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Gartner defines data security governance as a subset of data governance that deals specifically with protecting data, whether structured or unstructured, through defined policies and practices.

The unprecedented data growth and other factors that include scalability, flexibility, cost reduction, efficiency, and agility have pushed businesses to adopt cloud architecture. However, the combination varies; businesses move their applications and data to the cloud, cutting the hardware cost rather than running on-premise. Likewise, organizations may move only their data storage to the cloud or maintain their backup on the cloud.

An invaluable asset the organizations have is data. Data is vulnerable to theft, breach, or modifications. So the cloud service providers are entitled to ensure security measures that are well configured by implementing policies and laws.

Whom to trust?

According to Gartner, “The challenge exists not in the security of the cloud itself, but in the policies and technologies for security and control of the technology. In nearly all cases, the user, not the cloud provider, fails to manage the controls used to protect an organization’s data.”

The cloud provider should employ AI technology, policies, and practices to secure data. Businesses should be cautious while choosing cloud service providers. Security standards cannot be one-size-fits-all as they vary by industry, company size, actual business requirements, and local data privacy regulations. Accept those that follow policy and procedures per international security standards e.g.ISO 27001 and the National institute of standards and technology (NIST), and for local privacy regulations, consider frameworks such as Europe’s general data protection regulation, HIPAA, SOX, and Basel l/II. These factors will decide whether your cloud storage causes extra concerns or becomes a valuable ally for your business and its partners. You must plan and consider what cloud service you will use and assess their security in advance.

Practices that organizations should follow:

Run on internet protocols and virtualization techniques; cloud infrastructure is vulnerable to attacks. An assault can be made through ARP, IP spoofing, Denial of service DoS, and others. In cyber security, the significant challenge where an assault is unknown is called a zero-day attack. Conventional ways of addressing attacks are no more sufficient. Dealing with large data flow and, simultaneously, detection and prevention of attacks has become the priority. The ML-based approach may prove helpful as it can learn from patterns and easily capture any pattern change. Therefore, ML-based cloud platforms can help provide fully managed, end-to-end data protection in a security-rich environment.

-Authentication and authorization:-Authentication identify the user or program, and authorization is permission to access different resources. To monitor and control the same, the measures include secure password verification, personal identification number (PIN), two-factor authentication, and proper identity & access management(IAM). The IAM industry has introduced risk-based authentication as a response to security concerns. While traditional multi-factor authentication (MFA) relies on factors like passwords, devices, and biometrics, risk-based authentication goes further by considering additional factors to verify user identity. Real-time assessment of authentication data requires advanced and complex processing, which is where artificial intelligence plays a role. By analyzing and assigning weightage to various factors in a login attempt, AI calculates a risk score for the scenario.

-Data privacy: Clients and regulations hold a cloud service provider responsible for handling the data. After all, data privacy sets the basis for cybersecurity. AI algorithms have the potential to enhance data privacy by facilitating encryption and anonymization in various transactions, extending beyond online shopping. Additionally, AI can assist in implementing measures like data expiration, preventing companies from retaining personal information indefinitely. While AI contributes to data privacy, it is not sufficient on its own. Robust services and comprehensive regulations are equally crucial. Nonetheless, AI is currently demonstrating its value in data privacy and setting higher standards for data protection, which organizations should recognize and prioritize.

-Data integrity: the primary goal of cloud data security is to protect your files from illegal access; data integrity in the cloud guarantees that your data does not become damaged or changed. No matter how excellent your services are, if you have no way of knowing whether data has been deleted or altered or if you are unaware of how and by whom changes were made–your security, authenticity, and credibility are jeopardized.

Machine learning (ML) plays a crucial role in data management by validating data, eliminating redundancy, and conducting in-depth analysis. AI-powered management solutions utilize ML algorithms to identify data duplication and inconsistencies. Reliable anomaly detection tools based on ML are capable of efficiently and effectively detecting inaccuracies within datasets. By leveraging AI and ML, organizations can ensure the accuracy, consistency, and reliability of their data at every stage of its lifecycle.

Data security: Data security is a critical concern for organizations in today’s digital age. Cyberattacks and data breaches can result in significant financial losses, damage to reputation, and legal liabilities. AI and machine learning techniques can be used in security to detect anomalies and patterns that may indicate malicious activity. However, it’s important to consider that unusual patterns alone do not necessarily indicate malicious intent. Factors such as atypical user agents in HTTP requests, unexplained traffic from a single IP or IP range, and unusual sequences of accesses to endpoints can help make informed decisions. These techniques enable the analysis of multiple input variables to arrive at conclusions in the realm of cybersecurity.

How does cloud security work?

Cloud storage providers often use the TLS protocol throughout transmission to safeguard your data from eavesdropping. It employs a cipher, authentication, and critical exchange to secure a connection.

When the data exits this safe route, it is decrypted. As a result, when your data arrives at the provider’s server, a hacker or rogue employee can access it. The provider may then re-encrypt your data before storing it on its discs, known as at-rest encryption. However, because the service provider has encryption keys to your data, they or anybody who obtains access to the keys can decode your information. Identity attributes guarantee a legitimate certificate is used, avoiding fraudulent breaches.

There are various methods for obtaining the code. You can get it through email, phone calls, or SMS, as well as through a local mobile app or a physical token. This approach complicates the hacking procedure since they require an additional verification number to access your account.

Two emerging encryption protocols, secure multiparty computation (SMPC) and homomorphic encryption (HE), offer promising advancements in privacy protection for businesses

A ransomware assault may be devastating to your company. It is a form of malware assault designed by hackers to look for and encrypt your sensitive data. Hackers will demand a ransom for the key to unlocking your files. As a result, it is preferable to collaborate with cloud storage companies that provide ransomware protection services or perform well against such assaults.


Keep end-to-end encryption in mind if you intend to secure your data (E2EE). You don’t have to worry about your data with E2EE, even if your cloud provider suffers a security breach. Each file you share will remain encrypted. 

Leveraging AI/ML technology can help to look across the stream of security events and prioritize the ones that matter most. Specialists manage cloud services at the top of their game since they must adhere to stringent SLAs (service level agreements).

As a result, your primary worry should be if your cloud vendor is trustworthy and transparent about their security. Understanding how cloud providers differ in their security measures is critical before signing any contract.

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