Table of Contents
  • Assess your most valuable data and who has access to it. 
  • Ensure that employees are properly notified of policies and procedures. 
  • Monitor applications that contain sensitive data along with who's accessing it and why.
  • Immediately cut off physical access to your network when an employee departs. 
  • Use multi-layer authentication 
  • Implement a sanctioning policy and ensure employees understand they are being monitored. 
  • Implement a culture of accountability and security.

It’s becoming exceptionally rare for a week to go by without a significant digital breach making headlines. Companies are scrambling to respond to evolving threats and big data security concerns, but to do so, they must recognize the major risks that they face. By understanding the most significant threats out there, stakeholders can build improved mitigation and response measures. 

  1. Fake Data Generation
  2. Reversing Data Masking Measures
  3. Multi-Cloud Computing
  4. Data Cleansing Problems
  5. Big Data Complexity
  6. Real-Time Security Compliance
  7. Data Mining Issues
  8. Lack of Security Spending
  9. Lack of Security Audits
  10. Employee Theft
  11. Employee Negligence
  12. Conclusion

1. Fake Data Generation 

One of the most significant security issues facing big data today is the generation of fake data. You can choose the best type of data processing and implement a variety of security features, but if you’re unable to detect fake data that’s been placed within your central repository, you’ll face significant hazards that reduce your ability to protect client information. 

Fake information is a significant big data security concern because it reduces your ability to identify other issues. False flags from fake data, for instance, could make it difficult to identify fraud. False reports could also result in unnecessary actions being taken that could reduce production or other essential aspects of running a business. 

2. Reversing Data Masking Measures

When it comes to consumers' big data security concerns, the worry is always related to their personal data. Over 90 percent of people say that being in control of who can access information about them is important. To alleviate these concerns, many companies have opted to implement data masking policies. Unfortunately, this can create a false sense of security. 

Data masking is meant to separate confidential information regarding clients from identifying data. When done correctly, the process cannot be reversed, but malicious actors with the necessary equipment can sometimes reconstruct databases. This could allow them to reconnect individuals to their confidential info. In addition to endangering client data, sensitive corporate information can also be at risk. 

Data masking is one of the many services provided by Integrate.io. We understand that the integration process is only as safe as the data within it, so you can rest comfortably knowing your company's and clients' information will be safeguarded.

3. Multi-Cloud Computing

Multi-cloud computing has changed the way business is done, and it has allowed companies to get most of their work done in the virtual world. Unfortunately, this trend means there are more access and endpoints in need of protection. It also makes it easier for audits to overlook potential vulnerabilities. 

CSO listed multi-cloud computing as one of the most urgent cybersecurity threats facing the world today, and this risk will only increase as more of our data is stored in the cloud. This can present a particularly hazardous issue if you’re transferring information into or outside of the cloud, so it’s imperative to utilize appropriate tools when doing so.

4. Data Cleansing Problems

Big data security concerns aren’t always connected to breaches, and this becomes apparent when automatic cleansers are being utilized. There are many data cleansing tools, both manual and automatic, that your firm can choose from. Related data attributes can be inconsistent, though, if an automated data cleansing process is based on a faulty model. 

The other big issue with automatic cleansers is that data management personnel can become complacent. This can reduce the quality of your database, but it may also create the potential for breaches. In fact, security complacency is listed as one of the main causes of breaches around the world.

Fortunately, we utilize the most advanced data cleansing tools at Integrate.io. Your data needs to be more than safe; it needs to be accurate and easily accessible. Our resources make this a reality.

5. Big Data Complexity

One of the biggest threats with big data is the diversity of data set used at any given time. This information can be structured or unstructured, and its origin sources could include mobile devices, servers, email files, cloud applications, and more. Data becomes more difficult to secure as it becomes more complex, so it's important to utilize a proven extract, transform, and load (ETL) service to increase data compatibility.

6. Real-Time Security Compliance

Big data storage will ideally include real-time tools that ensure security compliance. These resources consistently monitor processes to ensure a company is taking appropriate measures to safeguard data. As these tools run, though, they create their own large amount of data that must then be processed. A breach in this data can be as detrimental as hackers accessing your other databases.

Even though it creates droves of additional data that must be safeguarded, these real-time compliance tools are essential. Make sure you research your options and choose wisely. Find an option that has tools meant to minimize potential false positives. A single false breach warning can result in wasted resources and the potential for overlooking actual breaches.

7. Data Mining Issues 

Data mining is a powerful tool in helping better understand and utilize the data your company owns. By utilizing your database systems along with statistics and machine learning, you can discover patterns that help you more effectively target consumers. Even though this process is handled by professionals, it could still create big data security concerns that should not be overlooked.

It’s imperative that you control the information that IT specialists are able to access when conducting data mining. While accessing age and geography demographics can help expose invaluable patterns, for instance, there’s typically no real reason to give them access to credit card information, Social Security numbers, or other confidential data. 

Anonymization can help reduce the likelihood that this big data security concern will become an issue, but remember that some tools can reverse this form of data masking. This makes it imperative for IT professionals to abide by physical security policies before accessing sensitive information. Sometimes this isn't enough.

The Cambridge Analytica breach left a data mine with droves of information vulnerable to hackers. Facebook ended up with $5 billion in fines due to the catastrophe.

8. Lack of Security Spending

Even as big data security concerns have become more apparent and hazardous over the years, spending on protecting this data hasn’t necessarily risen concurrently. Tech chiefs were expected to increase spending in this area, but average spending is still below what cybersecurity experts recommend for effective security. 

About 10 percent of a company’s IT budget should be devoted to data and cybersecurity. Breaches are occurring with greater frequency every year, and as we find new ways to fight these problems, criminals will improve their infiltration methods. If you’re not devoting the appropriate resources to combat the issues, protecting your data could become an impossible task.

9. Lack of Security Audits

Failing to complete adequate audits is one of the biggest big data security issues facing companies. These audits should take place on a regular basis in order to identify security gaps that could put a company at risk. Unfortunately, a lack of time, resources, security requirement clarity, and qualified personnel means this essential task is often put off or ignored completely. 

Security audits should be done either monthly or quarterly, depending on the size of your company, but can be done on a department-by-department basis if a company-wide audit would severely disrupt your business. Forbes recently found that data obtained during an audit could be at risk as well, so it’s imperative that this process is high-quality when it’s performed.

10. Employee Theft

Not all instances of data loss by employees are accidental. In fact, upwards of 70 percent of departing employees admit to stealing some amount of company data. Even more distressing is the reality that most intellectual property theft perpetrated by former employees occurs within three months of their resignation notice. This means your trade secrets - including client and employee lists - could be in danger. 

There are a variety of methods for reducing the likelihood that you’ll face this big data security concern. They include: 

Employees can either help alleviate big data security concerns or make them much worse. Fortunately, their ability to do damage greatly depends on how much focus you put on this issue. This was shown when an Apple employee walked out with droves of data related to their autonomous vehicle development. Had he not been caught by the FBI, the company could've lost their place in the race to self-driving vehicles.

11. Employee Negligence

Hackers and data thieves present significant risks, but the biggest cybersecurity risk faced by American businesses is employee negligence. Basic human error, such as losing a document or device, accounts for nearly half of all data breaches in the U.S.

There are a variety of ways to prevent this form of negligence: 

  • Update workplace policies: Implementing a clean desk rule along with policies focused on external vendors and remote workers. You can review a sample policy here.
  • Secure physical access: All sensitive information should be kept locked up, and paper documents need to be shredded when keeping them is no longer necessary. 
  • Proper disposal of hardware: Deleted information on hard drives can be restored, so it's essential for this hardware to be destroyed when no longer utilized. 
  • Improve communication: Create an environment where employees feel comfortable reporting lost or stolen devices. Make sure they also know exactly who to contact in these situations.

Completely eliminating big data security concerns linked to employee negligence may be a tall order, but it’s an important goal to strive for. This can minimize the potential of a simple oversight costing your firm millions. One need only look at the Equifax breach, which affected 146 million Americans. A single employee's error caused the entire debacle.

Don’t Ignore Big Data Security Concerns

Failing to understand these threats and appropriately prepare can leave your organization open to serious risks. The cost of securing your clients’ information after a breach or data loss can be significant, but the damage to your brand's image could prove incalculable. If you’re in the business of big data, make sure you take these issues seriously. Doing so could save your company. 

Connecting your data to business intelligence tools, transferring it to separate databases, and a variety of other essential business practices could put valuable information at risk. Integrate.io can help you alleviate big data security concerns and provide the extraction, transformation, and load solutions to improve your company's efficiency. Whether you need to implement an ELT or ETL solution, integrate essential data, or have access to an elastic and scalable cloud platform, we have you covered.

Contact us today and we’ll help you properly utilize your data in a safe and efficient manner.