AI can help identify threats, direct incident response, and distinguish malware attacks before they cause harm.Learn how AI can help with cybersecurity.

1. How AI can help with
cybersecurity
With the digitalization of everything, cybersecurityis becoming
increasingly vulnerable. The problem forevery IT professionalis
preventing these cyberattacks and fraudulent activities while saving
money on an annual basis. Taking the necessaryprecautions and
detecting such risks are required to prevent these types of cyber threats.
That is where AI comes in and simplifies the time-consuming processes
of data analysis, data screening,and risk detection.
The use of Artificial Intelligence in cybersecurity is growing, and many
businesses are incorporating it as a key tool in their cybersecurity
strategies.Every day, there are 4,000 new cyberattacks. A ransomware
attack occurs every 14 seconds,causing devastating financial losses to
companies,while 560,000 new pieces of malware are detected every
day. Because of the growing number of cyber threats and the scarcity of
skilled cybersecurityprofessionals,AI in cybersecurityis becoming
increasingly important. Continue reading to find out how artificial
intelligence can help with cybersecurity.
The Use Of AI in Cybersecurity
The use of Artificial Intelligence (AI) in cybersecurity has shown great
promise in identifying, detecting,and preventing security breaches.
● Known and Unknown ThreatDetection:
AI-based solutions use machine learning algorithms to detectand
respond to known and unknown threats. Traditional antivirus software

2. may miss some known and unknown malware variants, but AI can
identify this type of malware behavior and analyze it.
AI can assist security teams in monitoring, detecting,preventing,
mitigating threats, and managing their workload. Such tools use
sophisticated algorithms and predictive intelligence to hunt down
malware, run pattern recognition, and detectand thwart attacks that are
difficultfor humans to detectbefore they cause harm. They also keep
the team updated on new anomalies, attacks, and prevention methods.
● Securitylog Analysis:
Security log analysis is the process of reviewing system-generatedevent
logs to proactively identify bugs, security threats, or other risks. Rule-
based systems are limited in their ability to identify new and emerging
threats in traditional security log analysis. Machine learning algorithms
are used in AI and cybersecurity-basedlog analysis to analyze large
volumes of data in real time.
Security log analysis can also be used to ensure regulatory compliance
or examine user behaviour. It helps to extract data from logs and find
trends and patterns to guide business decisions,investigations,and
general security.
● Network security
Now, every organization wants to provide services to their customers,
and employees expectthat they must secure their network security. It
helps protect proprietary information from attack. This is why AI
algorithms can be trained to detectdevices that are not authorized to be
on a network, identify suspicious activity, and identify unusual traffic
patterns.
Anomaly detectioncan help AI in cybersecurityimprove network
security. This involves analyzing network traffic to identify anomalous

3. patterns. An AI algorithm can learn what traffic patterns are normal for a
particular network and identify anomalous or suspicious traffic based on
historical traffic data. It can include traffic from suspicious IP addresses,
unusual port usage, or unusual protocolusage.
● Endpoint security
Most cybercriminals target endpoints, such as laptops and smartphones.
Increasingly malicious and automated cyber activity targets endpoints,
leaving organizations that rely on traditional endpoint security
approaches vulnerable to attackers who exploit zero-day vulnerabilities
and launch ransomware attacks.
Traditional antivirus software relies on signature-based detection,which
can only detectknown malware variants. AI can analyze the behavior of
malware and detectunknown malware variants. Endpoint security
solutions based on artificial intelligence can detectand prevent
unauthorized access to sensitive data. The ability of AI-based endpoint
security solutions to adapt and evolve over time is a key advantage.
Closing Thoughts
In recent years, the increasing use of AI in cybersecurityhas presented
a transformative opportunity to improve the effectivenessand efficiency
of security measures. AI can provide much-needed analysis and threat
identification that cybersecurity professionals can use to reduce breach
risk and improve their security posture. In security, AI can identify known
and unknown threats, perform log analysis, perform network security,
and perform endpoint security. Cybersecurity teams can leverage AI to
create powerful human-machine partnerships that enrich our lives, push
the boundaries of our knowledge,and enhance cybersecurity in a way
that seems greater than its parts.