Companies are investing more and more in data protection. Compliance rules and regulations require organizations to develop sound security strategies in order to protect their valuable data assets and data privacy.
Reducing compliance burden is just one driver – minimizing risk, or at least lowering the impact of breaches, is another. It is an understood fact that attackers are constantly seeking ways to circumvent security to gain access to sensitive data. As many industry reports have shown, when it comes to a data breach, the costs can become astronomical due to the effects on stock price, customer retention, and brand reputation.
Another driver motivating companies to protect sensitive data is to monetize regulated data to stay competitive and gain new business. Some organizations only work with companies who have the ability to share data that is already protected, rather than having to carry the responsibility of protecting the data themselves.
Companies who have the ability to protect data will be in a better position to attract new customers. But where to start? Here are five important steps to protect sensitive data:
Step 1: Locate your Sensitive Data
In order to effectively secure sensitive data, companies must identify all places where data is stored, processed or used. This is a necessary first step in complying with many regulations, such as carrying out regular risk assessments, logging access, and data disposal.
Step 2: Data Minimization and Reduction of Scope
It is a common best practice to reduce the amount of data being processed. This has the advantage of minimizing risk and reducing the time, effort, and costs associated with securing data.
Step 3: Data Protection Risk and Impact Assessments
The threats to personal data and cardholder data are changing constantly. In order to keep up, organizations must conduct regular reviews to gauge how well data is being protected. In addition, whenever an organization undergoes major changes that might affect data security policy and processes, such as mergers and acquisitions, relocation, or the adoption of new data processing systems, risk assessments must be carried out.
Step 4: Define Policies & Protection Methods
Security policies should define which data is going to be protected and which protection methods to use. Data classification tools can help to identify data elements and decide the right protection method.
Limiting access to sensitive data and defining access policies is another key component. Every account with access to sensitive data is a possible attack vector and therefore limiting access is analogous to limiting vulnerability. Implementing data-centric security using a central access model helps to execute access policies in real time while increasing visibility on data usage on the user level.
Step 5: Keep an Audit Trail
In addition to the accessibility limitations referenced above, logging access to sensitive data is another indispensable part of any data security strategy. Access logs are useful for proactively detecting potentially malicious activity and, if a breach does occur, they are essential to investigations to determine the source of the breach. Again, using a central access model enables organizations to log every single time sensitive data is accessed and helps to create a detailed and meaningful access trail.
To evaluate the appropriate data protection technology, it is imperative to look beyond the high level buzzword messages of vendors and really understand the properties, benefits, and use cases of the various technologies available.
With the appropriate protection, security travels with the data – independent of applications, databases, and platforms – at rest, in motion, or in use. This allows organizations to take complete control of their sensitive data, lowering compliance costs and significantly reducing the risk of data breaches.