Cloud data security protects any type of sensitive data hosted on the cloud. It prevents its leakage, misuse, exfiltration, and unauthorized access. Cloud data security also ensures the privacy of data across networks inside and outside organizations, including apps, containers, servers, workloads, and other cloud environments.
In this guide, we will talk about how to keep your assets safe from various data security threats. You will learn the difference between cloud security and data security, and also about their benefits, limitations, and common cloud data security challenges.
What is Cloud Data Security?
Cloud data security involves tools, workflows, and practices used to secure your sensitive data and prevent its unauthorized access. Cloud data security doesn’t just involve the data you have or transmit. It includes data that is not bound by the constraints of your hardware used in the infrastructure. This includes data at rest, in transit, and data in use. Your sensitive data may include public and private info such as government data, IP addresses, names, birthdates, intellectual property information, biometrics, and so much more.
Companies are constantly collecting and sharing data across customers and clients. They store this data on the cloud which means that strong cloud data security is a top priority. As businesses expand their cloud footprints, the demand for strong cloud data security will naturally go up.
Need for Cloud Data Security
Organizations constantly shift their data from local to public or private cloud storage. As they grow their business, their data volumes and client bases grow as well. An organization’s data is accessed from multiple systems, and all this data is stored in cloud environments.
Unauthorized users can gain unwanted access and access networks. Once they tap in, they can thwart business continuity and prevent other users on the network from accessing or using that sensitive information. Exposure of sensitive data or its leakage can tarnish the reputation of the business. It can lead to loss of customer trust and open up more opportunities for data breaches or even large-scale cyber attacks.
Traditional on-premises data centers are no longer enough and security teams need to up their game. They need to rethink their cloud data security strategy because adversaries are getting smarter by the day. Also, companies need to comply with the latest data protection and privacy laws and regulations. Poor cloud data security can lead to costly lawsuits, heavy fines, and other legal troubles. A good cloud data security solution will also incorporate incident response in times of trouble and provide advanced data protection.
How secure is your data in the cloud? That’s the big question, because AI tools are being used to attack enterprises. Public sectors and startups are the most targeted victims of cloud data security breaches around the world. In 2024 alone, 73% of organizations were hit by phishing attacks and 56% couldn’t secure their cloud data on time across multi-cloud environments. There are many unique challenges being introduced by AI-powered tools that are used by adversaries to probe cloud-native systems.
Types of Threats to Cloud Data
Here are the different types of threats your cloud data can face:
- Distributed infrastructures are prime targets for various sophisticated threats that exploit different vulnerabilities. Misconfigurations are still the most common threat, where improper settings in storage buckets, access controls, or network configurations may inadvertently expose sensitive data.
- Insider threats, whether malicious or accidental, are also scary. These insiders can access and exfiltrate critical information, usually bypassing traditional perimeter defenses.
- Ransomware evolves and targets cloud-based backups and services, which encrypt data. It will demand high payments for decryption keys. Unlike traditional ransomware, cloud-based variants can quickly disrupt business continuity globally.
- API vulnerabilities are another critical threat vector. Because APIs enable interactions between cloud services, any weakness can be used for unauthorized access or manipulation of data. As APIs increasingly become the primary method to interact with systems, one exploited endpoint can compromise an entire system.
- Supply chain attacks are complicated threats. Adversaries infiltrate trusted software dependencies to introduce malicious code. They not only compromise cloud security data but also undermine the integrity of the software supply chain itself.
Core Principles of Cloud Data Security
Here are the core principles of cloud data security in 2025:
- Zero Trust is Not Optional: Trust nobody, verify everyone. Doesn’t matter who it is. Never give implicit access to any user account, network, or cloud workload.
- Shift Left Security: Add and enforce shift-left security to your cloud-native security strategy; right from Infrastructure as Code (IaC) to CI/CD and ML pipelines. It should be treated as being a part of your attack surface.
- Automate breach prevention and containment: Your cloud data security solutions should minimize blast radius and have the ability to automatically contain any data security anomalies. They should spot outliers as well.
- Observe All Sources: Cloud telemetry data, metrics, logs, model inputs and outputs, forensics, and any raw materials coming from different sources as well. Both structured and unstructured sensitive information.
- Improve Data Models’ Protection: Configure data models so that they ensure and require to maintain confidentiality, integrity, and availability without causing security compromises.
How Does Cloud Data Security Work?
Cloud data security works in several layers. You start by encrypting your data so only authorized parties can understand or access the information. They won’t be able to leak or share it.
Next is identity and access management, where you track who has the necessary access privileges. Identity and access management will reduce the scope for threats and restrict privileges. It can mitigate account takeovers and insider threats.
Firewalls are the next layer of protection. They are hosted on-premise. Firewalls can defend your network perimeters, and many organizations are using cloud firewalls these days. They can block DDoS attacks, malicious activities, and vulnerability exploits.
Additional security measures will include properly configuring your cloud server security settings. This is where you fix misconfigurations and tell your team to collaborate closely with the cloud vendor. You also set up consistent security policies across all your public and private clouds and data centers.
Data backup planning is another critical element. You need to prevent your data from getting lost or tampered with. Having failover plans is a crucial step in this so that you are prepared for cases where business processes may be interrupted or if a cloud service goes down, you can quickly recover again.
Also, your employees need to know the best cyber hygiene practices. They should know how to write strong passwords and not reuse old ones. They should also know where to store their sensitive data and how to operate on the cloud so that they are not exposed to various security risks. Whenever they run into any threats, they should know how to deal with them and not engage in the wrong ways.
CNAPP Market Guide
Get key insights on the state of the CNAPP market in this Gartner Market Guide for Cloud-Native Application Protection Platforms.
Read GuideCloud Data Security Benefits
Here are the benefits of good cloud data security:
- Greater Visibility – You know where your data lives, who uses your assets, and the owners of your data assets. Good cloud data security gives deep visibility about the kind of data being accessed and who accesses it.
- Smooth backups and recovery – Say goodbye to the days of manual data backup and recovery. You can now automate the entire process, set up cloud-based disaster recovery and recover and restore your lost or deleted data within minutes. It frees up a lot of time for your team and also helps standardize data backups.
- Cloud data compliance -Cloud data compliance can help you meet your compliance obligations. It takes care of data integrity and makes sure you store your data safely. You can easily classify, and de-classify data to reduce the risk of any violations.
- Data encryption – Organizations can protect their sensitive data at rest and in transit or wherever it goes. They can tackle cloud data transfer, storage, and manage data sharing by incorporating multiple layers of advanced encryption.
- Lesser costs – Cloud data security will lower the total cost of ownership (TCO) and reduce administrative and management burdens. It streamlines integration, continuous alerting, automation, and other aspects. Another benefit is that you save money on incident response since these solutions can automatically scan for suspicious activity to identify and respond to them.
Key Challenges in Cloud Data Security
There are many challenges associated with cloud data security.
- Companies with complex multi-cloud and hybrid environments must define their cloud data security needs. Hybrid environments are challenging to maintain and need a holistic approach to cloud data security.
- Many cloud service providers do not protect your data from external threats. And some of them cover only some of your cloud infrastructure. There is also the human factor that you need to consider. When your data gets compromised, your workers could be held responsible.
- There is also a need for more visibility when identifying your cloud assets. You may need help to track all your employees’ activities across your cloud estates.
- Expanding attack surfaces and different attack angles for your systems and data complicates cloud data security. When you have a lot of personal devices, remote employees, and unauthorized third-party cloud apps, services, and public networks in the loop, the risk of your cloud data going up more, both at rest and rest.
- Cost is another factor. If your organization has a lot of resources or data to manage, your investments in cloud data security solutions should increase.
- Cloud data security attacks can cause service outages and disruptions due to hardware failures, network issues, and cyber attacks. Your organization can face business disruptions, loss of productivity, and financial losses. Compliance violations, penalties, and the possibility of mishandling personally identifiable information are also risks.
Who is responsible for securing data in the cloud?
Cloud data security is a shared responsibility, so both the customer and the vendor are responsible for securing data in the cloud. The cloud provider handles the security of the cloud infrastructure while the customers manage data uploads, sharing, access controls, and encryption. Customers are responsible for managing their data settings and configurations for all of their data assets. User access management and ensuring data compliance are also other parts of their responsibilities.
Best Practices for Cloud Data Security
Here are the eight cloud data security best practices that every organization should follow:
-
Adopt a Zero-Trust Model
Embrace a zero-trust architecture. Assume no user or device is automatically trustworthy, whether inside or outside your network. Every access request should undergo rigorous verification. Ensure that only authenticated and authorized entities can interact with your data. Building a Zero Trust Network Architecture with multi-layered defenses is one of enterprises’ top cloud data security best practices.
-
Implement Strong Identity and Access Management (IAM)
Strengthen your IAM by ensuring only the right individuals can access the right resources. Incorporate multi-factor authentication (MFA) to add an extra layer of security. Use role-based access controls (RBAC) to limit permissions based on job responsibilities. You should conduct regular audits to review and adjust access levels as needed.
-
Data Encryption
Protect your data by encrypting it both at rest and in transit. Employ robust encryption standards to ensure that it remains unreadable even if data is intercepted or accessed without authorization. Manage your cryptographic keys securely using dedicated key management services. Also, comply with data privacy regulations to safeguard sensitive information from potential breaches.
-
Network Security
Fortify your cloud infrastructure by deploying comprehensive network security measures. Use virtual private networks (VPNs) to secure remote access, firewalls to control incoming and outgoing traffic, and security groups to segment your network. This will ensure that your data stays protected across all layers of your cloud ecosystem.
-
Intrusion Detection and Prevention Systems (IDPS)
Enhance your AI threat detection capabilities with Intrusion Detection and Prevention Systems. These systems will continuously monitor network traffic for suspicious activities and potential threats. By identifying and mitigating intrusions in real time, IDPS helps maintain the integrity and availability of your data.
-
Use Cloud-Native Security Solutions
Cloud-native security solutions should include cloud security posture management, Kubernetes security posture management, external attack and service management, and cloud workload protection. They must incorporate agent and agentless vulnerability scanning to protect your cloud assets from being incorrectly configured.
-
Install Web Application Firewalls (WAF)
Keep your web apps safe against attacks like SQL injections and cross-site scripting. Monitor and filter your HTTP traffic to prevent malicious file exploits, ensuring your applications remain secure against evolving web-based threats. WAFs are a crucial defense layer, protecting your web applications from unauthorized access and data breaches.
-
Implement Employee Training and Awareness
Educate your employees with the best cloud data security programs. Show them the importance of data protection. Teach them to recognize signs of data tampering and how to handle adversaries impersonating officials. Employees should also be adept at identifying common social engineering attacks and know the appropriate actions to take during accidental data breaches. A well-informed workforce serves as a critical line of defense against security threats.
AI & Cloud Data Security
Cloud + AI adds several new amplifiers, vectors, and attack surfaces. Adversaries can design custom payloads which bypass signature-based defenses. These AI tools can also learn from failed intrusion attempts and get better with every attempt. AI-generated voice, text-based phishing, Business Email Compromise (BEC) scams, and deepfake social engineering are also gaining traction. Attackers can poison ML data models, cause data interference, and misdirect or tamper with outputs. They can hijack input validation mechanisms, launch autonomous scripts to map networks, and automatically move laterally across networks without human supervision. AI-powered hacking tools can be used to start and coordinate widespread Distributed Denial of Service (DDoS) attacks, conduct data exfiltration, and cause maximum negative impact on organizations.
AI cloud data security tools can provide protection against AI-powered attacks. They can conduct automated threat and anomaly detection in real-time and provide predictive risk management. AI-powered solutions can help monitor user activities, unusual data access patterns, and identify compromised accounts. AI also automates tasks like configuration checks, reporting, and data classification, plus it ensures continuous compliance with industry regulations like HIPAA and GDPR. It can automatically adjust encryption methods and enhance data security and key management.
Cloud Data Security with SentinelOne
Singularity™ Cloud Data Security can do AI-powered malware scanning and level up your defenses. It can protect your cloud data storage, and protect against even the most advanced attacks. You can get active protection for your Amazon S3 buckets, Azure Blob Storage, and NetApp resources, and you can also make sure that they are compliant.
SentinelOne can detect zero-day exploits in milliseconds with its AI-powered detection engines. You can streamline and automate threat response with automatic quarantine of malicious objects. You can also scan objects directly in your cloud data stores and ensure no sensitive data leaves your environment. It can do real-time monitoring and analysis and track new changes in data. Plus, you can leverage its scalable and load-balanced protection against file-born malware and zero-days with one platform for cloud workloads, data security, endpoint, and identity for your AWS cloud real estate. Singularity™ Cloud Data Security will give you comprehensive coverage and support for regulatory frameworks like PCI-DSS, HIPAA, GLBA, and many others.
See SentinelOne in Action
Discover how AI-powered cloud security can protect your organization in a one-on-one demo with a SentinelOne product expert.
Get a DemoConclusion
Cloud data security and protection will always be multi-layered. As long as users interact and use the internet, data volumes will grow. Which means we need to do a better job to protect it. As organizations scale up, data will flow more freely across multiple apps, services, and cloud environments. The goal here is to ensure data security on the cloud without facing disruptions, interceptions, or compromises.
Now you know how to improve your cloud data security posture. Don’t neglect it because as technologies evolve, your data will too. Stay protected with SentinelOne today.
FAQs
Cloud data security means protecting the data that is hosted on the cloud. It also means securing the data that flows in and out of apps, services, user accounts, and any other digital assets.
Cloud data security is important because it ensures the safety, integrity, and well-being of your organization. Without cloud data security, you cannot really protect your business services, and it can really compromise the reputation of your organization. Once a user account gets breached, they will never trust your company again, and you will have a tough time recovering from such incidents.
Cloud data security focuses on protecting the data itself – files, databases, and information stored in the cloud. Cloud security covers everything else – networks, applications, infrastructure, and access controls. Think of it this way: cloud data security is about encrypting and protecting your files, while cloud security includes firewalls, identity management, and server protection. You need both to stay safe, but cloud data security gets more specific about what happens to your actual information.
Everyone is responsible for their cloud data security: the vendors, users, and anyone else involved in sharing or transmitting cloud data such as third-parties. It is a shared responsibility.
The cloud is never truly secure. As long as technologies evolve, threat actors will also continue to get smarter with their tactics. So you can’t exactly guarantee security always, but you can do your best in implementing the best cloud data security measures. Just stay up to date with emerging threat trends.
Businesses should store their data on the cloud because it’s more cost effective. You don’t have to spend so much money buying hardware and expensive physical resources. Cloud security is also improving and vendors are gaining awareness of the cloud security landscape. So there will be fewer vulnerabilities as newer cloud services come out.
Artificial intelligence and machine learning can enhance cloud data security by incorporating security automation. It adds a layer of thought to security, which makes it more proactive rather than passive. So AI and ML technologies can actually make security smarter and spot the latest threat tactics.
On-premises data environments are not secure, have high costs and not scalable either. They have high maintenance requirements and there’s a lack of end-to-end support. There’s also provide less access to analytics, which is another issue. You can also suffer from data losses and hardware depreciation.
Yes, AI can spot data theft attempts that humans might miss. AI systems analyze user behavior patterns and flag unusual file transfers or suspicious network activity. They can detect when someone downloads too much data at once, accesses files they normally wouldn’t, or sends information to strange locations. Machine learning algorithms learn what normal data movement looks like in your organization, so they catch anomalies faster. You can integrate AI detection with existing security tools to improve accuracy and reduce false alarms.
The biggest threats to cloud data include misconfigurations that leave files exposed, compromised user credentials, and data breaches. Attackers target insecure APIs, attempt account hijacking, and exploit weak encryption settings. Insider threats from employees and human error also put your data at risk. Cloud storage buckets left public, unencrypted databases, and poor access controls create easy targets for attackers. DDoS attacks and advanced persistent threats can also compromise your cloud data over time.