Law enforcement interest in IoT data is growing as connected devices proliferate across networks. The Internet of Things (IoT) is transforming industries from logistics and agriculture to healthcare and smart cities. Billions of connected devices now communicate over cellular and non-cellular networks, generating vast quantities of machine-to-machine (M2M) data. For telecommunications operators — particularly those providing Low Power Wide Area Network (LPWAN) connectivity and M2M services — this growth brings not only commercial opportunity but also expanding regulatory obligations, including lawful interception.
The application of lawful interception obligations to IoT and M2M communications is a developing area of regulation, but the direction of travel is clear: as IoT traffic grows and becomes more relevant to criminal investigations, law enforcement interest in IoT data is growing, and operators should expect more requests for data, mainly for subscriber, location and traffic data rather than live content. This article examines the current state of LI obligations for IoT operators, the technical challenges involved, and the steps operators should take to prepare.
Why IoT Lawful Interception Matters
The question of whether IoT and M2M communications fall within the scope of lawful interception obligations is primarily a legal one, and the answer varies by jurisdiction. In the European Union, the obligation to support lawful interception generally applies to providers of electronic communications services that are available to the public. Under the EU Electronic Communications Code, transmission services used for machine-to-machine communication are electronic communications services (Art. 2(4)(c) EECC). Whether they carry LI obligations depends on whether they are offered to the public and on national law, which sets the LI conditions and any exemptions.
In Germany, § 170 TKG and the TKÜV (Telekommunikations-Überwachungsverordnung) require operators of networks used for publicly available telecommunications services to provide interception capability, and M2M transmission services count as telecommunications services (§ 3 No. 61(c) TKG). The TKÜV exempts some systems from having to install interception facilities, for example systems used only to transmit measurement data (§ 3(2) No. 4 TKÜV) or systems with no more than 10,000 users (§ 3(2) No. 5). Whether an IoT offering is exempt therefore depends on what it carries, not on the label ‘IoT’. In other EU member states the details differ.
Even an operator that is exempt from installing interception facilities must cooperate with an individual order (in Germany, § 100a(4) StPO). It should therefore know how it would carry out an order on its IoT platform, even where no permanent LI system is required.
Why IoT Data Matters for Law Enforcement
IoT devices generate data that can be highly relevant to criminal investigations. Connected vehicles generate location data, driving patterns, and communication logs. Smart home devices record environmental data, usage patterns, and in some cases audio or video. Wearable health devices capture biometric data and movement patterns. Industrial IoT sensors can reveal operational activities, supply chain movements, and environmental conditions. Even simple M2M devices such as vending machines or utility meters generate location and usage data that can be relevant in certain investigations.
As law enforcement agencies become more aware of the investigative potential of IoT data, they are increasingly likely to request interception or data disclosure from IoT operators. Operators that are unable to respond to these requests face not only regulatory consequences but also the risk of being seen as uncooperative by law enforcement authorities, which can have broader implications for the operator’s relationship with regulators.
Technical Challenges of IoT LI
Implementing lawful interception for IoT and M2M communications presents several technical challenges that differ significantly from traditional voice and data interception. The first is the diversity of communication protocols. IoT devices communicate using a wide range of protocols — MQTT, CoAP, LwM2M, HTTP, and proprietary protocols — over various network technologies including LTE-M, NB-IoT, LoRaWAN, Sigfox, and satellite. Each protocol and network technology has different characteristics that affect how interception can be performed.
The second challenge is the volume and pattern of communications. Unlike voice calls or web browsing sessions, IoT communications are typically short, infrequent, and low-bandwidth. A sensor may transmit a few bytes of data every hour. This pattern matters less for capture, because interception points copy every packet or non-IP message of the target, however small, but it means many sessions stay idle for long periods and each transmission is reported separately.
The third challenge is target identification. IoT devices may be identified by IMSI, IMEI, IP address, or device-specific identifiers that do not correspond to traditional subscriber identities. Mapping these identifiers to a specific target — particularly when the device is owned by an organisation rather than an individual — can be complex. The administration function and the interception points must support the identifier types used for IoT devices (for example IMSI/SUPI, IMEI/PEI, external identifiers and IP addresses), and the operator must be able to map a device serial number to one of them before the task is provisioned.
The fourth challenge relates to encryption and security. Many IoT protocols implement application-layer encryption, which means that the operator may be able to capture the encrypted traffic but not access the content. The DTLS and TLS implementations used by CoAP and MQTT, for example, may encrypt the application payload in a way that the operator cannot decrypt. This limitation must be communicated transparently to law enforcement when responding to interception requests. Operators must remove encryption they apply in the network or whose keys they help generate or exchange (in Germany, § 8(3) TKÜV); application-layer encryption between device and customer platform that the operator holds no key for is delivered as captured.
A fifth challenge is the sheer scale of IoT deployments. An operator may have millions of IoT devices on its network, and large device populations matter mainly for identifying the right device (for example mapping a device serial number to IMSI/IMEI) and for making sure all IoT core functions are covered. The number of simultaneous intercepts remains driven by the number of orders.
LPWAN-Specific Considerations
LPWAN technologies — including NB-IoT, LTE-M, LoRaWAN, and Sigfox — have specific characteristics that affect LI implementation. NB-IoT and LTE-M operate within the 3GPP ecosystem and are served by the cellular core network. 3GPP TS 33.127/33.128 already cover their IoT-specific paths: data sent over the signalling plane (Data over NAS) and Non-IP Data Delivery via the SCEF (4G) or NEF (5G). Operators must make sure these functions, not just the user-plane gateways, have interception points.
LoRaWAN and Sigfox operate outside the 3GPP ecosystem and use proprietary or open-standard network architectures. The application of LI to these technologies is less well-defined in terms of standards, and operators may need to develop custom interception solutions. The network architecture of LoRaWAN, for example, includes gateways, network servers, and application servers, and the network server sees device identifiers, timing and gateway (location) metadata, but the application payload is encrypted end-to-end with a key held by the application server. Interception at the network server gives readable content only where the operator also runs the application or join server.
IRI and CC for IoT Communications
Standard IRI covers what the network knows: identities (IMSI/SUPI, IMEI/PEI, external identifiers), sessions, location. Sensor readings travel as content (CC). Any additional metadata must come from the national handover specification, not from operator-specific extensions.
CC for IoT communications is typically much smaller in volume than for voice or data sessions, but may be more diverse in format. The content of an IoT transmission might be a JSON payload, a binary sensor reading, a protocol buffer message, or a proprietary data format. CC is delivered as an unaltered copy of what was transmitted (for example IP packets or non-IP data), together with the IRI. Interpreting proprietary payload formats is the job of law enforcement’s analysis tools.
Preparing for IoT LI Obligations
Operators providing IoT and M2M services should take proactive steps to prepare for LI obligations, even where the regulatory requirement is not yet fully defined. First, assess the regulatory position in each market where you operate, consulting with legal counsel and the relevant national regulatory authority. Second, evaluate your current LI capabilities against the specific requirements of IoT interception, identifying gaps in target identification, traffic capture, IRI generation, and CC delivery.
Third, develop a technical roadmap for enhancing your LI capabilities to support IoT interception. This roadmap should address the integration of IoT network elements with the LI mediation function, the extension of target identification to support IoT device identifiers, and coverage of the IoT-specific data paths (Data over NAS, NIDD via SCEF/NEF). Fourth, engage with your LI solution vendor to understand their roadmap for IoT LI support and to influence their development priorities based on your requirements.
Finally, document your approach to IoT LI compliance, including any limitations in your current capabilities and the steps you are taking to address them. This documentation shows the regulator why your service is exempt or how your interception capability is implemented. Where an obligation applies, it does not replace the capability: in Germany the facilities must be in place when the service starts (§ 170(1) TKG).
Conclusion
The growth of IoT and M2M communications is bringing more law enforcement requests to operators, because IoT data is increasingly relevant to investigations. While the technical challenges of IoT LI are significant — spanning protocol diversity, traffic patterns, target identification, encryption, and scale — they are not insurmountable. Operators that assess their regulatory exposure, evaluate their technical capabilities, and invest in IoT-capable LI solutions will be well positioned to meet their obligations and to maintain compliance as the IoT ecosystem continues to grow.
The intersection of IoT and lawful interception also raises broader questions about the scope of surveillance in an increasingly connected world. As everyday objects become networked and generate data streams, the boundary between communications interception and broader data collection becomes less distinct. Operators should engage proactively with regulators and industry bodies to help shape the emerging framework for IoT LI, contributing practical technical expertise to ensure that the resulting requirements are both effective for law enforcement and implementable by operators.
The scope of IoT lawful interception obligations varies by jurisdiction and service type. Operators should map their IoT lawful interception requirements early in their deployment planning.
Related Articles
For further reading on related topics, explore these articles:
- Network Slicing in 5G SA: How It Complicates (and Can Simplify) LI Targeting
- eSIM and Lawful Interception: What the RSP Architecture Means for Compliance
- MVNO vs MNO: Who Is Legally Responsible for Lawful Interception?
External Resources
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