How to Leverage AI for Maximum Cyber Security?

How to Leverage AI for Maximum Cyber Security?

The cyber threat landscape is ever-evolving. From single actors to organized and state actors,  threats can quickly undermine simple and complex systems on a wide scale. So that we have come up with the easiest steps to leverage AI for maximum cyber security.

For example, the Solarwind hack, a supply-chain cyber attack, affected Fortune 500 companies and several US government departments. It cost the company over $18 million, and the total cost for fixing affected partners’ systems can reach $100 billion.  

The ease of conducting such a sophisticated wide-scale hack calls for advanced technologies to protect network and business assets. 

Picture this: evolving malware, increased connected business devices, and explosive sensitive data. Models by humans can easily be overwhelmed, limiting comprehensive and updated protection. 

AI is instrumental in addressing these challenges. Let’s talk about how AI maximizes cybersecurity. 

1. Quality Threat Intelligence

You need insights for offensive or defensive actions. Threat intelligence provides evidence of possible threats and vulnerabilities. But, you need quality threat data feeds to avoid raising false alarms. 

Exclusive data collection and analysis on your network, the internet, and other technical sources can get you quality threat data. Robust data scraping capable of bypassing captchas and IP blocks is vital for smooth threat data extraction. Using a residential proxy ensures successful data collection regardless of the complexity of the target. Besides this, there are some of the best network penetration providers that help you to secure your networks from simulating attacks.

Besides, it can capture structured data that is much easier to analyze. ML, a subset of AI, collects and examines extensive unstructured and structured threat data to learn about the behavior of threat actors. 

AI automates and makes the machine have human cognition. ML and AI can collect and analyze large data sets for monitoring, threat detection, and prevention. Also, they automate these processes, enhancing efficiency and accuracy unmatched by humans. 

Thus, combining residential proxy and AI improve the quality of your threat intelligence, including; 

  • Context of threat actions. 
  • Tactics involved. 
  • Threat actors’ methods.

2. Security Breach Prediction

As mentioned above, AI and ML incorporate predictive analytics and automation in cyber security operations. 

AI can identify current and future suspicious actions and threats using past and current data. AI-powered behavioral analytics can map malware signatures, associated IPs, attack methodology, affected devices, etc. 

Security teams use superior visibility to respond quickly to any malicious activity and de-escalate impact. Cybereason XDR, CrowdStrike’s Falcon, and SentinelOne XDR are examples of tools that contain layers of AI or ML for threat prediction. 

3. Addressing Bot Threats 

Bots partly inhabit the internet traffic. Bots like search engine crawlers are good bots. But, bad bots like those creating fake accounts or account takeovers can be a menace. Trickbot and Emotet botnet are good examples of bots that pose security risks.  

Using AI makes it easy to analyze vast data sets and differentiate humans, good and bad bots. It empowers your security team to keep tabs on the changing threat landscape. 

4. Eliminate Deepfakes 

Eliminate Deepfakes

Like bad bots, deepfake is part of hackers’ increasing use of AI. Deepfake is a synthetic media, image, video, or audio, altered digitally to represent a different person. Criminals use tools like Lyrebird to deep fake phone calls to commit frauds and other malicious actions.

Deepfake also has positive applications like in marketing. But, its harmful use in identity theft, financial fraud, etc., can overshadow its positive uses. 

You can train an ML model to identify deepfakes through eye-blinking behavior, voice and video anomalies. 

5. Prevention of Online Scams 

Some of the online frauds are facilitated by deepfakes and other techniques affecting online businesses, especially e-commerce. Global online payment fraud rose by about 15% to $20 billion in 2021. Most online payment providers are rising to the challenge of using AI. 

Eftpos, an Australian online payment provider, is leveraging an AI platform by Featurespace to reinforce its existing security platform. It provides a fraud scoring platform that marks and prevents fraudulent actors. 

6. Improving Cloud Applications’ Security 

Over 70% of companies have no security for data moving between their on-premise center and the cloud. As a result, organizations must update their security systems for open systems like the cloud. 

AI-powered security systems help sort and analyze several user accounts and evaluate and prevent threats. 

For example, Amazon Web Services (AWS) uses Sophos’s Cloud Optix simplified detection and response system for malicious actions across its infrastructure. The automated process provides detailed user activities, risky anomalies, and compliance events through AWS accounts. 

NTT’s Cyber Threat Sensor AI works similarly. These robust AI-powered cloud security systems have detailed visibility, capturing blind spots to avoid threat events in the cloud environment. 

7. Facilitates Smart Identity and Governance Administration 

Smart Identity and Governance Administration (IGA) is at the core of cybersecurity. But, the evolving workplace and digital transformation make it challenging to grant access to contractors and other workers at the right time. 

Integrating in-house business systems and cloud platforms challenges rigid legacy access control tools based on roles. It can increase entitlement creep that can be addressed through AI. 

AI drives flexible, autonomous, and dynamic IGA solutions for modern businesses. It streamlines and automates the various process in IGA solutions, e.g.;

  • Access reviews.
  • Access requests and approvals. 
  • Approving roles for a particular duration. 
  • Evaluate proof of adherence to policies
  • Complete visibility of granted permissions and management for security breach remediation. 

For example, the Autonomous Identity by ForgeRock can conduct a quick analysis of a company’s identity data and highlight;

  • Extremely privileged access
  • Orphaned accounts 
  • Excess granted permissions

The solution can evaluate user access behaviors and mark any suspicious user access. 

ClearSkye is another example of an IGA solution leveraging AI to enhance cybersecurity at the enterprise level. 

Also Read: Does VPN Slow Down Computer?

8. Increase Compliance With Dynamic Regulations in the Industry 

Increase Compliance With Dynamic Regulations in the Industry

Various data privacy rules govern how businesses gather, exchange, and transmit user data. As a result, every company should have additional security mechanisms to secure personal information and sensitive data while ensuring compliance.

Organizations can use AI-powered compliance technologies to monitor their enterprise and associate security posture continuously. It will ensure long-term compliance with changing regulatory requirements. 

Take Away 

The cyber security threat landscape is evolving at dizzying speeds. Hackers use AI tools like Trickbots, deepfakes, etc., to conduct sophisticated breaches. 

Fighting against such AI-powered threat actors with manual or less advanced tools is not an option. 

It is high time that AI should be integrated into your cyber security workflow. It will streamline your security architecture into a unified intelligent system that detects and prevents sophisticated attacks. 

Also, predictive analysis and increased automation through AI can free up your security team from mundane to highly technical tasks. Besides, it fills the skills gap existing in the field. 

AI reduces the burden of enterprise security, and you should embrace it too to maximize its impact.