Nowadays, the threat of online fraud is real and widespread. Millions of people around the world become victims of cybercrime every day. As humans increasingly rely on digital technology for information exchange, this number will only increase.
The adoption of Internet of Things (IoT) technology may complicate network fraud, but it can also become part of the solution. The versatility of the Internet of Things helps fraud detection programs. Here is how to implement it to fully utilize network security.
Internet of Things and Network Security
Like all emerging digital technologies, the Internet of Things also has many advantages and disadvantages. Devices connected to the Internet of Things network may be vulnerable to malicious software attacks, depending on their security level, thereby endangering the entire system.
In addition, without strong encryption protection, the connections between devices are also vulnerable to network attacks. As the name suggests, all data in the Internet of Things network must pass through the internet. Hackers can use this traffic to hijack systems.
Therefore, the network security of the Internet of Things network must be very comprehensive. An end-to-end security framework is necessary to protect connecting devices and the connection itself.
Multiple authentication, firewall layer, and data encryption are crucial for protecting IoT networks. However, connecting multiple devices and functions can also enhance other security mechanisms.
How to Strengthen Fraud Detection in the Internet of Things
Application of Artificial Intelligence in Fraud Detection Projects
Artificial intelligence (AI) and machine learning programs are the most powerful weapons in combating digital fraud. Software can detect illegal and high-risk online activities by monitoring user behavior and calculating the probability of transactions being fraudulent.
Artificial intelligence and machine learning programs can analyze online activities and predict whether these activities come from hackers attempting to commit fraud based on user behavior. They perform Real-time computing to identify possible theft while protecting sensitive information.
One of the main reasons why enterprises become victims of fraud is that most typical prevention methods are mutually exclusive among different departments of the enterprise. Each department is responsible for monitoring their own data, and there are no standards applicable to the entire enterprise.
This method has been effective in the past, but network attackers use more complex programs to locate and exploit vulnerabilities. Some enterprises may have more network security vulnerabilities than others, leading to Data breach.
This is particularly destructive for financial institutions. As online banking has become the preferred way for people to manage their finances, the opportunity for Data breach has become more common. Isolated network security methods are not sufficient to protect each customer's data.
How the Internet of Things Can Help
The Internet of Things can enhance the ability of fraud detection programs by promoting interconnectivity between them. Connecting to multiple devices and data streams simultaneously can provide more data for artificial intelligence and machine learning programs for more comprehensive analysis.
In addition, the Internet of Things can enable multiple fraud detection programs to work together to create a mutually constructed network for more comprehensive security. Machine learning programs can even use the "honeycomb thinking" method to design this type of collaboration.
The fraud detection program connecting enterprises can give them an advantage in resisting network attackers