How to Ensure Data Privacy in Custom Software Development

Whether you are planning to develop a mobile game, custom ERP, or SaaS tool, you need to pay attention to data privacy in software development.

It can be costly to not protect user data according to privacy regulations. Fines for GDPR violations can amount to up to EUR 20 million or 4% of the company’s global revenue, for example. Personal data is also a prime target for hackers. The average cost of a data breach jumped 10% year-on-year to $4.88 million in 2024.

That’s not to mention the associated reputational losses you’ll suffer from getting implicated in a regulatory compliance or data breach scandal.

To prevent these losses, data privacy has to be baked into your product during its initial development. Here’s how to do it right.

What Is Data Privacy in Custom Software Development?

In general, data privacy refers to the rights of individuals (i.e., personal data owners) to control what happens to their data when they share it with organizations. For organizations, in turn, ensuring data privacy means enabling users to exercise their rights with specific policies and processes.

N.B. Data privacy isn’t the same as data security, although they do go hand in hand. Data security refers to the measures taken to protect data from unauthorized access and use. It complements data privacy by preventing the wrong people from viewing or misusing personal data. Data privacy, in turn, determines who should be able to access data and how they can use it. Together, data privacy and data security make up data protection in software development.

Data privacy in custom software development means designing and building the solution in compliance with applicable regulatory requirements to ensure user privacy. It involves assessing which personal data will be collected, how it’ll be used, and how to enable users to control what happens to their data.

To address privacy risks during custom software development, you can use the LINDDUN framework to evaluate potential threats. LINDDUN is an acronym that describes seven common categories of privacy risks:

• Linkability: Linking separate data items or user actions to learn more about the user through inference. It doesn’t necessarily involve directly revealing their identity. Example: user XYZ spends office hours at location L → location L is the office of company C → user XYZ works at C.

• Identifiability: Discovering the user’s identity through data leaks, inference, or deduction. It can be done using both identified (direct link to user identity) and identifiable (indirect reference) data.

• Non-repudiation: Attributing a claim to a specific user. A claim involves specific evidence of action or fact. Example: authorship metadata can prevent deniability claims regarding the document’s content.

• Detectability: Inferring more information based on the simple fact data exists, without actually reading it. Examples: identifying communication flows, application side effects, or system responses.

• Disclosure of information: Collecting, storing, processing, or sharing more personal data than is strictly necessary.

• Unawareness: Not giving users sufficient information about or control over personal data collection and use.

• Non-compliance: Not following applicable data security and data management legal requirements and established best practices.

Compliance with Data Privacy Regulations

What addressing data privacy in custom software development means in practice depends heavily on the applicable general and industry-specific regulations.

General privacy regulations apply to all organizations collecting personally identifiable data. They’ll apply to your product whether you plan to develop a predictive maintenance AI solution, online store, or enterprise software system. The most noteworthy examples here are GDPR, CCPA, and PIPEDA.

General Data Protection Regulation (GDPR)

Passed in 2016, GDPR is the flagship privacy EU regulation that serves as a model for multiple other national privacy laws around the world. For example, the United Kingdom’s GDPR is practically identical to the EU’s regulation, and the CCPA shares many similarities with it.

Among many personal data rights, the GDPR established the right to be forgotten, meaning the data owner can ask the organization to erase their personal data. Other rights include the right to access the collected personal data, request corrections to it, and object data processing.

Under GDPR, data processors have to:

• Request user consent for personal data collection

• Notify regulators about data breaches

• Ensure personal data security

• Use pseudonymisation for certain types of personal data

California Consumer Privacy Act (CCPA)

Passed in 2018, the CCPA is a state statute that ensures California residents have the right to know what personal data is collected and whether it’s shared with or sold to third parties. It also establishes their right to refuse data sale, access the collected data, and ask for personal data erasure.

You’ll have to comply with the CCPA if you plan to conduct business in California and meet at least one of these criteria:

• Bringing in gross revenue over $25 million

• Collecting personal data of 50,000 or more individuals

• Generating half or more of the annual revenue by selling personal data

Personal Information Protection and Electronic Documents Act (PIPEDA)

Although less known than GDPR or CCPA, the PIPEDA is a Canadian privacy law that predates both. Passed in 2000 and amended with the Digital Privacy Act in 2015, it established the following rights for individuals:

• Knowing why data is collected, used, and stored

• Gaining access to personal data stored by an organization

• Requesting corrections to personal data

Under the PIPEDA, organizations can’t use personal data without consent or for purposes other than the ones for which they received user consent. They also must:

• Take appropriate security measures to protect personal data

• Provide a product or service even if the consumer doesn’t consent to personal data collection (unless it’s essential to the transaction)

• Maintain personal data policies that are easy to understand, clear, and readily available

Industry-Specific Privacy Regulations

Industries like finance and healthcare have to deal with extremely sensitive personal data. That’s why organizations in those industries have to comply with stricter privacy rules to ensure data protection in software development.

N.B. If you’re planning to build an AI/ML solution, pay attention to AI-specific regulations, such as the recently passed Artificial Intelligence Act in the EU.

Here’s a quick overview of some industry-specific privacy laws and standards:

Privacy by Design Principles

Whether you plan to turn to a custom software development service vendor or build your solution in-house, you need to consider data privacy in software development from the beginning. This is where the Privacy by Design (PbD) framework can help you mitigate privacy risks.

Privacy by Design is a set of principles describing a proactive approach to enabling and protecting data privacy in all data-processing activities. Let’s break down the seven principles that make up the Privacy by Design framework.

Systematic approach

You should conduct privacy impact and risk assessments both during product design and regularly throughout its lifecycle. All findings should be thoroughly documented, and the revealed privacy risks should be addressed.

Data minimization

Collecting unnecessary data gives rise to unnecessary privacy risks. To avoid them, your product should collect as little data as possible; this is known as data minimization. When data collection is a must, the collected data should be non-identifiable, non-observable, and non-linkable by default.

Purpose specification and limitation

Whenever you need to collect data, its owners (i.e., users) have to be notified about the data collection and its purposes. This notification has to be clear and delivered before you start collecting data. The stated purposes have to be reasonable, relevant, and limited in scope.

User consent and transparency

You need to obtain user consent for data collection, use, and sharing unless stated otherwise in law. You have to communicate what data is collected and for what purposes, including whether it’ll be shared with third parties. Users should be able to withdraw their consent and access their data whenever they want.

Visibility and accountability

All stakeholders should be able to review the personal data processing process and practices and verify that they meet the stated objectives and regulatory requirements. To enable this visibility and accountability, you need to document all data processing policies and activities. You should also be ready to share this information with stakeholders.

Security measures

Robust, appropriate security measures throughout the personal data life cycle are a must for enforcing privacy. These measures typically include encryption, authorization, access controls, and logging and monitoring. The ensemble of data security measures should ensure data remains confidential and available and preserve its integrity.

Retention limitation

You should store personal data only as long as it’s necessary to fulfill the stated purposes. The personal data no longer needed should be securely destroyed to prevent further privacy risks for the user.

How to Ensure Privacy Throughout the Development Lifecycle

Data privacy in custom software development should be foundational at all development stages, from requirements gathering to deployment and maintenance. Here’s how to adopt a Privacy by Design mindset at each stage of the project:

• Requirements gathering: Conduct a privacy impact assessment to identify potential privacy risks and compliance requirements. Select the appropriate mitigation strategies for each of them.

• Design: Make appropriate technological and architectural choices to implement data minimization and other PbD principles. Consider API security, encryption, and access controls. Add user consent and privacy notifications to the UI/UX design.

• Development and coding: Implement the designed safeguards for personal data. Ensure developers follow secure coding practices (e.g., input validation, secure error handling).

• Testing and QA: Check your solution’s data privacy and security before release. Use a combination of manual and automated testing methods, including penetration testing.

• Deployment and maintenance: Draw up comprehensive documentation and provide adequate training to the maintenance team. Conduct regular privacy audits and address changes in privacy risks.

Conclusion

To minimize the risk of non-compliance and data breaches, you need to consider data privacy starting with requirements gathering during custom development. That said, the Privacy by Design principles should be part of your approach throughout all software development lifecycle (SDLC) stages.

As privacy legislation continues to evolve across the world, implementing robust privacy practices is a must for any forward-thinking organization. If you choose Integrio to build your solution, our experts will consider all privacy regulations and follow Privacy by Design best practices. As a result, you’ll get a fully compliant solution that protects your users’ data privacy.