Artificial Intelligence Can Reduce Cyber Attacks
Cyber attacks are commonly viewed as one of the most severe risks to worldwide security and defense methods have evolved greatly over the past five years. Today, businesses can use Artificial Intelligence (AI) to implement automated security solutions in their systems to protect both online & offline security.
It is, however, a double edged sword. Although AI is an effective solution to protect organisations from cyber attacks, it can also be used by hackers to launch complex, automated attacks.
Since the onset of the coronavirus pandemic, the remote work culture and rapid adoption of cloud computing have encouraged hackers to come up with innovative solutions to break into online networks. One of the most intriguing ways that attackers are using AI is to simulate user behavior. If they can hide “in the noise” and make their activities appear to be regular user activity, this can help them avoid detection.
Cyber security experts re researching ways to use AI to combat these threats. Attempts are being made to integrate AI into existing security systems as AI has the ability to identify and predict security threats. AI-based attacks can help profile and simulate legitimate user activity to camouflage attacks from traditional cyber security tools.
- According to a report by MIT Technology Review, in association with Darktrace, “Offensive AI risks and developments in the cyber threat landscape are redefining enterprise security as humans already struggle to keep pace with advanced attacks.”
- According to a report by Capgemini Research Institute, 69% of organisations agree that AI is crucial for security as traditional methods are unable to curb the issue.
- According to a Forrester survey, 88% of cyber security experts believe that AI-powered attacks will grow in the coming years.
AI can identify suspicious activities throughout a company’s technology and its user tasks. To safeguard various software, AI-powered antivirus software can detect network anomalies. When a malicious software is launched in a network, AI antivirus software can detect it and prevent assets from exploitation.
AI has the capability to assess the behavior of network users. When a new user logs in, AI abilities can identify fraudulent activities and can disable the user, and notify the administrator.
While conventional management techniques take time to address elevated loopholes, they are essential for managing and controlling identified vulnerabilities. AI methods like User and Event Behavioral Analytics can analyze baseline behavior of the servers and help these traditional techniques strengthen the security.
- Traditional network security methods take time to develop cybersecurity policies based on an organisation’s network topology. For this, using AI to understand network traffic behavior will enhance network security. AI’s analytical and monitoring skills can enhance the efficiency of the infrastructure, and lower the price of system maintenance.
- Furthermore, traditional security methods depend on indicators of vulnerability to identify attacks. While this approach works against known attacking agents, it is ineffective against new attacks. Combining AI with existing traditional methods will improve the tracking rate and give an added advantage.
The proliferation of AI systems in critical sectors, including financial services, law enforcement and healthcare demonstrate just how important it is for policymakers to take seriously the security of these systems.
In today’s environment it’s not just about using automation to fight machines with machines; it’s about using the right tools and technologies to fight intelligence with intelligence.
The richer and more sophisticated the data you have, the more you will need to rely on AI to strengthen your defenses. But keep in mind your adversaries are doing the same, so it’s smart to always stay at least one step ahead.
Anayltics Insight: AT&T: AIMultiple: SSL Store: Brookings: ITProPortal:
Security Roundtable: MIT Technology Review:
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