Security

Network and connectivity security spans the technologies and practices that protect networks, devices, and data from a growing range of threats — from supply-chain and signaling attacks to threats against private networks, IoT, and critical infrastructure. As networks become more software-defined, distributed, and open, the attack surface expands, and security shifts from a perimeter model toward zero-trust, identity-based, and AI-assisted defense. For operators and enterprises, security is now central to private networks, 5G standalone, edge, and IoT decisions rather than an afterthought. Regulation and nation-state activity have raised the stakes further. This channel covers security across telecom and enterprise connectivity — private and public network security, zero trust, IoT and OT, and the threats shaping the landscape — with analysis aimed at teams securing modern, distributed networks against evolving risk.

SK Telecom ATHENA: AI-Native 6G Blueprint

SK Telecom ATHENA: AI-Native 6G Blueprint
SK Telecom introduced ATHENA—an architecture grounded in AI-native operations, Zero Trust security, hyper-connectivity, openness, and cloud-native design—to guide mid- to long-term evolution across RAN, core, transport, and network data platforms. The operator positions “AI for network” and “network for AI” as dual tracks: the former embeds AI into decision loops for autonomous optimization, while the latter tunes the network fabric to serve AI workloads efficiently. SK Telecom will showcase related technologies at MWC Barcelona 2026, including AI agents for networks, AI-RAN for combined connectivity and compute, device-side AI for antenna tuning, and integrated sensing-and-communications.

Nokia and AWS Launch Agentic AI for 5G-Advanced Network Slicing

Nokia and AWS Launch Agentic AI for 5G-Advanced Network Slicing
Nokia and Amazon Web Services (AWS) are bringing agentic AI to 5G-Advanced network slicing, moving closed‑loop, intent-based services from PowerPoint to live pilots with du and Orange. The partners unveiled an agentic AI-powered slicing solution that fuses Nokia’s RAN-to-core slicing, AirScale radio, and MantaRay SMO with AWS’s Bedrock AI platform and EKS Hybrid Nodes to turn external context—events, traffic, maps, weather—and live network KPIs into real-time policy decisions. The result is adaptive, premium slices provisioned when and where they’re needed, without manual reconfiguration.

The Future of Digital Identity: How AI is Enhancing Authentication and Fraud Prevention

The Future of Digital Identity: How AI is Enhancing Authentication and Fraud Prevention
As digital life expands, traditional passwords are no longer enough to protect users from rising fraud and identity theft. Artificial intelligence is transforming digital identity by enabling smarter authentication, real-time fraud detection and adaptive security systems. By balancing innovation with privacy and trust, AI is helping build a safer, more seamless online future.

Claude Code Security: AI finds 500+ vulnerabilities

Claude Code Security: AI finds 500+ vulnerabilities
Anthropic has introduced Claude Code Security, an AI capability that reviews codebases, flags complex vulnerabilities, and proposes patches with human oversight, and its early results should change how security leaders plan for AI on both offense and defense. Anthropic reports that its latest Claude Opus 4.6 model helped uncover more than 500 vulnerabilities in production open-source projects, including issues that had persisted for years. The product centers on high-signal findings, structured triage, and human-in-the-loop remediation so it can slot into existing DevSecOps workflows.

KDDI & Nokia: Quantum-Safe Optical Transport for AI DCI

KDDI & Nokia: Quantum-Safe Optical Transport for AI DCI
KDDI and Nokia validated quantum-safe optical transport at KDDI’s new Sakai Data Center, a facility built to support real-time AI training, inference, and analytics. The demonstration used Nokia’s 1830 Photonic Service Switch with C+L band capabilities for capacity scaling and the 1830 Security Management Server for centralized key and policy control. The goal is clear: deliver high-throughput, low-latency, and line-rate encrypted data center interconnect (DCI) that is resilient against both today’s threats and tomorrow’s quantum-era risks. Encrypting at the optical layer removes the performance penalties of application or IP-layer encryption and avoids fragmenting security by workload.

Infosys and Anthropic Claude: AI Agents for Telecom

Infosys and Anthropic Claude: AI Agents for Telecom
A new partnership between Infosys and Anthropic brings agentic AI into regulated, process-heavy industries, with telecom squarely in scope. Infosys will integrate Anthropic’s Claude models and Claude Code with its Topaz portfolio to build and operate enterprise-grade AI solutions across telecom, financial services, manufacturing, and software engineering. The collaboration emphasizes agentic AI—systems that can plan, call tools, and execute multi-step workflows with oversight—delivered with the controls, auditability, and policy enforcement that regulated sectors demand. Pairing Infosys’s domain depth with Claude’s reasoning and long-context capabilities gives operators a path to pragmatic automation that respects regulatory, safety, and transparency requirements.

India’s AI stack needs AI-native networks: Ericsson CTO

India’s AI stack needs AI-native networks: Ericsson CTO
India’s AI agenda increasingly spans silicon, data platforms, models, and applications, with an intent to catalyze domestic innovation and contribute to global ecosystems. For telecom leaders, the message is clear: AI is not a bolt-on capability but a system-level transformation that touches RAN, core, transport, cloud, and the enterprise edge. The AI economy runs on connectivity—low-latency access to data, assured bandwidth, location-aware processing, and programmable control. The operators that can fuse connectivity, compute, and data into a cohesive platform will set the pace for India’s next wave of digital growth.

OpenAI AI Devices: Multimodal Hardware Roadmap

OpenAI AI Devices: Multimodal Hardware Roadmap
OpenAI is reportedly building a portfolio of AI-native devices, signaling a push beyond software and into ambient, multimodal computing that will touch homes, workplaces, and networks. Multiple reports indicate OpenAI has over 200 people developing a family of AI-enabled hardware, with a smart speaker expected to debut first. Early guidance points to a price in the $200–$300 range and a ship window no earlier than February 2027. The device is said to include a camera to capture contextual information about users and surroundings—an explicit bet on multimodal AI that fuses voice, vision, and environment for richer interactions.

Ericsson and Mistral AI: Telco-Grade Network Automation

Ericsson and Mistral AI: Telco-Grade Network Automation
Ericsson and Mistral AI are aligning telecom-grade engineering with customizable foundation models to push AI deeper into network operations and RAN automation. The pairing marries Mistral AI’s fast-evolving model stack with Ericsson’s domain expertise across radio, cloud-native networking, and service management. For European operators, it signals a path to AI capabilities that respect data residency, security, and compliance expectations under the EU AI Act without ceding control to generic, hyperscaler-led platforms. The outcome operators want is simple: measurable gains in performance, efficiency, and resiliency with governance baked in.

Private Network Security Ecosystem

Private LTE, 5G, and CBRS networks are becoming the backbone of industrial operations. This article maps private network security vendors to a Four Pillars framework—Core Controls, Device Visibility, Detection & Response, and Orchestration—revealing where structural gaps emerge in real-world industrial deployments. From slice isolation and SIM lifecycle governance to OT micro-segmentation and SOC integration, it explains why layered enforcement—not vendor breadth—determines private 5G security resilience.

Monitoring, Assurance & Testing for Private LTE/5G

Monitoring, Assurance & Testing for Private LTE/5G
Private LTE and 5G security does not fail because of flawed architecture—it fails when enforcement controls degrade silently. This guide explains how enterprises implement continuous monitoring, assurance, and testing loops across control-plane signaling, user-plane routing, identity governance, and industrial OT environments. Learn how to validate segmentation integrity, detect policy drift, test Zero Trust enforcement, and produce audit-ready evidence across multi-site private cellular deployments.

Device Identity, OT & IoT Security in Private Cellular Networks

Device Identity, OT & IoT Security in Private Cellular Networks
Private LTE and 5G networks strengthen authentication at the transport layer—but device identity, lifecycle governance, and OT/IoT realities determine whether containment holds. This in-depth guide explains SIM and eSIM authentication models, service-profile authorization, identity drift risks, industrial gateway mediation, and Zero Trust containment strategies across multi-site private cellular deployments.

Frequently Asked Questions

What’s the biggest emerging security risk for telecom networks right now?
Quantum computing’s eventual ability to break current encryption standards is the dominant emerging concern, often described through the framing of ‘harvest now, decrypt later,’ where adversaries collect encrypted data today, intending to decrypt it once sufficiently powerful quantum computers exist in the future. This matters particularly for telecom given how much sensitive data flows across networks protected by encryption standards quantum computers could eventually defeat. Alongside this longer-term quantum concern, the more immediate, near-term risk involves the expanded attack surface created by 5G’s heavy reliance on cloud-native, virtualized infrastructure and exposed APIs, which gives attackers considerably more potential entry points than older, more closed network architectures presented.
Are telecom networks actually doing anything about quantum threats yet, or is it theoretical?
It’s moving from theoretical to practical. Thales demonstrated that existing deployed 5G SIM and eSIM cards can be upgraded to quantum-safe protection without service disruption, proving that mobile networks can evolve their security through crypto agility rather than requiring an entirely new generation of hardware. Operators including BT, SK Telecom, Orange, and Deutsche Telekom are running live quantum-safe networking trials, with Deutsche Telekom specifically demonstrating quantum teleportation over a meaningful distance of commercial fiber in early 2026. These aren’t purely academic exercises; they represent genuine, if still early, steps toward preparing live commercial telecom infrastructure for the eventual quantum threat.
What is post-quantum cryptography (PQC), and is there a deadline for adopting it?
Post-quantum cryptography, commonly abbreviated PQC, refers to encryption algorithms specifically designed to resist attacks from future quantum computers, in contrast to the encryption algorithms most networks currently use, which quantum computers are expected to eventually break. Regulatory pressure is real and increasingly specific: the NSA’s CNSA 2.0 standard mandates quantum-safe algorithms for new national security system acquisitions by January 2027, and the European Commission is pushing critical infrastructure sectors, including telecom, toward post-quantum readiness by 2030. These deadlines, while initially focused on government systems, are widely expected to influence broader commercial telecom security planning timelines as well, since telecom is frequently classified as critical national infrastructure.
Is AI making telecom networks more or less secure?
It cuts both ways. On the defensive side, AI dramatically speeds up threat detection by spotting unusual patterns across enormous volumes of network traffic far faster than manual monitoring, and it increasingly powers automated incident response. On the risk side, AI agents given meaningful operational access to network systems represent a genuinely new kind of attack surface; if an agent’s decision-making can be manipulated, or its access misused, the consequences could be more severe than a typical software vulnerability, since the agent is specifically designed to take autonomous action on live infrastructure rather than simply process and report information.
Are 5G networks more vulnerable than older networks, or more secure?
5G’s expanded use of cloud-native, virtualized infrastructure and exposed APIs creates a larger attack surface than older, more closed network architectures, since there are simply more distinct software components and potential entry points for an attacker to target. At the same time, 5G’s architecture also enables faster patching, since updating virtualized software is generally quicker than physically replacing hardware, network slicing isolation, which can contain a security incident within one affected slice, and AI-based monitoring capabilities that weren’t practically possible on older, less data-rich legacy hardware. The honest assessment is that 5G is both more exposed in certain ways and better equipped to detect and respond to threats quickly in others.
What is ‘harvest now, decrypt later,’ and why does it matter even before quantum computers are powerful enough to break encryption?
‘Harvest now, decrypt later’ describes a strategy where an adversary intercepts and stores encrypted data today, even without the current ability to break that encryption, specifically betting that future quantum computers will eventually be powerful enough to decrypt it retroactively. This matters even before such quantum computers actually exist, because any sufficiently sensitive data encrypted today using standard, currently-vulnerable algorithms could theoretically be exposed years from now once quantum decryption capability matures, meaning organizations handling especially long-lived sensitive data face exposure risk regardless of how far away the quantum threat currently seems. This is precisely why regulators are pushing for PQC adoption now, well before quantum computers are actually capable of breaking current encryption.
What role do network APIs play in expanding or reducing telecom security risk?
Network APIs, which let third-party developers access specific carrier capabilities like location data or SIM status, introduce both new monetization opportunities and new security considerations operators need to manage carefully. Each exposed API represents a potential new entry point that needs rigorous authentication and monitoring, since a poorly secured API could potentially expose sensitive subscriber data to unauthorized parties. At the same time, well-designed network APIs can actually improve security in certain ways, for instance by giving banks access to fraud-prevention signals like SIM swap detection. The net security impact of network APIs ultimately depends heavily on how rigorously operators implement access controls and ongoing monitoring.
How are telecom operators securing IoT devices specifically, given how many are deployed?
Securing the enormous number of IoT devices connected to telecom networks presents distinct challenges compared to securing a smaller number of more capable, actively managed devices like smartphones. Operators increasingly rely on network-level security measures, like specialized IoT-focused firewalls and traffic monitoring tuned to detect unusual behavior, rather than depending entirely on each individual device having strong built-in security, since many IoT devices have limited processing power for running sophisticated security software directly. Some operators also offer dedicated, isolated network slices specifically for IoT traffic, helping contain the potential impact if a vulnerability in one device category is exploited, preventing that compromise from spreading into the rest of the network.
Security in Private 5G Networks: A Practical Guide for Enterprises

As enterprises move deeper into digital transformation, private 5G has emerged as a pragmatic answer to a specific problem: how to deliver controlled, reliable, and secure wireless connectivity where public networks fall short. Unlike public 5G, a private network is built around the needs of a single organization, offering tailored capacity, customization, and coverage in environments that defeat conventional wireless.

That value is clearest in demanding settings. Industrial operations that depend on low-latency machine-to-machine communication, and businesses spread across large campuses, both gain from a network they own and control.

But control cuts both ways. The same architecture that makes private 5G powerful also makes security a first-order design question rather than an afterthought. In a threat landscape that grows more sophisticated each year, securing a private 5G deployment is not a feature to bolt on later. It is part of the build.

The right approach is grounded and comprehensive. It accounts for the current threat environment, the vulnerabilities inherent to the technology, and the critical business functions the network supports. For most enterprises, the real question is not whether to adopt private 5G, but how to stand up a security posture that is resilient, adaptable, and matched to the risks this technology introduces.

Is Private 5G the Most Secure Option?

Security is the headline advantage cited for private 5G, but the honest answer is more nuanced than "yes." Private 5G is not automatically the most secure connectivity option in every dimension. What it offers is the strongest balance of security, flexibility, and scale, which is why it fits enterprises that need both protection and reach.

What makes private 5G secure

The security of private 5G starts with its architecture. In its most secure form, the network is fully isolated from the public network, hosted and managed on-site, and operated entirely by the enterprise. That isolation removes the network from the open internet and the vulnerabilities that come with it. On top of it, private 5G layers advanced encryption, strict access controls, and close monitoring of network traffic. Together these create a framework that is far less exposed to unauthorized access and external threats. Network slicing adds another dimension. By carving the network into separate virtual segments, each with its own security policy, an enterprise can match controls to the sensitivity of the data flowing through each slice.

What are the Best Practices for Securing Enterprise Private 5G?
  • Strong private 5G security comes from layering deliberate practices on top of the network’s built-in features. Enterprises should start by building security directly into the network architecture. This begins with strict access control, including SIM-based authentication paired with role-based access, so only authorized users, devices, and applications can connect. Advanced encryption should be applied to data at rest and in transit, supported by disciplined encryption key management. Network slicing can further strengthen security by creating separate, secure virtual networks for different operations, teams, or use cases. Regular audits and ongoing compliance checks are also essential to ensure the network continues to meet relevant industry standards and regulatory requirements. In addition, 5G-specific security controls should be integrated with the enterprise’s existing security infrastructure, with careful planning around the unique requirements of private 5G environments.
  • Effective private 5G security also depends on how threats and people are managed. Enterprises should deploy advanced threat detection capabilities to identify breaches or abnormal behavior early, and they should support those tools with a clear incident response plan that enables teams to act quickly when an issue occurs. Staff training is equally important. Employees and operational teams need to understand 5G security protocols, device access rules, and incident escalation processes. Security awareness should become part of normal operations, not an occasional training exercise. Enterprises should also work closely with service providers, technology vendors, and system integrators under a clear shared-responsibility model, so every party understands its obligations and meets the enterprise’s security standards.
  • Organizations should also recognize the limits of private 5G’s “secure by design” foundation. Private 5G is not immune to attack, and built-in security should be treated as a starting point rather than a complete defense. A strong posture requires additional layers, including continuous monitoring, real-time threat detection, and an end-to-end view across every component of the network. This is especially important at the points where IoT, OT, and enterprise IT systems intersect. Regular software updates and patching are non-negotiable, as outdated systems can quickly become weak points. Physical security also matters, particularly for network equipment located in Radio Access Network areas, edge sites, and other operational environments.
  • Private 5G gives enterprises a level of control that public networks cannot provide, and that control is the source of both its security advantages and its responsibilities. The technology is not secure by default in every dimension, but with isolation, encryption, slicing, continuous monitoring, and a disciplined operational posture, it can deliver a strong combination of security, flexibility, and scalability. For enterprises weighing connectivity options, the question is less about whether private 5G can be secure and more about whether the organization is ready to build, operate, and maintain the security posture that makes it so.
How it compares to other options

A fair comparison puts private 5G alongside private LTE, Ethernet, and WiFi rather than against public 5G alone:

Feature Private 5G Private LTE Ethernet (Wired) WiFi
Isolation Full isolation possible Full isolation possible Inherently isolated Shared medium, less isolated
Encryption Advanced encryption Less advanced than 5G Depends on protocol Less robust
Access control SIM-based authentication SIM-based authentication Physical and protocol-based SSID and password
Network control Full on-site control Full on-site control Full control, limited flexibility Less control, more exposure
Network slicing Supported Not supported Not applicable Not supported
Edge computing integration Seamless, enhances security Possible, less integrated Possible, can be very secure Less integrated
Traffic monitoring Easier, software-defined Harder than 5G Easier, fixed pathways Harder
Attack surface Reduced by isolation Reduced by isolation Minimal, no wireless access Larger, wireless access
Physical security High, controlled environment High, controlled environment Very high, hard to tap Lower, easier to intercept
Scalability High, with slicing Scalable, no slicing Limited Scalable but less secure

The table makes the trade-off clear. Ethernet is exceptional on physical security and isolation, but it cannot match private 5G for flexibility, mobility, or scale, particularly when supporting large fleets of IoT devices and mobile users. Private LTE is secure but lacks 5G capabilities like network slicing. WiFi is convenient and widely deployed, but its shared medium leaves it more exposed to interference and eavesdropping.

No single option wins on every axis. The right choice depends on what the enterprise needs to protect and how dynamic its environment is. For organizations that need strong security without sacrificing scale and mobility, private 5G is usually the best fit.

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