Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics in ecommerce
    Analytics Technology Drives Conversions for Your eCommerce Site
    5 Min Read
    CRM Analytics
    CRM Analytics Helps Content Creators Develop an Edge in a Saturated Market
    5 Min Read
    data analytics and commerce media
    Leveraging Commerce Media & Data Analytics in Ecommerce
    8 Min Read
    big data in healthcare
    Leveraging Big Data and Analytics to Enhance Patient-Centered Care
    5 Min Read
    instagram visibility
    Data Analytics Plays a Key Role in Improving Instagram Visibility
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: Can ML Fix Cybersecurity Challenges in Healthcare?
Share
Notification Show More
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > IT > Security > Can ML Fix Cybersecurity Challenges in Healthcare?
ExclusiveITMachine LearningSecurity

Can ML Fix Cybersecurity Challenges in Healthcare?

Machine learning technology may be the most important line of defense against cyberattacks in the healthcare sector.

Matt James
Last updated: August 16, 2022 8:31 pm
Matt James
9 Min Read
benefits of machine learning in cybersecurity for healthcare organizations
Shutterstock Photo License - lumerb
SHARE

The Department of Health and Human Services HIPAA Breach Reporting Tool shows that there were over 700 data breaches in healthcare organizations last year. Healthcare organizations need to utilize the latest technology to stop these attacks. Machine learning technology is especially important.

Contents
Machine Learning Helps Healthcare Organizations Fight CyberattacksThe State of Cybersecurity in HealthcareTypes of Healthcare Cyber AttacksPhishing AttacksRansomware AttacksDenial-of-Service AttacksInsider ThreatsBest Practices and Strategies Preventing Cyber Attacks with Machine LearningEducate Employees about CybersecurityImplement Strong Security MeasuresRegularly Back up DataMonitor Networks 24/7Machine Learning is Vital to Protect Healthcare Organizations Against Cyberattacks

Machine Learning Helps Healthcare Organizations Fight Cyberattacks

Machine learning technology is a double-edged sword in many facets of our lives. One of the biggest examples is with cybersecurity.

A growing number of cybersecurity professionals can use machine learning technology to fortify their defenses against cyberattacks. On the other hand, many hackers are also using machine learning to conduct more insidious attacks with each passing day.

The harsh reality is that organizations that don’t use machine learning to improve their cybersecurity strategies will be sitting ducks against tech-savvy hackers. Their strategies will be less effective with each passing day as hackers find more heinous ways to utilize AI technology to conduct vicious attacks.

More Read

data warehouse

Data Warehousing: Lessons We Have Failed to Learn

Beware of Big Data Technology Zealotry
Can Fossil Analysis Software Help Us Plan Curriculum?
Cybersecurity Gaps Across Government, New Monitoring Tool, and More
5 Ingenious Big Data Strategies To Skyrocket Email Marketing Conversions

Healthcare organizations will be some of the most vulnerable. They will have to find approaches to cybersecurity that make the most of advances in machine learning.

The State of Cybersecurity in Healthcare

It’s no secret that, in recent years, cybersecurity has been an important topic – especially in the healthcare industry. Namely, healthcare has been one of the biggest targets of cyber-attacks. This is because healthcare organizations hold important data that could be very easily exploited. In most cases, the main target of cyber attackers in healthcare has been patients’ information, like credit and bank account numbers, social security numbers, and personal data related to their medical state.

In order to protect patients and their data, healthcare organizations must implement strong security measures. This way, they can ensure that only authorized personnel have access to patient data and that all data is appropriately encrypted.

There are many ways to protect a healthcare organization, yet not enough organizations take the necessary measures to do so. We will discuss all about cybersecurity in healthcare in our article below. Continue reading to learn more about cybersecurity in healthcare, the different types of cyber-attacks, and how to protect your healthcare organization successfully.

Types of Healthcare Cyber Attacks

There are many different types of cyber-attacks that healthcare organizations can fall victim to. In general, these attacks can be categorized into four main types:

Phishing Attacks

One of the most common types of cyber-attacks is phishing. This type of attack usually consists of a malicious email being sent to an employee of a healthcare organization. In the vast majority of cases, the email looks like it’s from a legitimate source, but it actually contains malware that, once downloaded, can give the attacker access to the organization’s network.

Ransomware Attacks

Ransomware attacks have become increasingly common in recent years. This type of attack usually starts with a phishing email, but instead of just containing typical malware, it also has a ransomware virus. This virus will then encrypt all of the data on the organization’s network and demand a ransom be paid in order to decrypt it.

Denial-of-Service Attacks

A denial-of-service attack (DoS attack, also known as DDoS) is a cyber-attack that aims to make a healthcare organization’s website or network unavailable. This is usually done by flooding the organization’s servers with requests so that they can no longer handle legitimate traffic.

Insider Threats

An insider threat is a type of attack that is carried out by someone who already has access to the healthcare organization’s network. This could be an employee, contractor, or vendor. In the majority of cases, insider threats are pretty difficult to detect and can do a lot of damage.

Best Practices and Strategies Preventing Cyber Attacks with Machine Learning

There are many different steps that healthcare organizations can take in order to prevent and protect themselves from cyber attacks. Machine learning technology can be very helpful. Here are some of the most important ways to use this technology to thwart cybercriminals.

Educate Employees about Cybersecurity

One of the best ways to prevent cyber attacks is to educate employees about cybersecurity. Employees should be trained on how to spot phishing emails, as well as what to do if they receive one. They should also know how to properly handle patient data and understand the importance of encrypting all sensitive information.

If you want to educate your employees, you have to make sure that you are properly informed yourself. You will want to use machine learning technology to track the latest developments in cybercrime. New AI-powered applications can monitor malware, track the activities of known cybercriminals and otherwise collect data on developments in cybersecurity. This knowledge can help you inform your employees about the cybersecurity protocols that they can follow.

Implement Strong Security Measures

We have mentioned in the past that it is essential to use AI to protect against cyberattacks. One of the reasons that AI can automate many of the protocols needed to thwart cybercriminals. Machine learning can also detect possible attacks that would otherwise go unnoticed.

Healthcare organizations should use AI technology to implement solid security measures, like strong firewalls and intrusion detection systems. They should also have a secure process for handling patient data and make sure that only authorized personnel have access to it. All data should be appropriately encrypted, both in transit and at rest.

Regularly Back up Data

Another critical step that healthcare organizations can take is to regularly back up their data. This way, if they do fall victim to a ransomware attack, they will still have access to their data. It’s also essential to make sure that backups are stored off-site so that they can’t be accessed by the attacker.

You can use AI technology to automate your data backups. Machine learning technology can help determine the best times to backup your systems, so you can minimize the risk of losing valuable data.

Monitor Networks 24/7

Network monitoring is vital for all organizations, but it’s especially important for healthcare organizations. This way, the IT staff in the company can quickly spot any unusual activity and take steps to stop an attack before it does any damage. Again, machine learning is vital to network monitoring in 2022.

Machine Learning is Vital to Protect Healthcare Organizations Against Cyberattacks

We can conclude that cybersecurity is a crucial topic for all organizations, and healthcare ones are often the biggest target. There are many different types of cyber-attacks that they can fall victim to, and the consequences can be severe. A big cyberattack can cost millions of dollars in damages, as well as an irreparable stain on a company’s reputation.

That’s why it’s crucial for healthcare organizations to take steps to prevent and protect themselves from these attacks. By taking strong security measures, like educating employees, monitoring network activity, and backing up data, most healthcare organizations will be safe from all attacks.

TAGGED:AI and cybersecurityAI in healthcareAI-driven cybersecurity
Share This Article
Facebook Twitter Pinterest LinkedIn
Share
By Matt James
Matt James is a veteran marketer & tech geek that has helped many large brands increase their online footprint. He specializes in influencer outreach and business growth.

Follow us on Facebook

Latest News

trusted data management
The Future of Trusted Data Management: Striking a Balance between AI and Human Collaboration
Artificial Intelligence Big Data Data Management
data analytics in ecommerce
Analytics Technology Drives Conversions for Your eCommerce Site
Analytics Exclusive
data grids in big data apps
Best Practices for Integrating Data Grids into Data-Intensive Apps
Big Data Exclusive
AI helps create discord server bots
AI-Driven Discord Bots Can Track Server Stats
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

artificial intelligence in healthcare and users trust
Exclusive

What To Know About AI In Healthcare And How To Help Your Users Trust It

11 Min Read
ai is a dangerous weapon in the hands of hackers
Artificial Intelligence

How AI Caused RYUK Ransomware to Disrupt Healthcare Technology

10 Min Read
ransomware increase
Data Management

AI-Savvy Hackers Threaten Businesses With 20% Ransomware Increase

6 Min Read
AI and nursing
Artificial IntelligenceExclusive

Nursing Schools Are Forced to Adapt to Advances in AI

7 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-24 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?