KDnuggets Home » News » 2016 » Aug » Tutorials, Overviews » How Can Data Scientists Mitigate Sensitive Data Exposure Vulnerability? ( 16:n32 )

How Can Data Scientists Mitigate Sensitive Data Exposure Vulnerability?

What is sensitive data? How does it affect data science, and what can be done to mitigate data exposure vulnerability? Read on to find out.

By Laurel Brian, Data Recovery Singapore.

What is Sensitive Data Exposure?

Sensitive Data Exposure Vulnerability is one of the most critical security threats that can result in compromising the security of modern­ day web applications. It occurs when a web application does not adequately protect sensitive information from being disclosed to unauthorized users. These are typically implementation flaws, which are exploited by the hackers to gain access to sensitive information stored by the application.

How Does Sensitive Data Exposure Vulnerability Affect Data Scientists?

Data scientists typically use several web­-based solutions, platforms and applications to process, analyze and visualize the data points. According to Open Web Application Security Project (OWASP) ­ a worldwide non­profit community focused on improving the security of web environments ­ issues related to sensitive data exposure vulnerability can adversely affect data mining platforms, data integration solutions, business intelligence suites and other analytics applications that are accessed via internet. As data science projects often deal with mission-critical business data, any unauthorized access may lead to serious information security and data privacy violations.

Sensitive data Coppertone girl
Image from Credera's blog.

How to Mitigate Sensitive Data Exposure Vulnerability?

Enforce Encryption for Accessing Critical Data:

Business Data can broadly be categorized into two groups ­ public and protected. Protected data should ideally be kept confidential to a group of authorized users only. First and foremost, you should identify the protected data that are sensitive enough to require extra protection. Once you have identified the sensitive data points, deploy a proven encryption technique to safeguard the data while at rest and during transmission. Key­ based encryption enforces the users to provide the corresponding decryption key for gaining access to the encrypted data points.

Safeguard the Authentication Gateways:

Weak authentication function can be a soft target for the hackers to steal sensitive information. For safeguarding critical business data, you should make use of an advanced transport layer security protocol (SSL/TLS). It's a good idea to enforce HTTPS sessions to protect all the authentication gateways. Businesses that deal with sensitive data can make use of two ­factor authentication technique to minimize the risk of potential security breaches.

Deploy Strong Password Hashing:

Brute ­force attacks can successfully penetrate weak password hashing techniques. There are several hashing algorithms to choose from, but when you are dealing with sensitive information, you should ideally opt for the one that supports cryptographic hashing function.

Simulate Retrospective Hacking Attack:

Penetration testing can be used to identify the weak areas in your environment before a hacker can exploit them. Simulate a real ­life hacking attempt on your application to figure out how secure the application is. If the attack succeeds, then investigate further to fix the vulnerable attack vector.

Have a Disaster Recovery Plan in Place:

When a hard drive crashes or gets corrupt, it is pretty easy to recover the data. For a data science project that deals with petabytes of data, however, the procedure of data restoration is far more complex compared to a standalone hard disk recovery. Isn't it better to be safe than sorry? That's why every data science project must have a proper disaster recovery plan in place to retrieve the data in the event of a disaster.

Final Thoughts:

The absence of a proven encryption technique to safeguard the application is the most common root cause for unauthorized data access. Improper key generation, weak password hashing algorithm, broken authentication tokens and brute­ force attacks are the other contributing factors that may result in sensitive data exposure. It does make sense to have a well ­defined disaster recovery plan when you are dealing with a huge volume of data. Last but certainly not the least, there should be periodic audits to review the security compliance to prevent unauthorized access of sensitive business information.

Bio: Laurel Brian is a content writer and marketing consultant at Data Recovery Singapore. As a tech geek he is continually drawing upon his own talent and skill, and as a marketing consultant he enjoys the business challenges and build relationships.


Sign Up