What is a data protection strategy?
A data protection strategy refers to a collection of steps and procedures to maintain the integrity of enterprise data. It is a holistic framework that defines how business-critical data should be maintained and with whom should it be shared. Most data today pass through some form of software application or the other. So, web application security assessment has become an integral part of most data protection strategies. Applications are subjected to stringent software security testing to ensure risks of zero data breaches.
Data privacy risk has always been a growing concern at the global corporate level. According to the findings of an extensive pen testing project, hackers can successfully crack into an organization’s internal data perimeter in 93% of cases. Many can’t prevent their super users from accessing sensitive information on production databases. Most are unable to even detect these incidents. Over time, there has been a marked rise in threats from social engineering and advanced ransomware as well. So, it is mandatory for applications to be robust and secure. But to ensure the same, organizations must have software security testing in place. A good Test Data Management strategy is super-critical in such cases.
The number of online transactions is increasing exponentially. In today’s post-pandemic world, everyone’s financial data is everywhere. Misconfigurations, poor maintenance, and unknown data assets at data-handling companies often pave the way for impending disasters.
Why do you need a data protection strategy?
The benefits of having a data protection strategy are manifold.
- Protects the holistic integrity of enterprise data
- Saves against financial loss and public relations hassles
- Safeguards customer privacy; strengthens trust
- Helps to maintain compliance with third-party regulations
- Facilitates easier management of data and information
Data privacy has been one of the most pressing concerns since the last few decades. And, given the rapid growth of data, some of the breaches are proving to be devastatingly massive. For example, back in September 2018, Hotel Marriott International (Starwood) reported a sensitive data breach for half a million of its customer base. The ensuing investigation exposed unauthorized hotel network access for four-long years preceding the attack. It goes without saying that the PR aftershocks were massive. On top of this, the company was fined £18.4 million by the UK Information Commissioner’s Office in 2020 for failing to keep customers’ personal data safe.
The benefits of having a data protection strategy in place
More recent examples of data breaches pertain to the Facebook data loss of 2021 and the data breach from Srilankan payment gateway PayHere that exposed over 65GB of customer payment records.
According to Verizon, 82% of breaches result from human discrepancies and social attacks. 62% of all attacks compromise client-sensitive information and affect partner relationships.
Should you include application testing in your data risk management plan?
Absolutely yes! A low-hanging fruit is to focus on the treatment of production database(s) while testing software applications. It’s not uncommon for large companies to maintain ten copies of production – full clones used for testing, training, and development purposes.
To make matters worse, the people who have access to these copies of production are often “outsiders” – third-party consultants who you may not have vetted as carefully as your actual employees. Giving them full access to sensitive corporate data creates a significant privacy risk.
Where to begin privatizing data? Many organizations struggle just to figure out where all their at-risk data lives in the corporate environment. The next step is to put in place a simple yet reliable mechanism for masking, or scrambling, that data so that it will still be useful for testing but won’t endanger the privacy of your customers and employees. In the face of a colossal threat to user data privacy, software testing security is a must-have function.
IBM InfoSphere Optim hosts excellent data privacy solutions
IBM InfoSphere Optim Data Privacy is a solution that minimizes risk without slowing down your testing. By masking personal information, IBM Optim protects confidential customer and employee data and ensures compliance with all levels of privacy regulations.
Of course, masking your data is only part of the game. It’s also a best practice to subset your production database, rather than use full copies of production, for testing and other non-production activities. IBM Optim Test Data Management facilitates that process. And when you use Optim Data Privacy and Optim Test Data Management in tandem, you can actually apply data privacy rules to production data while you’re subsetting it.
Implement IBM InfoSphere Optim solutions with a reliable data protection partner
The hallmark of a true partnership lies in its years of support and excellence. For us (Estuate) and IBM, the journey has been true to this essence.
We are IBM’s go-to partner for IBM InfoSphere Optim solutions across many platforms and use cases. Together, we have built a successful track record with 350+ InfoSphere Optim implementations.
Below is a snapshot of the Estuate-IBM synergy:
- IBM InfoSphere Optim Archive Solution – By archiving little-used data and retiring obsolete applications, you expedite cost-efficiency. What’s more? The archived data can be accessed at any time.
- IBM InfoSphere Optim Data Privacy Solution – This safeguards all your sensitive data located across non-production environments.
- IBM InfoSphere Optim Test Data Management Solution – Agile test environments having the right-sized subsets are the basis of robust software applications. It’s a bonus when you get to secure your sensitive test data too in the process.
What is your take on data protection and risk management? Is web application security assessment really necessary or it just tends to slow down the speed of deployment? Let us know on LinkedIn, Twitter, or Facebook. We would love to hear from you!