Introduction

If you spend any time in the security industry, you hear it regularly: “We keep our video local because it’s safer that way.” It sounds reasonable—until you examine the data, the threat landscape, the cost of breaches, and the rising operational demands in 2025–2026.

ArcadianAI speaks to hundreds of monitoring centers, guard companies, and enterprise SOCs every quarter, and the pattern is always the same: organizations cling to local DVR/NVR boxes not because they are safer, but because the belief used to be true in the analog era. Today, the assumption is not only outdated—it’s become a measurable liability.

Meanwhile, competitors like Genetec, Milestone, Eagle Eye Networks, Verkada, and Avigilon Alta are all aggressively pushing cloud or hybrid-cloud ecosystems for one simple reason: modern security workloads demand it. AI, GPU processing, event correlation, after-hours detection, remote scaling, compliance logging, and incident verification simply cannot operate at enterprise level on isolated, aging boxes sitting on shelves.

And yet, the myth persists.

This post breaks down why “local is safer” no longer matches reality, why cloud-native architectures have become the dominant security standard, and why organizations upgrading today are designing for the next decade—not the last one.

Quick Summary / Key Takeaways

• Local storage ≠ safer

• Cloud security outperforms local boxes

• Compliance favours cloud-native designs

• AI and GPU workloads require cloud scale

• On-prem systems increase breach exposure

• ArcadianAI delivers encrypted, zero-trust monitoring

Background & Relevance: Why Now?

The landscape changed—silently, but massively.

• False alarms remain at crisis levels. Over 36 million false intrusion alarms occur annually in the U.S., costing $1.8B+ in wasted police response. (Urban Institute, 2023)

• 90–98% of alarms are false, according to SIAC (2024). False positives overwhelm operators and create liability.

• NVR/DVR vulnerabilities continue to be exploited globally, with botnet infections, ransomware, lateral movement, and credential scraping increasing year over year.

• AI workloads exploded. Frame-by-frame GPU processing, forensic search, and contextual alarms can’t run effectively on traditional on-prem boxes.

• Compliance tightened. SOC2, PIPEDA, GDPR, and new state laws require auditability, encryption standards, and access logs that older systems can’t provide.

Put simply:
The world moved on. Most camera systems didn’t.

Core Exploration

Why does the “local is safer” myth still exist?

Because it feels true, not because it is true.

For decades, physical security was rooted in physical proximity: if the recorder was in the next room, the organization believed it controlled the risk. But modern attacks don’t require proximity—they exploit exposed ports, outdated firmware, weak passwords, and lack of encryption.

ArcadianAI Angle

ArcadianAI’s Bridge device uses outbound-only TLS 1.3 encrypted tunnels and stores no permanent credentials—removing the single largest attack vector in traditional NVR deployments. ()

Are local DVR/NVR systems actually safer?

No. They are consistently one of the most targeted and breached device categories globally.

Why?

• They require open inbound ports

• They often run outdated firmware

• They rarely implement zero-trust

• They have no SOC2/GDPR-grade audit trails

• They’re physically accessible, unencrypted, and unmonitored

Attackers know this. Local NVRs became soft targets years ago.

ArcadianAI Angle

ArcadianAI never exposes inbound ports, never stores credentials, and keeps all video encrypted at rest (AES-256) and in transit (TLS 1.3). ()

What makes cloud-native security architectures stronger today?

Modern cloud platforms, particularly AWS, provide:

• Built-in encryption

• Zero-trust access controls

• Continuous patching

• SOC2 Type II compliance

• Distributed infrastructure

• Multi-region failover

• 24/7 threat monitoring teams

No local NVR on earth offers this.

This is why Genetec, Milestone, Verkada, Eagle Eye, and Avigilon Alta have all shifted to cloud or hybrid-first ecosystems.

How do AI and GPU workloads make local storage obsolete?

AI changed everything.

Modern video security requires:

• Frame-by-frame analysis

• Context-aware detection

• Multi-camera correlation

• After-hours vs working-hours mode switching

• Forensic search

• Natural-language event queries

These workloads need scalable GPU compute, orchestration, and continuous improvement models. Local systems cannot perform this reliably.

ArcadianAI Angle

ArcadianAI runs all AI inference on secure cloud GPUs, dynamically scaling up or down. Ranger distinguishes between Active Hours and Passive Hours to optimize cost and performance. ()

What about compliance—does cloud create more risk?

Quite the opposite.

Regulations such as:

• PIPEDA (Canada)

• SOC2 Type II

• GDPR

• State-level privacy laws

all require:

• Audit logs

• Access controls

• Encryption

• Residency guarantees

Local recorders don’t meet these requirements unless extensively customized.

ArcadianAI Angle

ArcadianAI processes data in AWS Canada or AWS U.S., depending on client choice, ensuring jurisdiction control. All events are encrypted at rest and in transit. ()

Why do enterprises still hesitate to move to cloud video?

Three reasons:

1. Legacy beliefs from the DVR era

2. Misunderstanding of cloud vs internet

3. Fear of losing control

But modern cloud doesn’t reduce control—it increases it:

• Real-time policy editing

• Role-based access

• Mobile access

• Detailed audit trails

• Centralized configuration across sites

ArcadianAI Angle

ArcadianAI delivers a unified interface across Web, iOS, and Android for full operational visibility, real-time edits, evidence export, and forensic search. ()

What are the actual risks of staying on legacy local systems?

Tangible, measurable risks:

• Ransomware exposure

• Downtime during physical incidents

• Lost footage (drive failures)

• No remote access

• No AI/analytics enhancements

• No scalability

• Regulatory failure

• Evidence corruption

Security leaders face increasing liability for outages, lost evidence, and missed events—most of which stem from outdated infrastructure.

Comparisons & Use Cases

How does ArcadianAI compare to traditional NVR/VMS/VSaaS?

Use Case 1 — National Retailer

Before: 800+ cameras, overloaded operators, 95% false alarms
After: 85% reduction, 4× operator coverage, same staff

Use Case 2 — Property Management (Residential)

Before: Local NVRs with frequent failures
After: Cloud-AI event verification, lower liability, remote forensic search

Use Case 3 — Remote Video Monitoring Center

Before: Hiring to keep up
After: Ranger filters noise → humans resolve → more margin

FAQ  

Q1: Is cloud video surveillance secure enough for enterprise?
Yes. Cloud platforms offer encryption, zero-trust access, and SOC2/GDPR-grade audit trails that local recorders cannot match.

Q2: Does cloud mean my video leaves my country?
No. ArcadianAI processes data in AWS Canada or U.S. per customer choice. ()

Q3: What if internet drops?
Your NVR continues recording locally; Ranger backfills analytics when the connection returns. ()

Q4: Does ArcadianAI require port forwarding?
No. The Bridge uses outbound-only encrypted tunnels.

Q5: Can we control our own policies?
Yes. You can build, edit, and tune detection policies in real time.

Conclusion & CTA

The belief that “local is safer” once made sense. Today, it’s the single most dangerous assumption security leaders can make. Modern threats, compliance standards, and AI workloads have surpassed what isolated NVRs can ever deliver.

Cloud-native architectures are not just a convenience—they are now the security baseline.

ArcadianAI offers a secure, encrypted, zero-trust, GPU-powered platform that turns existing cameras into AI-as-a-Guard without replacing hardware or changing workflows.

See ArcadianAI in Action →

Quick Glossary (Embedded)

• VSaaS — Cloud-hosted video surveillance.

• VMS — Software for managing video feeds and cameras.

• NVR — Local recorder storing video onsite.

• AI Alarm Filtering — AI that suppresses noise and surfaces real events.

• Zero-Trust — Security model assuming no implicit trust.

• PIPEDA — Canadian privacy law governing personal data.

• SOC2 — Compliance framework for secure handling of data.

• Forensic Search — Ability to search video by objects, actions, or time.

• GPU Processing — High-performance computation required for AI tasks.

• Outbound-Only Bridge — ArcadianAI’s connector with no inbound ports.