11/07/2024 | News release | Distributed by Public on 11/07/2024 10:06
Data breaches more than tripled in volume between 2013 and 2022, highlighting the urgent need for comprehensive data security posture management (DSPM) to safeguard sensitive data from modern security threats and the breach rate jumped 20% by 2023. So far in 2024, over 1 billion records were stolen and compromised.2
These statistics emphasize the importance of prioritizing data security, and that's where data security posture management (DSPM) enters the picture.
Importance of data security posture management (DSPM)
A recent report by IBM3 revealed that the global average cost of a data breach in 2024 has reached an all-time high of $4.88 million. This statistic is unsurprising, given that data breaches and other data risks can disrupt critical business processes and systems to an extremely damaging degree.
Besides causing financial losses, these incidents take a toll on brand reputation and customer trust. They may even result in non-compliance with data privacy regulations like General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), which could lead to legal action and penalties-further damaging an organization's reputation.
While data risks increase, organizations continue to process more data daily and grow more dependent on it for decision-making and planning. In fact, according to research from IDC, it's estimated that by 2025, 175 Zettabytes (ZB) of data will be moving to the cloud4, showing the immense scale and importance of secure data management. The use of cloud-based applications-in an organization that employs people who work from anywhere-generates increasing volumes of data that are useful for analysis and business intelligence. The cloud and remote work aren't going anywhere, making it crucial for organizations to secure their data and cloud infrastructure using DSPM.
Understanding data security posture management (DSPM)
DSPM works by helping to protect data in the cloud against unauthorized access, misuse, or theft by continuously monitoring, updating, and refining security. DSPM solutions use intelligent automation to identify potential vulnerabilities, enact safeguards, and perform regular system tests and audits within cloud infrastructure.
Definition and key components of DSPM
DSPM focuses on a comprehensive approach to protecting business data from unauthorized access, alteration, disclosure, and theft. DSPM safeguards cloud data across all your multicloud environments.
DSPM involves several steps, including:
Benefits of a strong DSPM strategy
Implementing an effective DSPM strategy is a must for modern organizations because it helps protect data in, public cloud environments, third-party applications, and more.
The right DSPM strategy allows organizations to:
Identifying common vulnerabilities
One of the most critical functions of DSPM is identifying vulnerabilities that can expose sensitive data. It involves assessing your organization's current data security posture, as well as its cloud security posture management (CSPM) strategy, and spotting weak points.
Typical weaknesses in data security posture
The most common vulnerabilities that put sensitive data at risk of unauthorized access and exposure include:
Unpatched software and systems
Older computer systems and software-or software that simply hasn't been updated-lack the most recent security patches and tools. They provide bad actors with easy entry points to access data. Attackers are always on the lookout for known vulnerabilities in applications and plugins that haven't been updated.
Weak access controls
Do you know who has access to what data within your organization? Do you give people broad access to every kind of data so they can do their jobs?
Loose access controls and permissions exacerbate the risk of exposing sensitive data. Not reviewing user permissions regularly can be just as problematic.
Inadequate monitoring and logging
Given today's fast-changing data risk landscape, a lack of continuous monitoring and logging increases data exposure. Organizations need 24/7 monitoring to identify anomalies and mitigate potential data risks before they affect the entire organization.
Enhancing data security measures
How do you prevent sensitive business data from falling into the wrong hands? The key is to implement effective measures that strengthen your organization's data security posture. This includes a range of steps, from comprehensive discovery of structured and unstructured data with a single view to complete control and risk assessment.
Conducting comprehensive risk assessments
Risk assessment involves identifying, analyzing, and evaluating potential data risks and vulnerabilities that could jeopardize sensitive information.
Identifying and prioritizing risks
The first step of risk assessment is to identify high-priority data and potential risks to these assets. Once you've classified your high-priority assets, look for vulnerabilities such as outdated applications and over-privileged accounts, which create easy entry points for attackers.
Next, analyze each risk to determine its likelihood of impacting your organization. This prioritization will help you identify critical data risks that must be addressed first.
Developing a risk management plan
The next step is to create a comprehensive risk management plan that outlines measures to mitigate risks. It usually lays down guidelines for patch management and access controls to minimize vulnerabilities. Additionally, it specifies incident response protocols to deal with potential data compromises.
Implementing effective security policies
Unfortunately, risk management plans aren't infallible. Bad actors may eventually make their way into a company's network and systems. Be prepared for infiltration with security measures to curb data loss.
Data encryption and protection
Encrypting data at rest and in transit minimizes the risk of exposure and misuse. Even if an attacker gets their hands on data, they can't access or modify it without the necessary decryption keys. In addition to data encryption, organizations should also implement strict protocols to manage and safeguard keys and secure data flows.
Access control and identity management
Implementing strict access control helps ensure that only authorized individuals can view and use specific data. Leverage the principle of least privilege, meaning that each individual has only the minimum level of data access permissions necessary to do their job. Least privilege is a tenet of zero trust, which provides direct-to-app access between the workforce and its resources-bypassing their need to connect to the network altogether.
Additional measures such as multifactor authentication and biometric scanning help verify user identities and prevent unauthorized access.
Continuous monitoring and improvement
A set-and-forget approach doesn't work with DSPM. Organizations need to keep an eye on security posture to identify emerging data risks and adapt strategies accordingly.
Real-time threat detection
Monitor data flows, traffic, and user behavior in real time to detect anomalies and alert security teams. Modern security architectures like zero trust apply automated monitoring and machine learning (ML)-based detection tools to mitigate potential data risks at an early stage.
Regular security audits and assessments
Security audits help identify previously overlooked vulnerabilities and determine the effectiveness of existing security measures. To identify gaps in the security posture, regularly evaluate data protection strategies, access controls, and logging protocols.
Incident response and management
If you do experience a data breach or discover that data has been compromised, there are ways to minimize damage from these incidents and ensure speedy recovery.
Establishing an incident response plan
First, create a well-defined incident response plan that outlines the steps to take if data is put at risk. Establish an incident response team and assign clear roles and responsibilities for containment, investigation, and recovery.
Also, outline protocols for communicating with internal and external stakeholders about the incident, which will speed up your crisis response and help curtail the damage.
Post-incident analysis and learning
Conducting a post-incident analysis sheds light on how the attack happened to help identify gaps in your security posture. It also enables you to evaluate where you can improve recovery steps. Ideally, your analysis will assist with reducing similar incidents in the future and improving response time and remediation.
Leveraging advanced tools and technologies
You'll need to onboard some modern tools to implement the right DSPM strategy. Technologies like artificial intelligence (AI) and ML should be inherent in the ones you choose.
Overview of the latest DSPM tools
Here are a few advanced capabilities of DSPM to consider:
AI and machine learning in threat detection
AI/ML-powered security offerings help detect data risks in real time by learning from historical incidents and other events to pinpoint potential anomalies. They can also help in precise data discovery and classification which can be useful from a risk detection, policy implementation, and compliance perspective. These tools spot abnormal data transfers and unauthorized access attempts before a data risk spirals out of control.
Automation tools for policy enforcement
Advanced security offerings can automatically encrypt data and implement access controls. For instance, when a user completes a specific task, you can automatically revoke their permission to access certain data they no longer need-minimizing the risk of unauthorized exposure.
Integrating tools into existing systems
Cloud native DSPM tools should support integration with the following: