Artificial intelligence is a double-edged sword, which can be used as a security solution or as a weapon by hackers. Artificial intelligence needs to develop programs and systems that can show the characteristics of human behavior. These features include the ability to adapt to specific environments or respond intelligently to situations. Artificial intelligence technology has been widely used in network security solutions, but hackers also use them to develop intelligent malware programs and perform stealth attacks.
Artificial intelligence as a security solution
Security experts have done a lot of research to take advantage of AI functions and integrate them into security solutions. AI enabled security tools and products can detect and respond to network security events with minimal human input or zero input. Facts have proved that the application of artificial intelligence in network security is very useful.
25% of it decision makers regard security as the main reason for their adoption of AI and machine learning in organizational network security. AI can not only improve the security situation, but also automate the detection and response process. This can reduce the financial and time involved in human intervention and testing.
Application of artificial intelligence in network security
Modeling user behavior
Organizations use AI to model and monitor the behavior of system users. The purpose of monitoring the interaction between the system and the user is to identify takeover attacks. These attacks are malicious employees who steal the login details of other users and use their accounts to commit different types of cyber crimes. AI will understand the user’s activities over time and treat abnormal behavior as abnormal. Whenever another user uses the account, AI enabled systems can detect abnormal activity patterns and respond by locking the user or immediately sending a change notification to the system administrator.
Application of AI in anti-virus products
Anti virus tools with AI function detect network or system abnormalities by identifying programs showing abnormal behavior. Malware programs are encoded to perform functions different from standard computer operations. AI antivirus uses machine learning strategies to learn how legitimate programs interact with the operating system. In this way, as long as malware programs are introduced into the network, AI anti-virus solutions can immediately detect them and prevent them from accessing system resources. This is different from traditional signature based antivirus programs, which scan the signature database to determine whether the program is a security threat.
Automated network and system analysis
Automatic analysis of system or network data ensures continuous monitoring to quickly identify attempted intrusions. Due to the large amount of data generated by user activities, manual analysis is almost impossible. Cyber criminals use command and control (C2) strategies to penetrate Cyber Defense without being found. Such policies include embedding data in DNS requests to bypass firewalls and IDS / IPS. AI enabled network defense utilizes anomaly detection, keyword matching and monitoring statistics. As a result, they can detect all types of network or system intrusion.
Cyber criminals prefer e-mail communication as the main delivery technology of malicious links and attachments for phishing attacks. Symantec said that 54.6% of the emails received were spam and may contain malicious attachments or links. Anti phishing e-mail with AI and machine learning functions is very effective in identifying phishing e-mail. Through in-depth inspection of links. In addition, such anti phishing tools simulate clicks on sent links to detect signs of phishing. They also apply anomaly detection technology to identify suspicious activities in all sender functions. These include attachments, links, message bodies, etc.
AI weaponization of hackers
Hackers are turning to AI and using it to provide weapons for malware and attacks in response to advances in network security solutions. For example, criminals use AI to hide malicious code in benign applications. They program the code to execute at a specific time (for example, ten months after the application is installed) or when a target number of users subscribe to the application. This is to maximize the impact of such attacks. Hiding such code and information requires the application of AI model and derivation of private key to control the time and place of malware execution.
Nevertheless, hackers can predefine application functions as AI triggers to perform network attacks. Functions range from the authentication process through voice or visual recognition to identity management functions. Most applications used today contain such functions, which provides ample opportunities for attackers to provide weaponized AI models, derive keys and attack at will. When applications are most vulnerable, hackers wait for strikes, and malicious models may exist for years without being discovered.
In addition, the uniqueness of artificial intelligence technology is that they can acquire knowledge and intelligence to adapt accordingly. Hackers are aware of these features and use them to model adaptable attacks and create intelligent malware programs. Therefore, in the process of attack, the program can collect the knowledge to prevent the success of the attack and retain the proven useful knowledge. AI based attacks may not succeed in one attempt, but adaptability can enable hackers to successfully carry out subsequent attacks. Therefore, the security community needs to have an in-depth understanding of the technologies used to develop AI driven attacks to create effective mitigation and control measures.
In addition, network attackers use AI to perform intelligent attacks, which will spread themselves through the system or network. Intelligent malware can exploit unreleased vulnerabilities, increasing the possibility of completely destroyed targets. If an intelligent attack encounters a fixed vulnerability, it will immediately adapt to try to destroy the system through different types of attacks.
Finally, hackers use AI technology to create malware that can mimic trusted system components. This is to improve stealth attacks. For example, network participants use AI enabled malware programs to automatically understand the organization’s computing environment, patch update life cycle, preferred communication protocols, and the time when the system is least protected. Subsequently, hackers can perform undetectable attacks when integrated with the organization’s security environment. For example, taskrabbit was hacked and threatened 3.75 million users, but the investigation could not track the attack. Secret attacks are very dangerous because hackers can invade and leave the system at will. Artificial intelligence encourages such attacks, and this technology will only lead to the creation of faster and smarter attacks.