The online robot (or bot for short) is a piece of automatable and adjustable software that performs programmed tasks on the internet. With scripts of various complexities, a bot interacts with other websites, often without exposing the identity of its owner.
By speeding up monotonous tasks, bots accelerate processes where humans are too inefficient. In 2023, the internet is buzzing with automated robots, as their flexibility and application are too good to miss out on, even for the average web user.
All things considered, there is an elephant in the room: a toxic element that gives all bots a negative reputation. Because they are easy to set up, internet bots have a negative reputation that overshadows their positive use cases. Anyone can find a tutorial on how to write primitive scripts that wreak havoc on the web.
Internet bots are mostly known for spreading misinformation, propaganda, links to malware, and other similar activities. Without much trouble, third parties write a simple script that adds a comment. While one comment may seem insignificant, most owners multiply their bots, where hundreds or thousands of parallel instances transmit negative messages and malicious software.
Still, to counteract negative bot effects on social media networks and other important platforms, website owners use constantly improving technology to identify and block bot connections. The most popular emerging solutions utilize the growing power of Artificial Intelligence (AI). Their goal is to train computers to detect the difference between automated bots and organic user behavior.
While the capabilities of AI keep growing, the best bot developers do not sit idle, constantly searching for effective workarounds. Some protect their army of robots with internet privacy tools. For example, by routing bot connections through an antidetect browser, third parties avoid many red flags that are giveaways of a bot connection.
In more complex use cases, such as web scraping, an antidetect browser may not be as effective as, for example, a residential proxy network. For more technical information, check out Smartproxy – one of the best suppliers of proxy servers and digital privacy solutions.
In this article, our goal is to discuss the current capabilities of AI for bot detection. We will address the most common strategies to detect bots and instances where trained machines fail to detect inorganic web traffic.
The Power of AI: How a Computer Learns to Detect Bots
While computers are less effective than humans for multitasking, AI teaches itself to perform specific tasks with extreme precision with the help of Machine Learning (ML).
To separate real users from scripted behavior, AI has to go through tons of material to learn unique traits and patterns that separate authentic human actions from imitation. With enough information, AI can detect bots with decent accuracy by using these techniques:
Device Fingerprinting
Instead of focusing on complex patterns within the posted content and transmitted actions, platforms that forbid bots begin detection through analysis of incoming connection requests. Their most informative and revealing parameters are user agents and IP addresses.
User-Agents
A user-agent is a text containing versions of your browser and operating system. Websites use this information to redirect browsers incompatible with the web page format. Instead, they load an older fallback version to make the site accessible to all users. In some cases, the user agent contains your browser’s resolution and screen size.
AI-based detection systems can easily identify inexperienced bot users because they have a different user agent. A suspicious operating system version is another red flag that could warn about incoming bot traffic.
Still, relying solely on user-agent monitoring is a bad idea. The web is full of tools and extensions that let bot users alter this information.
IP Addresses
The IP address is a unique identifier that acts as a public identity for your web traffic. The site’s defensive mechanisms may track the IPs of previous offenders or reveal bots that route their connection through proxy servers. AI checks which incoming addresses are not associated with internet service providers (ISP) and monitors them closely to detect suspicious activity.
Catching bots based on their IP address is rarely effective because tech-savvy owners use more secretive residential proxies to mimic organic web traffic.
AI Detection Flaws
While AI can provide good help by tracking more obvious metrics, a lack of big, informative, and comprehensive data sets creates inaccuracies and subjectivity in its decision-making. Without an information source that describes a normal distribution of common robot behavior, bot developers can manipulate AI’s lack of objectivity and appeal to its biases to avoid detection.
Conclusion
While advancements in AI technology are certainly impressive, training a model that could accurately detect a constantly changing bot behavior is not yet possible. The process has too many complex parameters that can differ greatly depending on the developer. AI is getting better every day, and with enough data, it might detect all bots in the future, but we’re far from it yet.
