Today, the healthcare industry is using technology to perform the simplest functions, such as administrative duties or even complex tasks like robotic surgeries. Almost every health organisation stores patient information, medical records and treatment plans electronically on computers and networks. All of this may seem easy for medical professionals, but it also exposes healthcare organisations to security problems.
In this blog, we will explain cybersecurity threats in healthcare, how to address this challenge, and the role of software-defined networks and AI for cybersecurity in the healthcare industry.
What cybersecurity issues are we facing in healthcare?
The people behind cybersecurity threats are cyber criminals that are like digital thieves. These individuals are always looking for important data and information that can be used against the organisation or sold for money. This can cause major issues for healthcare organisations such as hospitals and NGOs. Here are a few cybersecurity issues that we are facing in healthcare:
Data breach: A patient’s sensitive information is extracted illegally and is used for identity theft or to cause harm to a patient.
Corrupt data: Cybersecurity criminals use malicious software to get inside healthcare data systems to delete and corrupt the data. As a result, healthcare industries lose large amounts of sensitive data that can cause financial loss and delay healthcare operations.
Denial of service: DoS attacks are the most common cybersecurity threats to a healthcare organisation. Cybercriminals can increase the traffic on a website, damaging healthcare services as users can not use the site properly.
Fraud emails: Important patient records and data can be revealed to cybercriminals when healthcare users open emails that have malicious software. These software are specially designed to get unauthorised access to data so that it can be sold on the black market.
What do the statistics tell us about the attacks?
Cyberattacks have become a big problem for every industry and healthcare is no exception. It is well-known that hospitals rely on computers to store patient data, provide treatment plans, and run important tests and equipment. Hence, they become a target for the hackers. We can imagine what would happen to a health organisation if a doctor ends up clicking the wrong link. Additionally, the numbers below show us why we need to take cybersecurity challenges seriously:
- There was a 75% increase in cybersecurity attacks in 2024 compared to 2023.
- If a company faces a breach of security, then the cost of recovering from the attack in 2024 is $4.5 million, which is a 15% increase over the last three years.
- 93% of networks, especially the healthcare system, are at risk of being hacked.
- Phishing attacks are increasing by a rate of 400% every year.
- A huge budget is to be set for cybersecurity challenges in healthcare systems by 2025 which will be around $458.9 billion.
How can we protect the data of the healthcare industry?
The healthcare industry faces a lot of pressure. From managing sensitive patient data, to providing quick and efficient healthcare services, to conducting the right health operations, these organisations work hard day and night to improve themselves. Therefore, cybersecurity attacks can not only damage their services but also ruin their reputation. To address these challenges, two important technologies must be used, which are:
Software defined networking (SDN):
Software-defined networking is a modern technology that makes it easier to manage computer networks. Before this technology, computer networks were controlled by physical devices like routers and switches. With SDN, you can manage networks with the help of software instead of hardware, which is more secure to use. Let us understand what are the main characteristics of a software-defined network:
| Feature | Explanation |
|---|---|
| Better Network Working | With SDN, you can see what is happening in the network and what data is passed around. You can easily monitor the performance and check for failures and security issues. Moreover, when there is a high demand for data, SDN automatically provides more bandwidth so that the software works efficiently. |
| Improved Security | SDN allows you to control how the data follows in the network. Network administrators can quickly identify if any suspicious activity is carried out. For instance, if there's a sudden increase in traffic from an unknown source, SDN immediately checks and blocks it. |
| Central Control | SDN has a centralised control management system, which means that the network is operated from one single point. This makes it easier to manage the software and its settings from one place than to spend time on each device (hardware). |
| Easy Changes | If more devices or users need to be added to the network, SDN adjusts the resources without additional costs or changes in the hardware. |
Advantages of software-defined networks in healthcare:
SDN can be used to improve the security and management of healthcare data. Here are the best advantages of using software-defined networks in healthcare:
- SDN ensures that patient data is transferred to different departments and networks safely without any data breaches. It also helps healthcare organisations meet important regulations like HIPAA (which protects patient data) by making sure that cybercriminals can not access the data.
- SDN helps healthcare organisations make changes in their networks easily and adapt to new technologies, such as telemedicine and IoT. This is done without any extra costs or causing problems in the healthcare services.
- SDN reduces downtime if the network faces cybersecurity threats, data breaches or equipment failure. It gives a quick response to these problems by rerouting the data as fast access to information is very important in the healthcare industry.
Artificial intelligence:
Artificial intelligence uses algorithms, such as machine learning, deep learning, and natural language processing, to perform complex tasks and human-like functions. It examines large sets of data, identifies patterns, and makes accurate predictions. Nowadays, it is used to make business predictions and improve the diagnosis of diseases.
Additionally, AI is of two types:
- Generative AI
- Predictive AI
Advantages of AI in healthcare:
The use of AI healthcare and medicine helps doctors and patients. Healthcare professionals can make accurate predictions about diseases and provide the right treatment by examining patient data and medical history. Here are some advantages of using AI in healthcare:
- AI assistants and chatbots are used in the healthcare industry to improve the patient experience so that doctors can focus on patient care. This technology is being used to provide 24/7 support for health concerns, medication reminders, and to schedule appointments.
- AI uses various models, such as deep learning, machine learning, and natural language processing, to analyse patient data and make predictions. It examines the genetic and historical data of patients so that doctors can make the right diagnosis which can save lives and prevent future health problems.
- A recent study about artificial intelligence in medical diagnosis found that it reduces treatment costs by 50% and improves the chances of accurate health predictions by 40%.
- AI manages patient and hospital information without causing any harm to the data. This can include genetic information, medical history, prescription and treatment plans and even information on the number of hospital beds for patients. Hence, it uses natural language processing models to understand human language and quickly finds what the doctors are looking for.
Want AI solutions for your company?
From chatbots to automation & predictive analytics, we help businesses get the most out of AI.
Boost efficiency. Reduce costs.
Book a ConsultationWhat is the role of AI in healthcare data protection?
Artificial intelligence is minimising cybersecurity threats and helping healthcare systems stay safe from attacks on personal data and medical records. Here is how AI is working to address the challenges:
- If someone is trying to gain access to private patient information, then AI quickly spots such illegal activities. It goes to the root of the problem and blocks them. Moreover, if someone is trying to hack a healthcare website, AI will not only notice the problem but also deal with it without waiting for any human assistance.
- AI will not only react to cybersecurity issues but also provide accurate predictions by examining the weak points in the network or system. It also studies the historical data of healthcare systems and websites. After a thorough analysis, it gives preventive measures to follow so that the risk of cyber attacks is reduced.
- Phishing attacks are very common in healthcare systems. However, AI checks the source of the email and immediately blocks any malicious links or information. It can also keep a system or email away from the main network, so that the malware is not spread everywhere.
- AI can lessen cybersecurity problems as it works 24/7. It keeps an eye on healthcare systems and uses encryption and other tools to protect medical data that is shared between different departments and devices. Hence, AI in healthcare cybersecurity solutions is very important.
Importance of Software-defined networks and AI for cybersecurity in the healthcare industry
It is necessary to understand the importance and role of Software-defined networks and AI for cybersecurity in the healthcare industry. Let us understand how they work with a few examples:
Example 1: An unknown device is trying to connect to the network of a hospital.
SDN: SDN controls the hospital’s network from one single point. It can see where the unknown device is trying to connect and from which source. It will immediately identify it and block it from causing any damage.
AI: AI will monitor the network and see what device is trying to connect. It will analyse its behaviour and compare it with other past cyber threats. If it detects an issue, it will alert the system at once.
Example 2: There is a suspicious attempt to read and access a patient’s medical data.
SDN: First, when data is sent to other departments through different networks, SDN checks that the file is encrypted. This means that it is protected by a code that only some people can read. However, if any suspicious activity is reported by AI, it immediately blocks it.
AI: AI uses algorithms to see whether the person accessing the medical data has used this network before or not. If it finds someone who does not typically access the information, it alerts the system and can also stop the user by blocking them.
Example 3: An internal source is trying to access patient and doctor treatment notes.
SDN: Only the right people, such as doctors or nurses can access patient data. If SDN detects an internal source who is not part of the department, it can block the request. Moreover, it can also segment the network so that the electronic data is limited to other people or roles.
AI: AI will alert the system and also stop the user if it compares the user’s online behaviour and pattern of access towards the patient’s data and finds an issue.
Example 4: A cyberattack is carried out in the research department of a healthcare system.
SDN: SDN will separate the research department from other departments so that the cyber attack does not spread. It segments the network and and lessens the impact of the attack.
AI: AI will use measures to prevent the malware from attacking the system. It will also try its best to stop the attack with the help of SDN.
Example 5: Certain parts of a network are being used more than usual.
SDN: SDN will quickly analyse if there is an increase in traffic. It will make changes in the network rules so that cyber attacks can be reduced. It will also reroute the data, and provide more bandwidth to areas where the traffic has increased so that the healthcare services are not disturbed.
AI: AI uses predictive analysis to understand why certain parts of the network are being used more than usual. It will use historical data to find patterns. After finding patterns, it makes predictions and alerts the healthcare systems so that they can avoid future cyberattacks.
Conclusion: what is the future of SDN & AI in healthcare
The need for strong security systems will keep increasing in the future as healthcare systems are going digital. Technologies like telemedicine, smart devices and electronic health records are making it necessary for SDN and AI to be used in the healthcare industry. Both of these technologies will not only manage large amounts of patient data but also make sure that everything runs smoothly.
As AI keeps growing and changing, we will see that it will prevent cyber attacks even before they happen with the help of deep learning and machine learning algorithms. By predicting security problems before they happen, it will be able to improve the network security so that it can adjust to any threats. Moreover, hospitals and research facilities will use Software-defined networking in healthcare security and AI-driven threat detection in healthcare by combining them with other security tools like firewalls, antivirus software and encryption technologies. Hence, this will lessen the cybersecurity challenges in the healthcare system.
Read More: Research article on ethical concerns for AI in healthcare
Frequently Asked Questions
- In medical research facilities (to protect information about research and clinical trials from the public).
- In hospitals ( to secure connections when medical records and patient information are shared between different departments).
- Telepath Platforms ( to ensure privacy between patient and doctor for online consultancy or appointments).
