How Data Risk Detection and Response Are Becoming Crucial Components of Cloud Security

Cloud Security
How-Data-Risk-Detection-and-Response-Are-Becoming-Crucial-Components-of

With so many complex threats online, organizations need to be able to detect and respond to cloud breaches in a matter of minutes if they want to protect their mission-critical data.

At a fundamental level, cloud security is data security. However, a lot of businesses are having trouble locating and safeguarding the data they’ve stored in the cloud. In fact, a recent report by Netwrix, 2022 Cloud data security report, reveals that although 53% of organizations recently experienced a cyberattack on their cloud infrastructure, 80% of organizations store sensitive data in the cloud.

Modern-day organizations need to be able to detect and react to cloud breaches in a matter of minutes if they want to protect their mission-critical data because there are so many complex threats online.

Also Read: Surge in IT Costs, Indian Companies Encountered More Cyberattacks

Using real-time data detection and response is one way to achieve this.

The reality of modern cloud security

One of the main reasons why cloud detection and response is becoming more important for enterprises is the cloud skills gap. Micro services, multicloud environments, and a dramatic rise in remote work are all contributing to the exponential growth in the quantity and variety of data assets in the cloud. Data now makes up a sizable portion of cloud resources and is more prevalent in public clouds than on-premises. In order to reduce the impact of security incidents, security teams must be able to react quickly to threats. A skilled attacker can carry out a data breach in the cloud in a matter of minutes.

Protecting data in multi-cloud environments

Despite the rise in popularity of cloud computing over the past ten years, businesses across all sectors have been hurt by the complexity and lack of transparency surrounding where and how data is stored. Today, the majority of big businesses use multiple clouds and have a wide variety of data storage options. Because of this fragmentation, businesses are unable to secure and manage their cloud data stores, comply with compliance requirements, and guard against data breaches. With agentless cloud monitoring of data assets kept in the cloud, businesses can address this visibility issue.

Cloud Detection and Response

A novel approach to cloud security called cloud detection and response (CDR) enables security teams to protect cloud applications and infrastructure from account compromise, insider threat, and unauthorized access. Consolidated visibility and data-driven analytics for cloud threat detection, investigation, and mitigation are provided by cloud detection and response.

In order to provide insights, situational visibility, and alerts about risks and threats, cloud detection and response solutions continuously aggregate, normalize, and analyze large volumes of data about accounts, privileges, configurations, and activity from SaaS and cloud services.

Cloud Access Security Brokers

Cloud access security brokers (CASBs), one type of existing cloud security solution, use a perimeter gateway approach to cloud security. By attempting to obstruct all point-to-point communication between users’ devices and cloud services, CASBs function. In addition to failing, this strategy leaves organizations with a fragile architecture made up of agents, forward proxies, and reverse proxies that requires a lot of operational work to deploy and maintain.

Also Read: Addressing Cybersecurity Needs with Managed Detection and Response (MDR)

Data Detection and Response

Using Data Detection and Response (DDR), organizations can address risk in ways that have never been possible before. DDR is a novel, revolutionary approach to the protection of enterprise data and intellectual property. As part of an approach that combines data security posture management (DSPM), data loss prevention (DLP), and cloud data detection and response (DDR) capabilities into a single solution, organizations can respond to these threats by using a threat model to detect and respond to threats at the data level. This strategy aids in addressing some of the additional particular difficulties associated with upholding cloud security

Attackers can still get past defenses and gain access to cloud assets even with such a solution in place. This is due to the fact that attackers are successfully using a variety of techniques, such as credential stuffing, social engineering, spear phishing, and brute force password guessing, to gain access to resources in cloud services while posing as users and service accounts. Account compromise and insider threats are on the rise, but as the attacker and company data move from the endpoint to the cloud, the data needed for security professionals to track down and investigate these attacks is lost.

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