Data is very quickly becoming the new endpoint, and as such, access control is a necessity for the modern enterprise to stay protected from breaches and attacks. With cloud computing and the Software as a Service (SaaS) revolution, more and more data is being moved off-premises to the cloud. This means that security breaches are more likely to occur as well as potential compliance violations if the right controls and processes are not in place. With properly managed data access control, you can protect yourself from insider threats, external attacks and ensure compliance with regulations while keeping your stakeholders happy with a seamless user experience.
Data Security in the Modern World
Data Security has become ever more relevant and necessary as the world of tech has become a SaaS application world. Especially with the high number of SaaS applications being utilized by present day businesses it becomes a challenge at scale to govern access and secure sensitive data that is shared and manipulated by internal and external identities. The more people who have access to your company’s data, the higher the risk of a security breach or other negative outcomes (i.e. business disruption, financial penalties, brand damage, etc).
Many enterprises today struggle with competing priorities such as ensuring customer satisfaction while balancing protecting customer privacy; providing employees with better tools for collaboration while not compromising on network security; enabling faster decision making without exposing too much confidential information about projects in progress; etc. – which means there are many potential incidents waiting on the sidelines if proper safeguards aren’t put into place quickly enough!
Why is Data Security Important?
Data access control helps prevent insider threats by controlling who can see what information and when they can see it. This includes restricting employee access rights based on their role in the business, location, and other factors such as proximity to sensitive data or instances where an employee has lost their phone or tablet device that contains sensitive data. In high-risk situations, security teams need to act quickly to remediate data access issues and prevent overexposure to protect the business (e.g. data exfiltration and insider threats). Remediation actions are typically performed manually across different SaaS applications, which is not operationally efficient and increases the response time.
Why is Data Security Extra Important in SaaS Applications?
Data security is especially critical within a SaaS environment and applications for a number of reasons.
Within SaaS apps, all end users can access and interact with your company’s data, at least to some extent. Basically, because SaaS apps make data accessible to so many people, you’re looking at a very large attack surface due to the sheer scale of potential exposures. This is opposed to configurations, to which only a few users will have access.
The collaborative nature of SaaS apps means that information is shared more frequently than in non-cloud environments. Focusing on productivity and streamlining workflows mean that users will constantly add additional permissions or grant access to their colleagues or third-party contractors, so your potential sensitive data exposures are exponentially growing.
That’s not to mention that change happens within SaaS apps incredibly fast. As fluid, dynamic spaces with constantly changing permissions, users, and access levels, your IS or IT teams don’t have the luxury of time to catch and mitigate potential issues.
Data assets within your organization are likely growing at incredible rates. A recent survey and analysis by DoControl of SaaS environments at businesses with more than 1,000 employees revealed just how quickly this expansion occurs. We found that on average, companies began 2023 with 7.9 million SaaS assets and ended the same year with a total of 22.8 million - signifying a massive growth rate of 189%.
Types of Data Security
There are numerous methods you can leverage to strengthen your data security, ensuring that sensitive information within your business stays safe. These include:
- Encryption
- Data access governance
- Data erasure
- Data masking
- Data resiliency
Encryption: Encryption is the process of converting data into a coded form that can only be accessed or understood by someone with the necessary decryption key. It is often used to protect sensitive information from unauthorized access or tampering.
Data access governance. Applying strict controls regarding which users can access your data, as well as verifying those users’ identities, is critical for safeguarding your data.some text
- This means taking steps to check that the people accessing your data are actually who they claim to be, and making sure that access to sensitive information is granted on a need-to-know basis.
- Data access governance also encompasses revoking permissions from users who no longer need access, along with regularly reviewing of all your sensitive data exposures and permissions.
Data Erasure: Data erasure, also known as data wiping or data sanitization, is the process of irreversibly destroying or deleting data from a storage device so that it can no longer be accessed or recovered. This is typically done to ensure that sensitive information is not leaked or disclosed when a device is no longer needed or is being reused.
Data Masking: Data masking is the process of disguising sensitive data with fake, but realistic, data while still maintaining the integrity and structure of the original data. This is often used to protect sensitive information when it needs to be shared with others, such as during testing or development.
Data Resiliency: Data resiliency refers to the ability of a system to recover from failures or disruptions and to continue functioning without data loss. This can be achieved through various measures such as backup and recovery systems, fault tolerance, and disaster recovery planning.
Data Security vs. Data Privacy
Data security refers to the measures taken to protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. It involves protecting data while it is being transmitted and while it is being stored. Data security is concerned with ensuring the confidentiality, integrity, and availability of data.
Data privacy, on the other hand, refers to the right of individuals to have control over their personal information and how it is collected, used, and shared. Data privacy is concerned with respecting the privacy rights of individuals and protecting their personal information from being mishandled or misused.
In short, data security is about protecting data from external threats, while data privacy is about respecting the privacy rights of individuals and protecting their personal information. Both are important for protecting sensitive information and maintaining trust.
Common Data Security Risks
The most common risks to data security include:
- Malware
- Insider threats
- Social engineering attacks like phishing
- Accidental data exposure
- Ransomware
Malware refers to software designed to cause harm to a computer or network. Malware can take many forms, including viruses, worms, trojans, and ransomware. It can be transmitted through various means, such as email attachments, infected websites, and removable storage devices. Malware can cause a range of data security problems, including:
- data loss
- system disruptions
- unauthorized access to sensitive information
Insider Threats refer to security risks that come from within an organization, such as employees or contractors who have legitimate access to an organization's systems and data but use that access for malicious purposes. Insider threats can include intentional or accidental data breaches, sabotage, and theft of sensitive information.
Phishing is the practice of tricking individuals into giving away sensitive information, such as passwords or financial information, through fake websites or emails that appear legitimate. Phishing attacks often use social engineering techniques to manipulate people into divulging their personal information.
Accidental Data Exposure occurs when sensitive data is unintentionally made available to unauthorized individuals. This can happen through a variety of means, such as misconfigured cloud storage settings, sending emails to the wrong recipients, or posting sensitive information on a public website.
Ransomware is a type of malware that encrypts a victim's data and demands a ransom from the victim to restore access. Ransomware attacks can be particularly disruptive and costly, as they can result in data loss and downtime.
Misconfigured access permissions and generative AI
Misconfigured access permissions - meaning permissions that grant too many levels of access or are too far-reaching - are especially problematic in the era of generative AI, with the potential to cause even more accidental sensitive data exposures than before.
Generative AI tools usually have access to ALL of your company’s data, and can theoretically pull and use any of it in its responses. But you wouldn’t want it to expose your secret go-to-market strategy to your company’s bookkeeping intern. So how does the generative AI know what it is allowed to use as source material for any given response? Asset access permissions.
When the prompter (i.e., the user prompting the AI tool) asks the generative AI tool a question, the tool uses as sources only assets to which the prompter has access permission. uses as potential sources. This reliance on SaaS asset access permission settings can lead to several types of situations where data is exposed beyond what it should be.
Amplified internal data leakage
Internal data leakage has long been a challenge for large organizations working within SaaS applications. Sharing settings that allow everyone within a business to view an asset are the source of much internal data leakage. Oftentimes, employees set this level of permissions on assets, because it’s easier than manually adding in each team member who needs access.
While the “everyone at my organization can view” setting certainly streamlines workflows and makes collaboration easier, it also means that 1,000 people within a business can view a sensitive document to which only 20 people actually need access.
The danger of this overprivileged sharing setting is exacerbated by generative AI. The reason? For companies not using generative AI tools, most employees with over-privileges to view sensitive SaaS assets simply had no idea of the existence of these items. Unless they were specifically given a link, most of the time these sensitive assets were hidden from them and they would never end up viewing them.
But if these same employees ask their company’s generative AI tool a question, the AI tool will use all relevant assets at its disposal to answer the question. Those assets will include these sensitive assets that they technically have permission to view, even though they shouldn’t. Suddenly all this sensitive information is placed right in front of the employee.
It’s clear that generative AI can lead to even more internal sensitive data exposures, especially in the event that mistakes grant employees access to assets which they don’t need to view.
External leakage of remixed data
Because generative AI creates new content based on existing assets within a business, it’s easy for the tool to accidentally create new content that contains sensitive information and isn’t labeled as such.
Let’s say a prompter uses AI to create a draft of a product marketing plan. They then send it along to their external marketing agency. The prompter, however, doesn’t realize that the AI tool drew information from a confidential go-to-market strategy for an upcoming product release.
Because this is newly generated content, it doesn’t necessarily get labeled or categorized as “sensitive”. It gets shared indiscriminately, potentially harming the company
How Data Security Works with Other Types of Security
Data Discovery and Classification Tools: These tools are used to scan through an organization’s data to discover any sensitive or confidential information, and then classify it according to its value and sensitivity. This helps organizations to better protect their data by placing the appropriate security measures on each type of data.
Data and File Activity Monitoring: This solution monitors and records any data access, changes, or transmissions that occur, allowing organizations to spot any suspicious activities and take the necessary action to protect their data.
Vulnerability Assessment and Risk Analysis Tools: These tools analyze the security of an organization’s systems by scanning for any known vulnerabilities, and then calculate the risk associated with those vulnerabilities. This helps organizations identify any gaps in their security, and take the appropriate measures to fix them.
Automated Compliance Reporting: This solution automates the process of generating reports that demonstrate an organization’s compliance with any applicable data security regulations. This helps organizations meet their regulatory requirements while also providing evidence that they are taking the necessary steps to protect their data.
Data Security Trends
Cloud Computing Security: Cloud computing has become an increasingly popular option for storing and managing data, and businesses of all types are taking advantage of its scalability and convenience. As the use of cloud computing continues to grow, so does the need for improved security measures. Companies are now taking steps to ensure that their data is stored securely and protected from potential cyber threats.
Artificial Intelligence (AI) Security: AI is being used to detect and prevent cyber threats, as well as to improve the accuracy of security systems. AI can detect patterns in data and recognize malicious activity, allowing organizations to respond more quickly to potential threats.
Agentless and Event-Driven: It has become an absolute necessity for modern enterprises to secure sensitive data and files within business-critical SaaS applications. Doing so over time through granular, no-code workflows helps you understand how much data is exposed, remediate it quickly, and automatically remediate.
Data Security Solutions: Protection from External Attacks
The first benefit of data access control is having the ability to protect your business against external threats. Attacks on your company can come from a variety of avenues, but they all have one thing in common: they are the result of someone who was given access to vital information.
The second benefit is that by controlling this access, you can prevent insider attacks as well. The nature of these attacks may differ based on whether it's a threat coming from someone outside or inside your organization, but the end goal remains the same – someone who has been given access uses it for malicious purposes.
Data Security Compliance with Regulations and Business Mandates
Compliance with regulations and business mandates is a necessity for the modern enterprise. From HIPAA to GDPR, data access control is now a business priority for many organizations.
This is why compliance and management of regulated information has been a top priority for many organizations. It’s also why leading companies like Google and Amazon are investing so much in this area – because complying with regulations doesn't just mean being able to pass audits; it means being able to run your business effectively while still protecting sensitive data from misuse or exposure.
Data Access Control is a Necessity for the Modern Enterprise
Data access control is not only about protecting against insider threats – it also protects against external attacks, and complies with regulations and business mandates. With this, data access control provides unparalleled protection for your SaaS apps that is seamless to use and transparent to your users. Enterprises must have the ability to centrally enforce comprehensive data access workflows throughout complex SaaS application environments and auto-expire sharing permissions for assets within SaaS applications to prevent overexposure and minimize the attack surface area.
Data Security with DoControl
By managing access to your data, you can protect it from insider threats, external attacks and compliance with regulations. DoControl’s approach to data access control provides unparalleled protection for your SaaS apps that is seamless to use and transparent to your users. With DoControl Security Workflows, you can automatically revoke external access to SaaS assets after a predetermined time period; allow business users to provision and deprovision access to approved third parties on-demand; and restrict third-party collaborators from sharing your SaaS-hosted data with unauthorized fourth parties, such as their own vendors or personal email accounts. DoControl makes it easy for cloud-first organizations to secure their collaboration with third parties without sacrificing operational efficiency.
If you’d like to learn more about how DoControl offers industry leading data security solutions and DLP security try a demo today.
FAQ’s
What are the four 4 key issues in data security?
Poor data security elimination protocols: Enterprises may not take notice that in cases where data is no longer in use, it can be the target of a cyberattack. When a company lacks a data elimination policy or has faulty controls in place for data sanitization, it may lead to costly data breaches.
Lackluster remediation: Companies should closely evaluate how they store and remediate data. Establishing automated workflows is an essential way to keep track and identify when and how data should be remediated.
Not adopting a 'zero-trust' approach: Data controls must support a zero-trust approach in order to deliver a fully integrated data security strategy. Security professionals must lose the idea of a trusted internal network and an untrusted external network in order to continuously assess trust through a risk-based analysis of all data.
Not being flexible/hybrid in their approach: Modern data security poses more risks than ever before and therefore requires subsequent actions to those risks. With this, the need for security tools and practices that are inherently flexible, no-code, and hybrid in their nature. In addition, by replacing manual work with automation, it reduces the overload of work and complexity that Security/IT teams have to deal with every day.
What is the primary objective of data security controls?
The goal is to remediate data access issues and prevent overexposure. This can be achieved through centrally enforced comprehensive data access workflows throughout complex SaaS application environments and auto-expire sharing permissions to prevent a malicious data breach and minimize the attack surface.
Who is responsible for data security?
Every employee is responsible for following the data security policies instilled by the IT and security teams. However, at the end of the day, the blame for a data breach will most often be on the IT team and C-level leadership.
What are the risks of weak data security?
If you don’t invest in robust, comprehensive data security for your business, you are putting your company at risk for numerous consequences. A data breach or leak, in which a threat actor obtains your company’s sensitive information, could spell disaster for your business. This could look like a cybercriminal stealing customers’ PII (Personal Identifiable Information), leading to a major loss of consumer and investor trust. That’s not to mention potential damage to your brand reputation and standing in the market once the breach becomes public knowledge. It’s also important to remember that if a regulatory agency finds you were not in compliance with local data protection laws, you could be subject to large financial penalties or even legal action due to the data leak.
What are best practices to strengthen my data security?
Ensuring that your data security is strong enough to effectively safeguard your business’ critical internal and customer information is a multi-pronged process. First, you should locate and categorize all of your sensitive data exposures - you can’t protect assets if you don’t know where they are located, or are unaware of their existence. Second, take steps towards a Zero-Trust approach, which makes verification of user identities and evaluation of access controls a central part of your data security strategy. Third, consider using third-party tools and platforms, such as SSPMs, to help you gain critical control over your assets and the sensitive data within them.
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