With cyberattack incidents constantly rising, it is clear that traditional defense mechanisms cannot fight cyber threats with modern AI-powered cyber threats, both in terms of volume and scope. Similarly, advanced defense systems are required to effectively combat these sophisticated threats. This can be achieved through AI power security, which can provide much better protection against attacks. This will even predict hidden risks and prompt action to stop the attack before it triggers an attack. In short, to use bad AI, you need to protect against bad AI. In this article, we will discuss various ways that AI can help fight cybercrime and stay one step ahead of the threat actors.
How does bad AI support threat actors?
Let's start by understanding the various ways malicious elements use AI to increase the amount and impact of attacks. Understand the limitations of traditional systems and the need for AI-enabled security.
Increases the amount of attack
By adopting data science and machine learning threats, actors can easily expand the amount and range of attacks like spear phishing, including social engineering, and usually consume a lot of time. Along with collecting large amounts of target data, attackers must analyze demographic aspects and create contextual emails to gain trust. Not only can you extract huge amounts of data through ML and Data Science attackers, you can also create authentic soundmails and send them to your intended recipients.
Deepfake
Deepfake is rapidly emerging as one of the most serious AI cyber threats that can be adopted to influence human psychology and emotions, spread disguise, and mistrust or deceive audiences. Can a more advanced Deepfark compromise business emails by impersonating them as trustworthy contacts to financially fraudulent businesses? Deepfake can even mimic human voices, and attackers use more reliable platforms such as audio and video evidence to gain unauthorized access or psychologically affect victims, prompting them to take specific actions, such as transferring money or sharing sensitive information.
Misleading detection tools
Data addiction focuses on weakening its core defense mechanisms by destroying training data in advanced threat detection tools. In this attack, the threat could inject malicious and misleading data into the training data, identifying spam-looking emails as secure emails, and then send them to the primary folder in your inbox.
Continuous evolution
Unlike traditional attacks, AI attacks can automatically evolve continuously. This means that the power and scale of AI attacks continue to increase over time thanks to machine learning. Moreover, automation also helps attackers increase both the frequency and scope of their attacks.
How can AI help cybersecurity?
In the above section, we read about the various ways AI is being exploited by threat actors to carry out malicious activities. Such sophisticated attacks can easily avoid traditional security systems. However, using AI power security allows for increased defense mechanisms, making them powerful enough to combat the latest threats.
Advanced threat detection with machine learning
Using advanced AI technology, threat actors can employ sophisticated techniques that traditional firewalls and anti-malware systems cannot detect or combat. Machine learning makes defense systems smarter by monitoring and detecting anomalies in network usage patterns between staff and immediately alerting supervisors when they notice suspicious patterns.
As threat actors constantly improve their attack systems through AI, equally effective AI-enabled security is needed that can automate surveillance, detection and prevention to stop these attacks.
AI-enabled authentication
Authentication is a key gateway of security and therefore the main target of threat actors. Through Deepfake AI, attackers can infiltrate endpoints using context-based access requests and inject malicious elements. Advanced access methods such as biometric authentication can also be weakened.
To protect against this, risk-based authentication tools can be used that can detect aberrant activity via AI-powered behavioral biometrics. Deny access if necessary. Also known as adaptive intelligence, RBA is an even more sophisticated technology that allows you to assess various details such as IP addresses, locations, data sensitivity, device information, and measure risk scores, allowing/restrict access accordingly. In that ability, it helps to defend against real-time attacks.
For example, if a person who typically logs in via the office desktop on a weekday tries to log in from a business center via a smartphone on the weekend, the system will promptly flag it as a suspicious activity.
AI-powered authentication systems not only protect authentication during entries, but also function in the background, constantly analyzing user behavior throughout the session to protect against midway attacks. Therefore, if an authorized person leaves the seat without logging out and someone tries to tamper with it, the RBA security model can issue a warning when they notice differences in usage patterns (such as confidentiality settings).
Blocks AI phishing attacks
Deepfake is one of the most widely used AI technologies used in modern phishing attacks. For example, an attacker could send an email that he is impersonating as a manager, asking for a document review. In such cases, defensive AI tools can deep scan features such as flow writing, word selection, grammar, and syntax to discover suspicious differences from the usual way of the sender's communication style.
AI can also change signatures by detecting email addresses and checking email metadata. Additionally, security AI can also verify the reliability of links and images. In its capabilities, defensive AI can help defend against social engineering where traditional malware cannot be detected. Therefore, for AI-equipped phishing emails that can easily bypass traditional filters, the Defense AI employs 360-degree surveillance to ensure maximum security.
Social engineering attacks affect recipient psychology, encouraging them to gain trust and rush into action. AI can identify email patterns that the human eye may not notice. While employees working in some tasks can easily overlook the reliability of their emails, AI-powered monitoring tools can instantly detect red flags and take precautions.
Predict potential attacks with aggressive countermeasures
AI helps to build aggressive defenses against future/possible attacks before they are triggered. AI allows supervisors to gain full visibility across their network infrastructure. By automatically flagging vulnerabilities, AI allows all endpoints to be kept safe. This is currently not possible with work from home or from BYOD policy.
