The pressing need for cybersecurity in healthcare today is evident. As
digital systems are more widely utilized for maintaining accurate
information on patients and automating various operations within
healthcare organizations, protecting patient data has become of
paramount importance. Healthcare data is often more valuable and
vulnerable than other types of data, as it typically consists of
private, medical, and financial information, and its excessive
exposure is highly undesired. A single data breach could result in
massive financial loss, reputation damage, and, above all else, a
compromised sense of patient safety and secrecy.
The daily barrage of cyber attacks on the healthcare sector shows how
crucial a robust cybersecurity posture is. With the threat of
ransomware, data breaches, phishing, and internal threats,
organizations need to understand the growing scope and sophistication
of threats to embrace a robust and full-circle approach to
cybersecurity in healthcare software development. This strategic
approach is critical and mandatory, as there is no room for compromise
in the safety of patient data.
Healthcare software encounters unique cybersecurity challenges as
healthcare data comes with a set of vulnerabilities that can
effectively be exploited in prohibitive or cost-prohibitive ways in
other realms. In turn, the promise of big data and precision medicine
requires us to contend with these vulnerabilities and develop pockets
of cybersecurity that can accommodate our ever-growing and more
vulnerable big data sets. This article takes us through the salient
issues facing healthcare software development and privacy and suggests
steps to shore up the defense of this data.
But health data – from identification details such as names,
addresses, and dates of birth, Social Security numbers, contact
details, diagnostic codes, and even cancer claims – offers a virtual
larder for cybercrooks. Not only do these data open the way for
identity theft, forged cards, insurance fraud, blackmail, and even the
perpetration of unauthorized medical treatment, but they are also
exceptionally rich in their clinical, temporal, and pseudonymized
forms. Electronic records are where coded numbers and letters
substitute the characteristic names and dates associated with a
person. Unlike those where the electromagnetic tagged payment data can
be canceled post-transaction, medical records are mother’s milk to a
hacker, containing information written in stone.
As US healthcare delivery systems become more electronic, with the
widespread use of electronic health records (EHRs) and EHR
interoperability systems, security continues to be an issue. Most
records contain patient financial information, along with a plethora
of information vulnerable to being exploited, including the ability to
open fraudulent accounts or fraudulent prescriptions. But there is
much more. Records also offer the opportunity to access medical
services and control or direct medical care. Healthcare records remain
some of the most valuable data commodities on the dark web, and the
payoff remains enticing.
With so many vulnerabilities, healthcare organizations are facing a
menagerie of severe threats, all with the potential to stop the work
of frontline staff and break the privacy and confidentiality of our
data. Data breaches are one of the most common threats to healthcare.
This is when data, including patient information, is accessed by
someone who doesn’t have permission. Data breaches might happen by
hacking, software with malicious intent known as ‘malware,’ or when
vulnerabilities in the IT systems uncover the data. Like all
companies, healthcare organizations can be affected by a ransomware
attack. In a ransomware attack, malicious ‘ware’ is injected into the
system that encrypts all the data so that it can’t be accessed from
the systems; until a ransom is paid, the attacker holds the data and
won’t return access. Healthcare facilities have been bought down,
postponing and even suspending important treatments and procedures
that can have fatal outcomes for patients.
Intentional or otherwise, insider threats are a major threat to
healthcare cybersecurity. This includes staff with legitimate access
to sensitive information who may accidentally or deliberately breach
data security with inappropriate actions or make mistakes with
authentication or security settings that accidentally expose sensitive
information. Furthermore, phishing and social engineering attacks
continue to advance as a preferred mechanism by which indiscriminate
sharp practice in deceiving healthcare staff is used to manipulate
them into divulging sensitive information or to allow unauthenticated
access. This is typically done through malicious emails that resemble
authentic communications and trick people into clicking links or
sharing information that can be used to spoof or compromise accounts.
Understanding these threats is important to developing a cybersecurity
approach that targets the value of healthcare data and considers the
different types of cyber threats that place healthcare systems at
risk.
Adhering to all regulations is a unique and fundamental challenge in
developing healthcare software, as the software has to follow various
standards to protect patient data according to strict rules and
regulations. Some of them are specific to the United States, like the
Health Insurance Portability and Accountability Act (HIPAA), and they
enact the set of rules that govern the use and disclosure of
individuals’ health information, while others are on a more
continental level like the General Data Protection Regulation (GDPR)
in the European Union. At a high level, these regulations protect a
citizen’s right to privacy regarding the processing and storing of
personal data, living without surveillance, and not having their data
misused. The European regulation ensures all of this – GDPR.
The biggest challenge regarding these regulatory standards is that
everything from their design to the mechanics of deployment must
comply with the rules, be it technical, administrative, or physical
protections. Developers must think at the system's edge, ensuring that
their software can enact safeguards to protect transmitted data as it
is stored and accessed. On top of that, regulatory compliance is
frequently a question of navigating complex legal and ethical
boundaries. Few software developers can afford to remain ignorant of
constantly evolving regulations, requiring extra effort to keep their
solutions relevant in the face of changing times.
Data privacy is one of the top priorities for healthcare software.
Ensuring solid data encryption at rest and during data transfer is
essential for meeting patients' expectations that their health
information will be kept confidential except when disclosed by valid
consent or regulation. Storing data securely in compliance with data
governance, privacy, and confidentiality policies can prevent
unauthorized usage, breaches, or leaks while maintaining patient
trust.
One of the most perplexing challenges for maintaining patient
confidentiality involves patient information held across platforms and
devices such as mobile apps, cloud storage, and electronic health
records (EHR). These platforms vary in terms of the security measures
they need to implement to be secure and their vulnerabilities.
Developers must implement consistent and robust security across all
platforms as information is shared between patients, healthcare
providers, and numerous third-party services and apps. The conflicting
needs for information exchange and documentation (interoperability),
on the one hand, and strict data privacy protections, on the other,
require careful orchestration and implementation of advanced
safeguards.
Secure authentication and access controls so that you can be certain
that only the right individuals will get access to information stored
in your healthcare system. Strong authentication processes, such as
multi-factor authentication (MFA), are essential for confirming the
identities of users trying to access patient files. MFA processes
generally require at least two different methods of verification, such
as something that the user knows (such as a password), something that
the user has (for example, a security token), or something that the
user is (such as through a biometric identifier).
The challenge is to balance the security issues against the usability
issues. The more robust the authentication, the better the security,
but the more challenging it can be for users. For example, healthcare
workers may need to access patient files quickly in a life-or-death
situation and cannot be delayed by extensive authentication checks. At
the same time, healthcare software developers may want to use
Role-Based Access Control (RBAC) so that users can only access those
patients assigned (or delegated) to them for their decision-making.
This is a good example of enhancing usability without giving up
security.
It’s important for different systems in healthcare to share
information and for devices to work together in a process known as
interoperability. However, integrating with other people’s software or
IoT devices for more complete patient care inevitably creates security
issues. Merely allowing a third party (human or otherwise) with open
access to your network creates bigger threats than many organizations
can fix. Security problems can arise from these third-party
integrations because even though there might be verifiable interfaces
involved, you don’t know what they’re doing behind the scenes – the
CIA’s account packages could have a backdoor for other systems too.
To ensure proper security when integrating systems and systems with
devices or components, standards-based protocols with data encryption
best practices need to be developed and implemented: APIs need to be
secured, communication channels need to be secured, and third-party
integrations need to be authenticated as secure. Importantly, the
interoperability requirements that allow for efficient, effective care
delivery must be balanced with efforts to maintain a certain level of
security.
Such systems, particularly those used in healthcare where they’re
frequently connected to legacy systems, sometimes supersede others and
outlast multiple software upgrades. They’re also often full of holes
and comparably vulnerable to attack because of their (frequently)
antiquated software and hardware – not to mention the fact that it can
be very hard to replace some legacy systems that are essential to the
functionality of a healthcare organization.
Patch management and regular security updates are important to address
legacy systems' existing vulnerabilities. However, frequently
releasing updates can disrupt services and affect interoperability
among different systems. Developers must carefully conduct risk
assessments and develop strategies for deploying updates in a manner
that causes minimal disruptions to operations while enhancing
security. In the long run, strategies for phase-out, replacement, or
upgrading legacy systems to more secure, modern solutions are required
for a resilient cybersecurity infrastructure of healthcare services.
Adopting a security-first approach to development can help developers
build secure healthcare software. This paradigm introduces security
considerations at the very beginning of the development lifecycle and
keeps security central to the process. Having security as an integral
part of our software’s architecture can help developers proactively
prevent malicious attacks and reduce risks.
Security audits and regular testing, such as pen testing and code
analysis based on best practices and secure coding standards, are key
practices in a security-by-design approach. The same applies to
software monitoring, with updates as vulnerabilities are identified in
both the software being used and the core systems being linked to.
Data encryption is a basic component of safeguarding sensitive
healthcare information. Best practices include encrypting data at rest
(e.g., stored data) and in motion (e.g., across a network) using
standards-based algorithms and key-management practices to ensure that
data is unreadable and unusable if captured without consent or
otherwise compromised.
Secure data transmission protocols, such as HTTPS and SSL/TLS, provide
encryption of data during transfer between health information software
and other systems or devices (e.g., clinical, consumer, research
databases, payment systems, and the greater Internet). The use of
secure APIs for data exchange and communications further helps to
prevent malicious modification of data and ensure its privacy and
confidentiality.
Strong authentication and authorisation methods are an absolute
necessity for the safety of access to healthcare systems and data,
while multi-factor authentication (MFA) builds security by providing
more than one verification form to the system, such as a password and
a one-time code delivered to a mobile phone, minimizing the impact of
compromising one form of authentication.
RBAC is another help that ensures that individuals have access to the
pertinent information contained in EMRs and resources according to
their role: you cannot access anything without a very strong reason.
In some scenarios, approaches like least privilege can be of use to
minimize the likelihood of exposure and misuse. In a healthcare
setting, decisions regarding permissioning would ultimately depend on
the organization's size, nature, and priorities. Although insider
threats would not always be at the forefront of a healthcare
organization, ensuring a cautiously implemented policy, where access
rights are reviewed regularly, would minimize the risk of an insider
threat.
MFA adds a second or third step to the authentication process, making
it harder for attackers (multi-factor authentication – image courtesy
Northern Illinois University Center for Information Security
Education). Strong authentication and authorization controls are
essential to secure access to health IT systems and data. MFA adds a
second or third step to the authentication process to make it harder
for attackers (say, to intercept passwords) to succeed without
legitimate credentials (see figure above). Even if someone were to get
hold of one authentication factor, for example, when logging in from
an unknown device, the second factor (the one-time password or OTP
sent to a previously registered mobile device) would be necessary to
gain access.
Users have access only to what they need for their roles, a crucial
principle known as ‘the principle of least privilege’. And they can’t
share that access even if they choose to. This potentially prevents
great harm since sensitive information is kept out of the wrong hands,
the typical root of a data breach, while minimizing the potential for
malignancy and misuse. By judiciously applying the principle of least
privilege and continuously reviewing who can do what, security
achieves its most practical and perhaps incredibly beneficial
objective: collision-proofing all the ways for an insider to become a
threat.
Every corporation will need an incident response plan to prepare for
and respond to cyber security breaches. A good plan outlines what to
do should a breach occur, including determining the breach, containing
the breach, killing the breach, and recovering from an incident. The
plan should also contain procedures to advise key stakeholders, report
to regulators, and perform post-mortems on an incident to better
prepare for the next one.
A good way to ensure an incident response plan is effective and
current is to test and update it regularly as newer threats are
uncovered. Knowing that a clear, practiced plan is in place also
allows HDOs to reduce their response time to a cybersecurity incident
and halt the damage before personal data gets misused and patient
trust is eroded.
Machine learning and other technologies are also beginning to
transform cyber security, backed by artificial intelligence (AI)
programs, to consistently improve their capabilities in identifying
and mitigating threats, especially at the organizational level of any
system. Health care, for example, can leverage the sophisticated
sensing, computing, networking, and detection capabilities of IoMT to
harness AI and ML for protective surveillance and timely notification
of aberrant behavior and user or device behavior that is highly
suggestive of cyber threats.
AI and ML have significant potential to be applied toward automating
threat intelligence in cybersecurity. AI tools can learn from new
information and apply it towards enhancing prediction. For instance,
with advanced AI systems, it might be possible to establish the
behavioral patterns of users and devices. This would cause anomaly
alerts to be sent when an insider threat has compromised an employee
or an account. AI might also be useful in helping automate present
processes such as granting privileged systems access, establishing
user profiles, patch management, vulnerability assessments, and other
commonplace security tasks and undertakings where human effort is
needed. However, what are the challenges for AI and ML adoption in
healthcare cybersecurity? Since AI and ML use data, the issue of data
privacy arises. Algorithms should learn from safe, protected, and
traceable data and be unbiased.
However, the blockchain’s distributed and immutable ledger
architecture could be a good way to securely store data and
electronically share it among healthcare professionals involved in a
patient’s care, making records virtually tamper-proof and tightly
controlled. Its architecture can improve data integrity because any
alterations to data are recorded in the blockchain and are, therefore,
visible to all parties to the network, making unauthorized data
tampering virtually impossible.
Using blockchain for patient data in healthcare allows more secure
sharing of clinical and individual-protected health information with
an access control restriction within the system. Sensitive patient
information is secured. Claims processing and streamlining medical
billing with a ledger for medical transactions allows for a permanent
audit trail with no hidden entries. Similarly, having access to
digital, verified identities for patients and practicing providers can
be easy with blockchain. Challenges for using blockchain broadly
shortly are scalability from a technical perspective, interoperability
with existing healthcare IT systems and infrastructure, and regulatory
realm. As blockchain evolves and matures in the years to come,
addressing these technical and functional challenges will be essential
to facilitate its spread in healthcare.
The pandemic forced healthcare to adopt telemedicine, and the swift
growth of this new domain brought a new breed of cybersecurity
threats. Our health information exchange must be private and secure,
and there have been many reports and incidents of data to attend to.
Telemedicine relies on an information exchange, so the security of
these platforms is critical to patient privacy and trust in healthcare
services as they become more remote.
The security issues that arise when video consultations are involved
and the data is in motion are unique to telemedicine. The identity of
the patient and an attending medical professional must be verified.
Good security practices for a telemedicine platform include but are
not limited to end-to-end encryption for video and data transmission,
robust authentication, compliance with healthcare security regulations
(such as the Health Insurance Portability and Accountability Act or
HIPAA in the USA), timely updates and security monitoring for the
platform, and alerting and educating patients on safe practices when
utilizing a telemedicine service.
Cybersecurity must keep pace with the spread of telemedicine. Because
healthcare providers' needs are so specific, the demand for secure
communications will be just as specialized and innovative. From
identity verification for doctors and nurses at home giving care to
data protections for patients being checked on by a doctor, the
cybersecurity industry will benefit from the increasingly broad range
of use cases.
The challenges associated with cybersecurity in healthcare software development are extensive. They can no longer be ignored when it comes to protecting sensitive patient data and the integrity of healthcare systems. The fact is that healthcare data, in particular, presents a big target for cybercriminals. At the same time, this data is generally considered highly sensitive and critical, so every stage of developing software should adhere to the most stringent security standards possible. Healthcare software developers are faced with some enormous challenges, such as complying with strict regulations intended to protect patient rights to data privacy and safeguarding complex system interoperability. However, by approaching security as a key strategic goal in software development, implementing some of the most advanced forms of encryption and authentication, as well as having adequately trained staff to stay at the forefront of emerging cyber threats, there is no reason why healthcare software developers cannot catch up with the cyber criminals. As technology continues to evolve, with AI, machine learning, and blockchain also looking to utilize their capabilities to bolster cybersecurity integrity, I hope that healthcare systems will be as resilient now and in the coming decades to face new and emerging threats.