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  1. DZone
  2. Data Engineering
  3. AI/ML
  4. How AI Is Improving Privacy in 2020

How AI Is Improving Privacy in 2020

Thomas Griffin user avatar by
Thomas Griffin
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May. 17, 20 · Opinion
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If you’re like everyone else around the world, privacy is a big deal. We regularly upload our personal information to websites when we make purchases, we also add customer information to our website as a business owner, and we want to preserve the integrity of our code data to prevent theft and abuse. 

Everyone understands how artificial intelligence and machine learning help with data-driven decisions by compiling massive amounts of information into easily digestible reports. But the real question most people are asking right now is, “how are developers using this information to improve privacy?” 

When you consider the number of IoT devices, smartphones, and internet connections worldwide, it becomes clear that privacy is the fabric that holds these connections together. For example, out of the over 194 billion phone applications, developers that don’t put privacy first will quickly fizzle out in such a saturated market. 

Today, we are going to take a look at several ways that AI is improving privacy for consumers and website developers worldwide. 

Let’s dive in! 

Quickly Resolve Exploitable Bugs 

You’re probably familiar with the harmless bugs that affect programs after launch. In many cases, these problems do not put consumer privacy at risk. However, there are ways that hackers and scammers try to steal data from your website visitors by exploiting programming bugs. 

AI and machine learning can identify issues with programming by quickly examining data and looking for anomalies. Once you create a blog or online store, you might be tempted to use a static analysis scanner to check your site for bugs. 

You should know that static analysis scanners are notorious for delivering false-positive results. Consequently, consumer data could be at risk if your scanner is targeting the wrong parameters. If someone can exploit this system, they will be able to identify and capitalize on errors, which could result in loss of privacy for your consumers and business. 

When you add AI to the mix, the process becomes more stable than ever before. Instead of tossing your static scanner aside, try using AI simultaneously so you can fine-tune the margin of error. Because AI relies heavily on our feedback, it’s crucial that you regularly check your error reports to confirm whether the flags are legitimate or false. 

The more time you have to sort through this information and improve the AI system helping your scanner, the better chance you have at reducing exploits and privacy invasions on your site. 

Prevent Formjacking 

Forms are prevalent on most websites and blogs. Developers create forms for a variety of reasons. In most cases, people create contact forms to keep in touch with their visitors or payment forms to sell products or services. 

The truth is, your on-site forms might not be as safe as you think. Since there are many ways AI can enhance the security of your website, we are going to focus specifically on how this technology can combat formjacking. 

As the name implies, formjacking is when a hacker takes control of the data that users enter in your form. Once they have this data, they can sell it to the highest bidder, or if they find enough information, use what they’ve learned to open credit cards under the name of unsuspecting consumers. 

Time is of the utmost importance if you hope to stop formjackers on your website. Adding machine learning to your website can help you protect visitors by identifying when someone is trying to take control of your forms. 

The old ways of detecting these types of scams won’t give you the immediate protection and data analysis of a machine learning-based system. Similarly, human employees are only capable of monitoring a certain number of transactions per day, while an AI system can scan a purchase for errors in a staggering 250 milliseconds. 

Protect IoT Devices 

Internet of Things (IoT) devices are more popular now than ever before. Everything from the smartwatch on your wrist, to your smart speaker, fall under the category of IoT devices. When you consider that estimates show that around 25 percent of all cyberattacks will happen to IoT devices by the end of 2020, securing these devices in our homes is paramount. 

When smart devices first hit the market, they severely lacked the protection needed to keep privacy intact. Most products featured blatant exploits with no real way to install patches or updates. Luckily, things have changed since that time, and IT professionals are implementing machine learning-based software to protect IoT devices on their network. 

The advantages of using machine learning in this capacity look positive for the privacy of consumers and the security of businesses creating these devices. For instance, AI security can prevent cryptojacking, brute force attacks, and improve IoT visibility on your network.

Back to You

As technology evolves, we expect to see revolutionary changes in the way privacy works online. However, we must remain cautious. As our tools improve, so does the sophistication and nuance of privacy-based attacks. If we keep finding new and exciting ways to use AI to fight back against hackers, the fight for privacy is a battle we can win. 

AI IoT Machine learning

Opinions expressed by DZone contributors are their own.

Related

  • AI in Edge Computing: Implementing Algorithms to Enhance Real-Time
  • Exploring Cloud-Based AI/ML Services for IoT Edge Devices
  • Harnessing the Power of MQTT for the Future of IoT
  • Using AI To Optimize IoT at the Edge

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