With digital assets scattered around IT environments and data breaches still a constant concern, companies face a daunting security challenge: how do they harmonize the security model to avoid using different tools and best practices for the traditional three-tier data center than they have for the cloud?
A recent study revealed that securing data moving between on-site and the cloud was the second data protection obstacle, followed only by protecting against malicious damage/hacking.
A more programmatic approach that explores and incorporates all data sources and networks into a holistic security strategy is required by organizations today.
User Behavior Is Important
A more user-centric approach is required. In other words, the security policies should be applied to each user individually, based on where they fall on the risk scale. Depending on the actions of an individual, such risk assessments and the policy implementation based on them will change dynamically.
This notion is confirmed by the study findings. Businesses deploying behavioral analytics, machine learning, and cloud-based access controls were the least likely to have been violated.
Traditional approaches to security have been established to secure a conventional infrastructure with a defined perimeter. As the perimeter is all but gone, organizations that identify data movements between data centers and the cloud and enforce policies that account for changing risk factors, such as the device and network in use and the user’s identity and job status, are more likely to avoid breaches.
1. Deploy Data Loss Prevention (DLP) systems with machine learning, automation, and data analytics.
Companies that have added automated DLP systems can easily detect users’ patterns of activity and learn from them to grant or deny access automatically based on the significant variables of the business.
2. Implement user-centric policies.
Securing channels one by one is not easy as staff interacts with information on PCs, tablets, USB sticks, email, etc., especially when using different security products that do not integrate. It’s easier to track data based on user variables like device, network, and application.
3. Be careful of protecting only a subset of your entire data.
Many enterprises run their DLP systems in audit-only mode or take a black-and-white approach to blocking or allowing all access to data. Besides, they protect data carefully but only for certain networks or avenues while leaving others wide open. These approaches leave organizations vulnerable to downtime, loss of reputation, fines, lawsuits, and loss of information.
4. Avoid a mix of unintegrated, point security products.
This mainly happens when businesses initially have a very simple requirement, which increases when security products are extended and integrated. Joining many security instruments leads to disconnects, gaps, and inefficiencies when you want a more comprehensive, streamlined, and efficient solution.
5. Assess emerging centralized security systems.
Newer, more unified systems will allow visibility through hybrid, private, and public cloud networks while automating security policies based on changing circumstances.
Although several businesses are struck by breaches, those with behavioral analytics, cloud data control, and machine learning who have added automation are much better. Focusing on the individual, taking a dynamic approach to evaluating their behavior, and changing security policies based on real risk can help organizations manage their security more effectively.