How data poisoning is used to trick fraud detection algorithms on ecommerce sites

June 21, 2021 | Theodoros Karasavvas

This blog was written by an independent guest blogger.

Artificial intelligence (AI) and machine learning (ML) systems have become the norm for using client data to provide recommendations to customers. As more people are working from home and conducting business online, it is imperative that fraud detection software is used to protect user information. But these protective systems also utilize ML to automate the process and understand when a potential attack is taking place. 

Unfortunately, all systems that utilize ML could be subjected to a data poisoning attack. Most of the time, a data poisoning attack will end up having a greater effect on online businesses and ecommerce sites because companies are commonly unaware of the malicious software’s existence in the first place. This means it is important for all users to be aware of what data poisoning is and how to protect personal data from attacks that may be difficult to detect.  

What is data poisoning?

ML algorithms rely on data to teach them what to look for and how to respond in different situations. The algorithm “learns” based on past information and then generates future decisions accordingly. Online businesses have become increasingly reliant on data generated in this manner for their marketing and customer outreach, to the point that a majority of online business owners have cited data collection and utilization as their single most important priority. 

Data privacy protection is absolutely essential for online businesses using customer information for their analytics and algorithms. One of the biggest threats to customer data privacy, however, is data poisoning. 

Data poisoning is a type of cyber-attack that causes an algorithm to produce improper results for the data that it reads. In essence, these attacks change the way that algorithms read and react to data inputs, tricking them into generating incorrect results. This can cause business operations to become slow or unproductive, but it can also cause significant financial repercussions to a company as well. 

For one thing, it could cause a consumer data breach, reducing trust in the company from existing customers. But it could also result in a big price tag. The cost for retraining an algorithm is very high, so even if the attack is detected, it could ruin a business trying to fix the issue. For these reasons, it is critical that businesses learn how to prevent data poisoning attacks. 

Fraud protection

Making decisions concerning your technology can be stressful, but making the right cybersecurity choices is key to protecting yourself from fraud. Ecommerce companies use many vendors and products to collect, process, and analyze user data, and each of those vendors could have different privacy terms. 

If these outside companies are using AI to provide their services (which they most likely are), you need to be cognizant of their efforts towards data privacy in ML in addition to your own.

When a user agrees to work with an online company, they may also be agreeing to share their data with the other businesses that support that company. If a data poisoning attack takes place in one of those, the attack could potentially go undetected and data could easily be used for malicious purposes. 

Humans lean towards creating communities and sharing information, so using social media and allowing companies to use our data to provide personalized experiences feels like a natural part of the digital era despite the risks involved. But there is a lot of controversy that surrounds data ownership and whether or not data can truly be protected. 

For example, most people are very wary of how major social media outlets such as Facebook or Instagram handle their data, and yet willingly share their personal information and photos on those outlets anyway. Granted, most social media sites have fraud detection systems in place already, but these systems often utilize ML as a way of automating the detection software. A data poisoning attack can even penetrate high quality detection software itself by tampering with the ML’s training data.

As long as consumers continue to use the internet and take advantage of algorithms to have a better online experience, there must be more of a focus on fraud protection. For users, there are a number of programs and apps available for areas of security you may not be thinking about. For example, you should prioritize mobile phone security since you are likely accessing the internet on your phone daily.

Not only should users be more aware of when and how they share their data, but companies that collect personal data need to be more aware of the effects of data poisoning and how to protect fraud from occurring. In general, both users and companies that operate online need to consistently check the privacy terms that they agree to. 

The future of data protection

Ecommerce sites use numerous innovative marketing strategies to differentiate themselves from the competition, and they will surely continue to do so. Unfortunately, this means even more avenues for bad actors to try to exploit businesses.   

ML has become deeply embedded in social and economic infrastructure, and it is only going to become more integral moving forward. The decisions that AI makes must be based on reliable data. If not, it can quickly become skewed and spread false information like what we’ve seen on social media outlets over the past couple of years. 

As data protection becomes more advanced, there is hope that data poisoning will become easier to detect and mitigate. But this won’t be possible without companies and users making an active effort to understand and prevent these attacks. Businesses who are more recently learning about data poisoning can look to existing strategies other companies use to detect fraud. 

For example, there have been significant developments in user privacy when it comes to financial technology, and these developments are expected to become stronger and more personalized as we learn more about ML and AI security. 

Conclusion

Keeping personal data secure is crucial to maintaining the integrity of the companies that utilize this information for entertainment, sales, and other purposes. But an otherwise successful data security approach can be rendered useless if a data poisoning attack causes it to misread threats. Due to this, it is important to choose a network protection service that offers a variety of security solutions to best protect personal information online. 

What’s more, the majority of data responsibility lies in the hands of everyday people who use online services for banking, communication, storing information, and working from home. Take steps today to secure yourself or your ecommerce business against data poisoning attacks.

Theodoros Karasavvas

About the Author: Theodoros Karasavvas

Theodoros ‘Theo’ Karasavvas is a freelance writer based out of Corinth, Greece. He has written for Ars Technica, American Express, Gizmodo, Gold Visa Japan, Mental Floss, and Ancient Origins, among others. He has a Master of Studies in Law from the University of Athens and speaks four languages. He specializes in writing about history, current events, tech trends, and privacy technology.

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