Data Security Refers To The Process Of Protecting Digital Information From Unauthorized Access, Accidental Loss, Disclosure, Manipulation, Or Corruption.
Data protection is the key to maintaining the triple principles of “confidentiality, integrity, and availability” of organizational assets.
Confidentiality refers to the private preservation of data and the lack of access by unauthorized users to the data, integrity to ensure the completeness and reliability of the data, and accessibility means the key of authorized individuals and entities to the data.
If any of these three components are compromised, companies may experience substantial financial losses. These three principles form the basis of the data security strategy. Generally, a data security strategy should include policies, technologies, controls, and procedures that protect the data that is created, collected, stored, received, and transmitted.
Why is data security important?
Data is the lifeblood of any organization because it informs decisions, provides solutions to problems, and improves the performance of business activities so that customers are better served and marketing campaigns are highly effective.
This approach will increase profitability. On the other hand, data allows security experts to identify risks and take necessary measures to counter threats quickly. That is why data is known as the most valuable asset of an organization, and it is essential to protect it in the best way.
Like the secret recipe of Coca-Cola, which is kept in a cowshed far from everyone’s reach, protecting private information is just as important. However, protecting data isn’t always as simple as putting it in a sealed safe, especially in a digital environment.
Typically, employees, stakeholders, and partners need access to data to perform their activities. For this reason, the more people have access to information, the greater the chance of information disclosure due to human errors.
A data breach occurs when people gain unauthorized access to data, a challenge that almost all small and large organizations in all industries face. In 2021, nearly 63 percent of KPMG survey participants reported experiencing a data breach. Also, it is expected that more companies will face this problem in the coming years.
Data breaches occur for various reasons, the most important of which are the following:
- Existence of bugs in software that are connected with databases
- Phishing attacks
- Distributed denial of service attacks
- Physical access to equipment
- Lack of access controls
- Back doors on systems
It is not harmful to know that the biggest and most well-known companies have also faced cyber attacks and infrastructure intrusions that led to the disclosure of their information. In most cases, data breaches have heavy consequences for companies and reduce their business activities, as companies are forced to limit the scope of their business activities during audits and security assessments. Additionally, in some countries, data breaches carry hefty fines for companies. In more critical cases, companies may go bankrupt and go out of business.
Data security is an essential component of data compliance, which defines policies and procedures to protect data. The data compliance process includes selecting applicable standards, defining metrics, and controls for accessing the repositories on which the data is stored. Large organizations that hold sensitive customer information must comply with national or international, and industry laws, policies, and regulations to be allowed to operate in a country or country regulatory compliance standards require using specific controls and technologies to meet defined data protection criteria from the bars and compliance rules that a cyber security expert must-knows including PCI DSS, HIPAA, Federal Information Security Modernization Act, Sarbanes-Oxley Act, GDPR, and CCPA.
For example, HIPAA outlines regulations for protecting medical information and provides security standards for healthcare organizations to protect patient data. In some countries, such as the United States, failure to comply with such laws carries heavy fines and penalties.
PCI DSS is a global standard developed to protect bank and credit card data.
This directive defines policies for companies and organizations active in financial affairs. It is based on which they can safely implement networks related to payments and transactions, correctly maintain cardholders’ information, and use secure and encrypted communication channels to send and receive financial data. to use
Most of the regulations and standards are subject to audits, during which organizations must prove that they adhere to the established policies of a bar. Beyond preventing violations and compliance with regulations, data security maintains customer trust in the brand. It creates sustainable interactions, which is essential in maintaining a competitive advantage over competitors.
What is data security divided into?
Before an organization can protect data, it must know what data it has. For this purpose, you need to know where the information is located and for what purposes it is used. The ideal way to recognize the data type is to classify them. Security experts label data in the data classification mechanism to make managing, storing, and securing them more accessible.
In general, data is divided into the following four main groups:
- Public Information
- Confidential Information
- Sensitive Information
- Personal Information
Sensitive data is often classified as “confidential” or “series.” this classification can be accompanied by changes depending on the type of organization and its size and smallness. For example, in the data labeling process, some businesses use only two modes to classify information: “Business Use Only” and “Secret.”
These data are as follows:
- Information that refers to the identity of people
- Medical records information of individuals
- Statistical information related to tax files
- Intellectual property information
The process of cataloging and classifying data is complex and challenging because the data may be stored in different locations, such as users’ computers, servers, storage, cloud space, distributed databases, or mobile devices, such as laptops.
In addition, data can have the following three states.
- In the transmission state: data is being transmitted through communication channels.
- At rest: Data is located in databases on storage or servers.
- In-use status: Data is in use. This process refers to writing, updating, changing, and processing, not transfer or storage.
Andrew Froehlich, network security expert and the director of West Gate Networks, said: “In the face of increasing and evolving cyber threats, IT professionals must develop a strategy based on best practices for securing data at rest, in use, and transit.
Organizations are forced to protect data because they constantly face the challenge of data theft, as stolen data can be used for impersonation, phishing attacks, etc.
Small and medium-sized organizations are attractive targets for data theft because they often lack sophisticated data protection policies and tools. However, this does not mean that larger companies are immune; They should also allocate adequate funds for purchasing security tools and employee training. Additionally, while organizations spend a lot of time identifying and fending off external threats, they should not neglect internal threats.
Verizon Institute’s 2022 Data Breach Research Report shows that nearly one in five data breaches occurred due to employee theft or negligence. Once a company considers itself obligated to protect data, the next step should be developing strategies to monitor and secure data.
Since data does not have a single form, different policies must be used to protect data at rest, in use, and in processing. Security experts recommend a defense-in-depth strategy that combines tools, techniques, and procedures to protect data.
Critical technologies available to security experts for data protection are as follows:
- Data Masking
- Access Control
- Data Loss Prevention
- Data Backup and Resiliency
Encryption is converting readable plain text into unreadable text using encryption algorithms. Encrypted data is worthless if intercepted because someone who does not have the associated encryption key cannot read or decrypt it. Encryption is divided into two main groups, symmetric and asymmetric:
Symmetric encryption uses a single secret key for encryption and decryption. Advanced Encryption Standard is the most efficient algorithm used in symmetric key encryption.
Asymmetric encryption uses two interdependent keys. A public key encrypts data, and a private key decrypts data. Among the powerful algorithms in this field, the Diffie-Hellman and Rivest-Shamir-Adleman key exchange mechanism should be mentioned.
Data obfuscation involves hiding data so that it cannot be read. In this case, a cover layer of seemingly valid data is placed over the original data, but it lacks any sensitive information. Scrambling, Substitution, Shuffling, Data Aging, Variance, Masking Out, and Nullifying are standard data masking techniques.
Data hiding is proper when specific data is needed for software testing, user training, and data analysis, but sensitive data should not be used. While both encryption and data masking technologies perform almost the same, they create unreadable data if intercepted and different from the original data.
One of the best ways to secure data is to control who has access to it. Information security will increase significantly if only authorized people can view, edit, and delete data. Access control includes the following two main processes:
- Authentication: Ensuring that users are who they claim to be.
- Process authorization: This solution allows the authenticated person to access only the required data and resources.
Authentication and authorization are the main components of an enterprise Identity and Access Management (IAM) strategy. Other fundamental IAM processes and techniques are multi-factor authentication (MFA), the principle of least privilege access, role-based access control, and privileged access management.
Another solution that interests security experts is the zero-trust access control strategy. This framework provides strict control and monitoring of resource access.
Prevention of the problem of data loss
A practical solution for data protection strategy is DLP, called Data Loss Prevention. This mechanism analyzes data to identify anomalies and violations of regulatory policies. DLP-based solutions are based on data and asset discovery mechanisms, data classification, and data analysis in transit, at rest, and in use.
The above mechanism identifies problems and provides a report to security experts. DLP tools can be integrated with technologies such as SIEM systems to automate the alerting and response process.
Data backup involves copying files and databases to a secondary location. In such situations, if the original data fails, is corrupted, or is stolen, a backup copy of the data ensures that it is possible to restore the data to normal conditions. Data backup is essential when it comes to disaster recovery plans.
The self-healing feature is another strategy that is of interest. The ability of an organization to adapt and recover after a cyber incident depends on the self-healing and resilience of the organization.
Data security, data privacy, and data protection
- Data security, privacy, and protection are seemingly similar concepts but are technically different.
- Data security has a broad scope and aims to protect digital information from unauthorized access, intentional loss of information, and prevention of data corruption.
- Data privacy primarily focuses on confidentiality and the three security principles mentioned earlier.
- Data protection focuses on the integrity and availability of information.
For example, imagine threat actors obtain a confidential file, but encryption prevents the data from being read. The information itself remains inaccessible, and data privacy remains intact.
However, attackers can still corrupt or destroy the unreadable file, which is a security flaw.
- Data privacy aims to protect the identity of individuals and ensure that unique methods are used to collect, store and use sensitive data that comply with legal regulations. Policies and measures preserve privacy and prevent unauthorized persons from accessing data, regardless of their motivation.
- Data protection is an integral part of a security strategy that can protect data as a last resort when other security mechanisms are unsuccessful. Data protection ensures that if digital data is lost, corrupted, or stolen, business operations will not be disrupted. A backup copy is always available to recover the data.