By Garth, Senior Director at Gigamon

The pressure on industries to pursue digital transformation has increased exponentially in recent years. While the cloud and the Internet of Things (IoT) are key tenets of this transformation, they are also accompanied by several security concerns and damning cyber attack statistics. For example, one report found that 98% of organisations suffered at least one cloud security breach within an 18-month period. IoT and Operational Technology (OT) convergence poses an additional threat, as OT security is typically much weaker than in more modern devices. Not designed for today’s cyber-scape, the OT leveraged by manufacturers and engineers could become a critical point of weakness within their security strategy.

TIndustries are under growing pressure to embrace digital transformation. Cloud and IoT technologies lead this shift but raise serious cybersecurity concerns. One report shows 98% of organizations faced at least one cloud breach in 18 months.

The convergence of IoT and Operational Technology adds risk, as OT systems often lack modern security. Designed for older environments, they are now a key weakness in many strategies.

To stay secure, organizations must ensure deep observability across all networks, devices, and moving data. Still, this raises concerns around data privacy and compliance.

Security teams must strike a balance. They need to detect threats across cloud and IoT/OT setups while staying aligned with data protection rules like GDPR.

The risk is rising fast. Ransomware attacks are growing, and 59% of survey participants say the threat worsened recently. Criminals are now more organized and precise in their operations.

Often, attackers stay hidden for long periods. On average, adversaries dwell in systems for 287 days, gathering intelligence before striking.

Encrypted traffic adds complexity. SSL/TLS encryption is a standard tool for protecting data, but now it’s being misused. Around 91.5% of malware arrives through encrypted connections.

Businesses must inspect encrypted traffic, analyze it, and re-encrypt it to stop threats. This demands better visibility tools without compromising sensitive data.

Deep observability gives a complete view of traffic, helping teams identify issues quickly. Yet full visibility must still protect user privacy.

Data masking offers the solution. It alters sensitive data to make it useless to attackers. This also simplifies GDPR compliance since the masked data isn’t processed or stored.

Data masking is especially vital in sectors like finance and healthcare, where regulations are strict and data is highly sensitive. It also shields NetOps teams from exposure to private information.

By combining deep observability with data masking, organizations can secure networks and maintain privacy. As threats evolve, data masking will play a bigger role in cybersecurity strategies.

Security depends on visibility, but privacy must not be sacrificed. The future of digital safety lies in getting both right—together.

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