Privacy in the Cloud: Fortifying data protection with business processes

Cloud infrastructure is swiftly becoming the essential foundation for a flexible, modern enterprise. More and more organizations are well into their cloud migrations and are reaping rewards through unprecedented scalability and next-generation speeds.

However, many of enterprise technology’s most stubborn challenges do not vanish with implementing a cloud model—they merely change shape. Data protection and privacy compliance are top priorities for the administrators of on-premises networks, and although the attack vectors and types of threats may change, the emphasis for cloud administrators is no different. The novelty of cloud systems and the resource constraints of migration risk monopolizing a technology team’s focus at the expense of securing sensitive data.

At the same time, the development of privacy regulations in nations worldwide and the rise of generative AI (gen AI) are presenting businesses with additional unique data security challenges. The European Union’s General Data Protection Regulation (GDPR) has changed the regulatory landscape for markets that handle the personal data of EU citizens, adding another layer of complexity to Canada’s patchwork of evolving provincial and federal privacy laws.

Even as these laws seek to address the needs of contemporary commerce, gen AI introduces further twists: adding an all-new attack surface, providing threat actors with robust social engineering and intrusion tools, and transforming the risk management and response capabilities of modern security platforms. In this shifting landscape of sophisticated threats and costly penalties, enterprises can protect themselves and their customers by building cloud transformations based on best practices for data protection and privacy.

Common threads emerge in traditional data protection and privacy strategies

Although each organization’s cloud transformation is unique, enterprises often face some combination of similar hurdles.

• The demands of “big data” –Cloud architectures enable the collection and storage of enormous amounts of data that the physical constraints of an on-premises data center would otherwise limit. This volume of data requires alternative techniques to secure, back up, and manage.
• Data governance policies –Cloud storage offers unprecedented accessibility, but organizations must match it with robust security tools and policies to prevent breaches and theft.
• Infrastructural complexity –The proliferation of platforms in a cloud-based ecosystem risks siloing information and may be resource-intensive to manage.
• Transparency hurdles –The hardware supporting cloud-based platforms is not wholly owned in the way an on-premises data center is, and different cloud-native tools are required to achieve the same level of visibility.

Cloud evolution introduces new challenges

Next-generation technologies introduce threats and opportunities that are transforming data protection and privacy strategies for modern businesses.

• Regulatory evolution –The cost of non-compliance is rising, and enforcement is growing more stringent. Multiple Canadian privacy laws are being updated for 2025 at both the provincial and federal levels, with the potential to increase protections for consumer data.
• AI-driven security platforms –AI tools open the door to swifter, more effective cybersecurity with intelligent, autonomous threat identification and remediation. Key to these tools’ effectiveness, however, is their secure and knowledgeable implementation, in addition to compliance with evolving legal requirements around gen AI.
• Next-generation AI cyberthreats –Threat actors also have access to the power of AI and are leveraging it to develop more convincing social engineering strategies, as well as intelligent penetration and camouflage tactics.

<strong>Read more: <a href="/blog/cybersecurity-awareness-month-2024">Cybersecurity Awareness Month: Staying safe with AI solutions</a></strong>

The foundations of cloud data protection

Information security is concerned with shielding sensitive data and processes from unauthorized access. The core principles of information security are summed up in the CIA triad: confidentiality, integrity, and availability. Secure data is kept inaccessible to threat actors, is adequately maintained and accurate, and can be accessed by credentialed personnel.

Data privacy is a related but distinct discipline. These standards concern how authorized users handle sensitive personal information, including the policies governing how it is collected, shared, and accessed.

Key strategies for protecting data in the Cloud, from both privacy and security standpoints, include:

• Risk assessment: Identifying and addressing vulnerabilities, beginning with the most pressing.
• Access control: Implementing robust policies to guide and limit access to sensitive data.
• Data encryption: Leveraging strong encryption to shield data at rest and in transit.
• Anonymization: Removing personally identifying information (PII) and/or combining datasets to protect individuals’ identities.
• Backup and disaster recovery: Ensuring business continuity and reducing vulnerability to catastrophic events or attacks with high-quality backup tools and policies.
• Destruction: Thorough, unrecoverable deletion of sensitive data that no longer serves a business interest.

The above principles translate into an array of best practices and tools to support cloud-based data protection and privacy:

Principles

• Zero-trust network architecture: The zero-trust security philosophy is the current gold standard of cybersecurity. Zero trust demands explicit, continuous verification of users and assets across an enterprise’s digital footprint and is rooted in principles of least access and impact mitigation.

Processes

• Risk analysis: Create a rubric to outline the security posture and potential risks of any cloud partners or tools.
• Security assessments: Leverage trusted third-party security experts to conduct regular testing, pinpoint vulnerabilities, and develop mitigation strategies.
• Organizational education: Establish a strong understanding of best practices among staff regarding data handling locally and in the Cloud. Emphasize general security awareness and empower employees to identify and flag risks.
• Leverage AI: Intelligent security tools can learn and adapt to user behavior, identify deviations and risks, and respond to threats in real time.

Tools

• Secure authentication and identity management: Multi-factor authentication and strong credential policies help ensure files are accessed only by authorized, appropriate individuals.
• Access control: Design role-based permissions structures according to the principles of least access and limit privileges to what is strictly necessary
• At-rest encryption: Ensure that stored data is encrypted by your cloud provider or your own resources.
• Encrypted data transfer: Leverage secured connections and file encryption protocols to secure data in transit.
• Endpoint security: Set centrally enforced security policies and establish threat monitoring on any user devices that access cloud data.
• Secure APIs: Protect API connections with robust authentication and encrypted transmission to prevent access by threat actors.
• Backup and disaster recovery: Avoid losses from data breaches, hardware failures, or service interruptions with incident response planning and backup tools.

The role of AI in securing cloud data

Next-generation, cloud-native security platforms increasingly use AI to interpret and respond to threats in a number of ways. Intelligent security ingests network activity and builds a model of legitimate traffic and user behavior, against which it can compare anomalous events such as resource utilization spikes or atypical login locations. Critically, these AI tools are also ideally positioned to identify insider threats using the same model.

With access to the latest threat information, AI-enhanced platforms are capable of autonomous assessment and mitigation of cybersecurity risks before breaches even occur. Its ability to analyze network traffic and patterns makes AI an essential partner in optimizing security infrastructure and policies for effectiveness and usability.

<strong>Read more: <a href="/blog/integrating-ai-and-cybersecurity-emerging-threats-and-strategies">Integrating AI and cybersecurity: Emerging threats and strategies</a></strong>

Transform your data protection to match your cloud architecture with OnX.

Migration to the Cloud requires a modernized approach to data protection and privacy. To keep sensitive information secure, enterprises must tackle longstanding challenges in novel ways while also addressing the unique hurdles of cloud cybersecurity. AI can help, but organizations will also benefit from the expertise of an accomplished third-party provider like OnX to ensure regulatory compliance, conduct thorough vulnerability assessments, and develop comprehensive policies.

Cloud providers and their clients are connected through a shared security model. While providers secure their infrastructure, enterprises can safeguard their data with the support of a knowledgeable partner above and beyond what cloud providers alone can offer. To begin developing your cloud-native approach to compliance and data security, contact OnX today.