
In January 2021, a database of 1.9 million user records owned by photo editor Pixlr was leaked on a dark web hacker forum.
What Are The Best Data Security Practices?
Listed below are some of the best practices that you should follow for data security-
- Understand data technologies and databases
- Classify and identify sensitive data
- Control access to sensitive data
- Implement change management and database auditing
- Use data encryption - while in transit and at rest (in storage)
- Create a data usage policy
- Backup your data - have proper backup policies based on data volumes and frequency
- Protect your data from insider threats - provide access to only those who need it
- Use endpoint security systems to protect your data
- Perform vulnerability assessments and cybersecurity penetration tests
In The End
Safeguarding data has never been more crucial than during the COVID-19 pandemic. It has dramatically changed the way we work, live, connect with people & learn.
Not having a robust strategy in place for information security can result in grave consequences for businesses.
Most people believe that hackers only target fortune companies as they offer the maximum payoffs. While it is true as they have more data to exploit, hackers do not leave SMEs too as they tend to have simpler access systems to penetrate, per this report, where 43% of cyber-attacks still target small businesses only.
Keep your data safe from intruders. Discover what Srijan can do for you today!