Analyzing 2019 Trends of Artificial Intelligence in Cybersecurity

Sanam Malhotra | 30th October 2019

The wave of artificial intelligence has accelerated the efficiency and productivity of several legacy businesses. The application of artificial intelligence in cybersecurity is enabling organizations to detect malware and operational risks with greater accuracy. Leading businesses are significantly reducing fraud detection costs by using AI’s underlying technologies such as machine learning, deep learning, and computer vision services.

Let’s review the latest developments and advancements in cybersecurity with artificial intelligence.

 

Significance of Artificial Intelligence in Cybersecurity

The rapid proliferation of online business and consumer data is compelling organizations to level up their cybersecurity efforts consistently. It is challenging for cyber analysts to monitor large data volumes, velocity, and variety across firewalls.

According to Capgemini’s Reinventing Cybersecurity with Artificial Intelligence Report, around 23% of senior IT executives are unable to successfully track anomalies and breaches. It leads to an increased number of severe cyber attacks and more incidents of data breaches.

artificial intelligence for cybersecurity

The data analyzing capabilities of AI can serve as an antidote to the current state of cybersecurity in the following ways-

1) Machine Learning to Handle Data Explosion

The machine learning (ML) capabilities of AI are effective at analyzing and extracting valuable insights from unstructured and unlabeled datasets. Well-trained ML models enable businesses to detect, prevent, and respond to cyber threats in a more time and cost-effective manner than analysts.

2) Predictive Engines to Anticipate Threats

Businesses using the advanced Internet of Things (IoT) devices can now access and use large amounts of user data including behavioral insights. The ML algorithms can predict critical vulnerabilities by analyzing anomalies in user behavior based on their roles, past activities, and more. Moreso, Capgemini’s Report records that 51% of executives are already using AI for cyber threat detection, prediction, and response.

Related- How Machine Learning Is Improving Business Processes

 

How Artificial Intelligence is Strengthening Cybersecurity Systems?

1) Event monitoring and incident response

Manual intervention in traditional cybersecurity practices such as backup scheduling and setting up firewall policies hamper business efficiency. To combat this challenge, businesses are now turning to AI-powered firewalls with machine learning capabilities. It enables the software to recognize network behavior and patterns in web requests to automatically block and prevent cyber threats.

Also, AI-based cybersecurity technology can accelerate incident detection by collecting accurate data, correlating, and triggering high-volume security alerts. The incident-response capabilities of AI include improving business operations, prioritizing the right incidents, and automating remedial actions.

 

2) Adaptive authentication

Password-protected applications and business assets are the most vulnerable to cyber-attacks. Poor password protection under identity and access management has led organizations to invest in AI-based password-less systems. It involves technologies such as facial recognition and voice-based surveillance systems at critical entry-points and unauthorized areas. 

The predictive analytics services under AI can be deployed for user authentication to collect and identify patterns in log-in ties, locations, and device footprints. It enables AI systems to detect abnormal user behavior and change access controls accordingly.

 

3) Phishing Detection And Prevention Control

Phishing emails are one of the most prevalent cyber-attacks that cause businesses and individuals considerable losses. Practices including spear phishing, whaling, business email compromise, have long been circulated in the name of renowned companies to exploit customers.

Businesses can now deploy AI to identify diverse combinations of forwarding addresses, payload data, and suspicious text or graphics across emails. Also, the data-analyzing capabilities of AI detect malicious email content before it is downloaded by employees. It can enable businesses to save a significant volume of data and assets lost due to poor antivirus protection.

Also Read- Improving Industrial Processes with Machine Learning

 

Oodles Artificial Intelligence Services for Cybersecurity

We, at Oodles AI, build advanced AI solutions with machine learning capabilities that analyze and extract meaningful insights from historical datasets. We have experiential knowledge in applying natural language processing, predictive engines, and computer vision services for threat detection, prevention, and response.  Our AI team matches your business objectives with function-specific ML models that strengthen the cybersecurity efforts of global businesses.

Talk to our AI development team to know more about our artificial intelligence services.

 

About Author

Sanam Malhotra

Sanam is a technical writer at Oodles who is currently covering Artificial Intelligence and its underlying disruptive technologies. Fascinated by the transformative potential of AI, Sanam explores how global businesses can harness AI-powered growth. Her writings aim at contributing the multidimensional values of AI, IoT, and machine learning to the digital landscape.

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