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The development of digital technologies, including artificial intelligence (AI) and machine learning (ML), has given hackers new opportunities and methods to hack websites, steal content, and commit advertising fraud. In 2018, the damage from fraud amounted to $19 billion, and by 2028, according to experts, it will increase to $172 billion.
Automated AI bots controlled by fraudsters attack websites, bypass filters of advertising systems and other security tools that are not designed to detect “complex” bots. They disrupt the stability of the business processes of the attacked companies: they spoil metrics, cause pessimization of websites, spend the advertising budget, reduce conversion and increase the cost of achieving the goal.
In this article, we will tell you how to protect your website or advertising campaign from bot attacks using AI systems.
Contents
1. How scammers use bots to attack advertising
1.1. Types of bot attacks
1.2. Signs of a bot attack
1.3. How to identify a bot attack and protect yourself from it
2. What is bot management
3. How bot management works
Attackers use bots to manipulate data, steal it and use it for fraudulent purposes, inflate metrics and traffic. Unfortunately, such attacks are already becoming the norm for companies of all sizes.
Bots are automated programs used to commit fraudulent actions or disrupt networks. For example, malicious bots can be used to distribute viruses, worms, Trojans, steal personal and banking data, generate fake traffic, send spam, boost likes and reposts, and attack competitors' websites. To carry out large-scale attacks (DDoS, phishing, brute force attacks, etc.), fraudsters usually use botnets, i.e. entire networks of bots.
For example, attackers create bots to delete data from websites or send spam in comments, letters, and social networks. This annoys both regular users and website owners. Fraudulent actions worsen the user experience when interacting with advertising or a website.
The most common bot attacks are phishing and spamming. They allow you to automate processes associated with fraud. Botnets can send spam via email, click on ads, generate malicious traffic, DDoS sites, and steal personal, confidential, and corporate data.
The most common form of bot fraud is DDoS attacks, in which attackers use botnets. They overload a network or server with artificially generated traffic, causing a website or application to crash.
These voracious and fast automated scripts consume server bandwidth and affect the performance of the site. All this can negatively affect the company's income, spoil the performance of the site or advertising, and even damage the reputation.
Behavioral analysis and device or browser fingerprinting can be used to detect bot attacks. This method allows analyzing unique metrics of a site visitor and distinguishing between a human and a bot. Bot protection systems can also initiate additional actions to verify users, such as multi-factor authentication to prevent further bot attacks.
For example, to protect a site from fake applications, you can use Smart Captcha , which blocks bots from accessing forms and buttons on the site. If the visit is suspicious, deviating from the norm, signaling bot behavior, then such a visitor will be shown a captcha. An ordinary user will not see it. The tool uses machine learning to accumulate a database of technical and behavioral patterns of malicious actions.
Bot management allows companies to detect malicious activity, identify its source, and block invalid visits while leaving useful bots untouched.
Bot traffic management is useful in combating automated attacks such as click fraud on ads, generating fake site requests, inflating traffic and views, taking over accounts, stealing content, and more.
Cybersecurity systems that use AI can reduce business risks associated with fraudulent attacks and can become a key component of a defense strategy.
Anti-bot solutions monitor incoming traffic to a website, app, social network, or API to detect and block malicious activity. These solutions are a combination of a number of tools and technologies that help companies distinguish malicious bots from legitimate users. These include artificial intelligence, machine learning, data analytics, behavioral biometrics, device fingerprinting, and many other methods.
Advertising and website cybersecurity systems currently use three approaches to detect and stop bot attacks:
Depending on the level of threat they face, companies use one or a combination of the above approaches.
Automated AI bots controlled by fraudsters attack websites, bypass filters of advertising systems and other security tools that are not designed to detect “complex” bots. They disrupt the stability of the business processes of the attacked companies: they spoil metrics, cause pessimization of websites, spend the advertising budget, reduce conversion and increase the cost of achieving the goal.
In this article, we will tell you how to protect your website or advertising campaign from bot attacks using AI systems.
Contents
1. How scammers use bots to attack advertising
1.1. Types of bot attacks
1.2. Signs of a bot attack
1.3. How to identify a bot attack and protect yourself from it
2. What is bot management
3. How bot management works
How Scammers Use Bots to Attack Ads
Bot attacks pose a serious threat to websites, applications, advertising campaigns, including social networks. They are automated and vary in frequency, duration, complexity and scale.Attackers use bots to manipulate data, steal it and use it for fraudulent purposes, inflate metrics and traffic. Unfortunately, such attacks are already becoming the norm for companies of all sizes.
Bots are automated programs used to commit fraudulent actions or disrupt networks. For example, malicious bots can be used to distribute viruses, worms, Trojans, steal personal and banking data, generate fake traffic, send spam, boost likes and reposts, and attack competitors' websites. To carry out large-scale attacks (DDoS, phishing, brute force attacks, etc.), fraudsters usually use botnets, i.e. entire networks of bots.
Types of Bot Attacks
Attacks have become more sophisticated and complex. Bots can imitate the behavior of real users, causing harm to online systems. Bots are versatile and can perform various malicious actions under the control of bot operators, who are constantly improving their fraud tactics.For example, attackers create bots to delete data from websites or send spam in comments, letters, and social networks. This annoys both regular users and website owners. Fraudulent actions worsen the user experience when interacting with advertising or a website.
The most common bot attacks are phishing and spamming. They allow you to automate processes associated with fraud. Botnets can send spam via email, click on ads, generate malicious traffic, DDoS sites, and steal personal, confidential, and corporate data.
The most common form of bot fraud is DDoS attacks, in which attackers use botnets. They overload a network or server with artificially generated traffic, causing a website or application to crash.
Signs of a bot attack
The most obvious sign of a bot or botnet attack: an abnormal number of clicks on ads, ad views, site visits, as well as a high bounce rate and minimal session duration. If you see suspicious traffic statistics, be sure that bots have worked for this.These voracious and fast automated scripts consume server bandwidth and affect the performance of the site. All this can negatively affect the company's income, spoil the performance of the site or advertising, and even damage the reputation.
How to identify a bot attack and protect yourself from it
Protecting against bot attacks requires understanding how malicious bots operate and taking steps to detect and block them in real time. Bot attacks can be difficult to detect, and security teams may not realize they are under attack until it is too late.Behavioral analysis and device or browser fingerprinting can be used to detect bot attacks. This method allows analyzing unique metrics of a site visitor and distinguishing between a human and a bot. Bot protection systems can also initiate additional actions to verify users, such as multi-factor authentication to prevent further bot attacks.
For example, to protect a site from fake applications, you can use Smart Captcha , which blocks bots from accessing forms and buttons on the site. If the visit is suspicious, deviating from the norm, signaling bot behavior, then such a visitor will be shown a captcha. An ordinary user will not see it. The tool uses machine learning to accumulate a database of technical and behavioral patterns of malicious actions.
What is bot management
To manage bot traffic, advertisers can use AI tools and strategies to protect ads, websites, and apps from malicious attacks. One of them is to implement a bot management system that uses machine learning or artificial intelligence to detect and prevent malicious traffic.Bot management allows companies to detect malicious activity, identify its source, and block invalid visits while leaving useful bots untouched.
Bot traffic management is useful in combating automated attacks such as click fraud on ads, generating fake site requests, inflating traffic and views, taking over accounts, stealing content, and more.
How Bot Management Works
Over the years, marketing and cybersecurity experts have developed a number of solutions to manage bot traffic. They help companies, website owners, and advertisers filter out useful and invalid visits. The solutions use a variety of technologies, including machine learning, artificial intelligence, and big data.Cybersecurity systems that use AI can reduce business risks associated with fraudulent attacks and can become a key component of a defense strategy.
Anti-bot solutions monitor incoming traffic to a website, app, social network, or API to detect and block malicious activity. These solutions are a combination of a number of tools and technologies that help companies distinguish malicious bots from legitimate users. These include artificial intelligence, machine learning, data analytics, behavioral biometrics, device fingerprinting, and many other methods.
Advertising and website cybersecurity systems currently use three approaches to detect and stop bot attacks:
- static;
- based on constructing tasks in response to user actions;
- behavioral;
Depending on the level of threat they face, companies use one or a combination of the above approaches.
