The Implementation of an HSM-Based Smart Meter for Supporting

DLMS/COSEM Security Suite 1

Tzu-Hsuan Huang

, Chun-Tsai Chien

, Chien-Lung Wang

and I-En Liao

Department of Computer Science and Engineering, National Chung Hsing University, Taichung, Taiwan

Taiwan Information Security Center at NCHU, National Chung Hsing University, Taichung, Taiwan

Keywords: Smart Meter, Hardware Security Module, DLMS/COSEM, Security Suite 0, Security Suite 1.

Abstract: To mitigate the impacts of climate change, many governments are making efforts to increase electricity

generation from renewable sources. However, the massive amount of distributed energy resources (DER)

involved introduces many challenges to electricity grid management. In the last decade, we have witnessed

power grids gradually evolving to become smart grids with advanced metering infrastructure (AMI). The two-

way nature of communication between smart meters and energy suppliers inevitably increases cyberattack

surfaces for smart grids. As a result, cybersecurity problems associated with smart meters and smart grids are

of great concern.

The purpose of this paper is to develop a smart meter using a hardware security module (HSM) that supports

the security mechanisms specified in Security Suite 1 of DLMS/COSEM. To the best of our knowledge, our

smart meter prototype is the first published implementation using HSM. This also represents an important

step in developing more secure IoT devices in general and smart meters in particular. Our implementation is

based on the open-source project GuruX, available on GitHub. We revised the smart meter program

GuruxDLMS.c to run on the Nuvoton M2354 hardware security module with the ability to invoke ECDSA,

ECDH, and SHA-256 functions implemented on the HSM. The smart meter developed in this research is also

tested for the implementations of ECDSA with P-256, ECDH with P-256, and SHA-256 using Conformance

Test Tool version 3.1 (CTT v3.1).

1 INTRODUCTION

The Glasgow Climate Pact delivered at COP26

declared a near-global net zero carbon goal by 2050.

Among the mitigation strategies for reducing

greenhouse gas emissions, energy supply

transformations, especially phasing down coal power

and speeding up the transition to clean energy and

electric vehicles, are the most important issues

(United Nations Framework Convention on Climate

Change [UNFCCC], 2021). Therefore, we can expect

that smart meter rollout will be accelerated, and the

integration of massive distributed energy resources

(DER) into the smart grid is a must.

The traditional power grid consists of centralized

power generation plants, transmission, distribution,

and substations, usually operating under security

protection within an isolated network. In contrast, a

modern smart grid will include front-of-the-meter

(FTM) and behind-the-meter (BTM) energy systems

such as wind turbines, solar panels, and power storage

systems (International Energy Agency [IEA], 2022).

With hundreds of thousands of smart meters on

the end-user side and massive interconnected DERs,

a smart grid increases available cyberattack surfaces

dramatically. In this paper, we focus on enhancing the

security of smart meters, since they are located on

user premises and are accessible to potential hackers.

To address the interoperability, efficiency, and

security issues of smart meters, the Device Language

Messaging Specification User Association (a.k.a.

DLMS UA) defines DLMS/COSEM (Companion

Specification for Energy Metering) for managing

smart meters. DLMS/COSEM has also been adopted

by international standards bodies and became the

standard for IEC 62056, ANSI C12, and EN 13757-1

(DLMS User Association, 2022a). In

DLMS/COSEM, three security suites that define the

set of security algorithms used are provided, namely

Security Suite 0, Security Suite 1, and Security Suite

2 (Kozole and Kmethy, 2019).

Huang, T., Chien, C., Wang, C. and Liao, I.

The Implementation of an HSM-Based Smart Meter for Supporting DLMS/COSEM Security Suite 1.

DOI: 10.5220/0011825300003482

In Proceedings of the 8th International Conference on Internet of Things, Big Data and Security (IoTBDS 2023), pages 123-130

ISBN: 978-989-758-643-9; ISSN: 2184-4976

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

123

Most of the smart meters deployed so far support

the security mechanisms in Security Suite 0,

including Advanced Encryption Standard-

Galois/Counter Mode-128 (AES-GCM-128) for

authenticated encryption and AES-128 key wrap for

key transport. This is evidenced by the majority of

smart meter products certified by DLMS UA being

Security Suite 0 compliant. Even though

authentication can be done using GMAC in Security

Suite 0, the increasing demand for communicating

with smart meters to ensure secure and efficient

energy management requires stronger authentication

mechanisms such as ECDSA (Elliptic Curve Digital

Signature Algorithm), ECDH (Elliptic Curve Diffie–

Hellman key exchange), and SHA (Secure Hash

Algorithm); these are defined in Security Suite 1.

In this paper, we develop a smart meter using a

hardware security module (HSM) that supports the

security mechanisms specified in Security Suite 1.

The smart meter developed in this research is based

on the open-source software GuruxDLMS.c (GuruX,

2022) with several modifications to enable it to run

on the Nuvoton M2354 hardware security module

(HSM); it is also tested for the implementations of

ECDSA with P-256, ECDH with P-256, and SHA-

256 using Conformance Test Tool version 3.1 (CTT

v3.1).

The rest of this paper is organized as follows.

Section II discusses related work on smart meters and

smart grids as well as their security issues. Section III

describes the testbed and test tool for our research.

Section IV provides more detail on how

GuruxDLMS.c was modified for invoking ECDSA,

ECDH, and SHA-256 functions implemented on the

Nuvoton M2354 HSM. Section V concludes our

research results.

2 RELATED WORK

A smart grid with large-scale integration of DER will

increase cyberattack surfaces. Qi et al. (2016) discuss

the cybersecurity issues of integrated DER and

propose a holistic attack-resilient framework to

protect the power grid. They also identify some

important attack scenarios against DER and suggest

that more research is needed to explore how trusted

platform modules (TPMs) and trusted execution

environments (TEEs) can be used in DER devices.

As a standard language for smart devices,

DLMS/COSEM specifies a data model, an

application-layer protocol, and media-specific

communication profiles for smart metering and

control across electricity, gas, heat energy, water, and

so on (DLMS User Association, 2022b). The

specifications for DLMS/COSEM are found in two

colored books, the so-called Blue Book and Green

Book. The COSEM object-oriented data model and

the object identification system (OBIS) are specified

in the Blue Book, whereas the application layer, the

lower layers, and the communication profiles are

specified in the Green Book. The latest versions of the

two books are Edition 14 for the Blue Book and

Edition 10 for the Green Book. The information

security features are defined in the Green Book.

Over 1500 DLMS-certified meter types are

currently used in more than 60 countries. We

therefore review several research results that pinpoint

the potential vulnerabilities in DLMS/COSEM

specifications.

Dantas et al. (2014) in an early paper, developed

an automated tool called eFuzz for security

assessments of DLMS/COSEM smart meters. The

security analysis is based on the specifications in the

DLMS/COSEM Green Book (Edition 7), in which

AES is the primary authenticated encryption

algorithm. Their experiments showed that eFuzz is an

effective tool for security inspections for smart

meters.

Mendes et al. (2018) developed an open-source

tool called ValiDLMS for validating and auditing

security of DLMS/COSEM implementations using

power-line communication. ValiDLMS consists of

three layers: the DLMS/COSEM environment,

interaction, and testing. The security analysis was

performed by employing fuzzing techniques and

vulnerability tests. Their experiments found security

flaws in the Low-Level Security (LLS)

implementation of the smart meter provided by their

industrial partner.

Luring et al. (2018) performed by-hand analyses

on security aspects of the Green Book (Edition 8).

They identified several vulnerabilities and suggested

some effective countermeasures. In the COSEM data

model, a smart meter acts as the server, and any

application acting as the client that needs to access the

smart meter should first establish an application

association (AA). Authentication is therefore very

important in the AA process. DLMS/COSEM defines

three security levels for authentication, namely No

Security, Low-Level Security (LLS), and High Level

Security (HLS). In HLS, five methods are provided:

MD1, SHA1, GMAC, SHA2, and ECDSA. The

authors in (Luring et al., 2018) suggested that

ECDSA provides the most secure authentication out

of these methods.

The widespread use of IoT devices raises great

concerns about cyber threats to resource-constrained

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devices. This results in more and more IoT devices

being implemented with hardware security modules

(HSMs). Sklavos et al. (2017) gave a comprehensive

introduction to hardware security in their edited book.

The authors describe the attacks such as fault attacks

and side-channel attacks and give some

countermeasures against those attacks. Physically

Unclonable Functions (PUFs) are also presented for

improving hardware security in the IC level.

Luo et al. (2022) proposed a security framework

for IoT devices using TrustZone-M-enabled MCUs

and presented security analysis for potential runtime

software security issues such as stack-based buffer

overflow (BOF) attack, return-oriented programming

attack, heap-based BOF attack, format string attack,

and attacks against non-secure callable functions.

Their experimental results showed that even though

the HSM-like ARM Cortex-M23 provides another

layer of security protection in hardware, any IoT

device developed using HSM without careful

programming could still suffer attacks against

vulnerabilities.

3 THE TESTBED AND TEST

TOOL

The testbed for our implementation consists of

Nuvoton NuMicro M2354 and Conformance Test

Tool (CTT) V. 3.1, as shown in Figure 1. It is a client-

server model in which the CTT serves as the client

and the smart meter is the server. A modified version

of the GuruX smart meter program is written in

M2354 to simulate a smart meter that uses a

cryptographic accelerator in M2354. In this section,

we describe the relevant features in Nuvoton

NuMicro M2354 and then discuss how the CTT was

used to test the smart meter.

3.1 Nuvoton NuMicro M2354

The NuMicro M2354 microcontroller is based on

Arm Cortex-M23. In addition to the built-in

TrustZone technology of the Arm v8-M architecture,

Figure 1: The testbed.

it also adds protection functions against side-channel

attacks and provides microcontroller platform

security hardware features that allow the application

system to easily realize data storage security,

software execution security, and message

communication security (Nuvoton NuMicro M2354 ,

2022). The cryptographic accelerator in M2354

includes a secure pseudo-random number generator

and supports AES, SHA, RSA, and ECC algorithms.

3.2 The Conformance Test Tool

The Conformance Test Tool (CTT) released by

DLMS UA is a software package that implements the

Abstract Test Suites (ATSs) as Executable Test Suites

(ETSs). CTT acts as a DLMS/COSEM test client

whereas Implementation Under Test (IUT) acts as a

DLMS/COSEM server. CTT allows the selection,

parametrization, and execution of the ETSs using the

information taken from the Conformance Test

Information (CTI) file and the information obtained

by CTT from IUT (DLMS User Association, 2022).

The CTT test report can be used to obtain the DLMS

UA Certification.

3.3 The Test Process and Conformance

Test Information

The conformance test process has three phases,

namely preparation, test operations, and test report.

The preparation phase involves preparation of IUT,

the production of the CTI, and the preparation of the

CTT. The test operations include review of the CTI,

test selection and parameterization, and one or more

“test campaigns” (DLMS User Association, 2018a).

A conformance test report and a log file will be

produced at the end of each test campaign.

The production of the CTI is an important step

before testing. The CTI includes an Implementation

Conformance Statement (ICS) that identifies

capabilities and options as implemented in IUT. It

also has information relating to IUT and its testing

environment, including addresses, timeouts, baud

rates, passwords, and so on.

Here we only show parts of the CTI settings, in

Figures 2 and 3. Figure 2 specifies the test options and

communication profile. As in Figure 1, CTT and

M2354 are connected using UART, while the High-

Level Data Link Control (HDLC) is used as the

communication protocol. Figure 3 shows some

security settings on the smart meter application layer.

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Figure 2: Test options and communication profile.

In Figure 3, we specify HLS_ECDSA as the

authentication mechanism and use the security

algorithms in Security Suite 1. We also specify the

Global Unicast Encryption Key (GUEK), Global

Authentication Key (GAK), Key Encrypting Key

(KEK), and some other key pairs not shown in the

figure.

4 IMPLEMENTATION DETAILS

USING HSM

The objective of this research is not to build a full-

fledged smart meter using a hardware security

module. Instead, we demonstrate the feasibility of

using a cryptographic accelerator within HSM to

provide more robust security features for smart

meters. In this section, we detail the modifications

made to the open-source software GuruxDLMS.c

such that the algorithms ECDSA with P-256, ECDH

Figure 3: Some security settings on the application layer.

with P-256, and SHA-256 provided by the HSM can

be invoked for smart meters.

In our implementation, we use Mbed Studio 1.2.1

and Keil uVision 5.31.0.0 (Nuvoton NuMicro

M2354, 2022) as the development tools and modify

GuruxDLMS.c with Version 20200911.1 (GuruX,

2022) for smart meters.

4.1 Modifications to Application

Association

Application association (AA) refers to a logical

connection between a client and a server. Establishing

an AA is the first step in accessing smart meter

services. AA is modelled by COSEM “Association

ShortName(SN)/LogicalName(LN)” objects that

hold the Service Access Points (SAPs) identifying the

associated partners, the name of the application

context, the name of the authentication mechanism,

and the xDLMS context. Authentication takes place

during AA establishment. Once the AA is established,

COSEM object attributes and methods can be

accessed using xDLMS services subject to the

security context and access rights specified in the

given AA (DLMS User Association, 2014).

During AA establishment, the CTT will send an

Association Request (AARQ) to the server, which

will reply with an Association Response (AARE).

Because the cip_crypt() function in src/ciphering.c

did not set the security control byte (SC) correctly, the

CTT cannot receive the AARE. The

Security_Suite_Id in SC should be changed to 1. With

this modification, an AA can be established correctly.

4.2 Modifications to SHA-256 in

GuruxDLMS.c

SHA-256 can be used as an HLS authentication

method in DLMS/COSEM; it is also used as hash

algorithm in ECDSA. But the implementation of

SHA-256 in GuruxDLMS.c is incomplete. We first

complete a correct version of SHA-256 for HLS

authentication. Two files, include/mbedsha256.h and

src/mbedsha256.c, are added to provide the crypto

function mbedsha256_encrypt(), which in turn uses

the API provided by M2354 to call the hardware

accelerator SHA256. Figures 4 and 5 show the

programs mbedsha256.h and mbedsha256.c,

respectively. In line 49 of Figure 5, the SHA256()

function of the hardware accelerator is enabled and

then invoked in line 56.

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Figure 4: Declaring the crypto function

mbedsha256_encrypt().

Figure 5: Defining the crypto function

mbedsha256_encrypt().

Figure 6: A successful HLS SHA-256 authentication.

To complete the AA using SHA-256, a client

needs to compute a hash value H1 on data M1,

sending these to the server for verification. Upon

receiving the messages M2 (rather than M1) and H1,

the server will compute a new hash value H2 on M2.

If H1 = H2, then M1 = M2, meaning that the client is

authenticated. Finally, the server will do the same for

the client to authenticate the server. When AA is

successfully established using SHA-256, CTI will

report “success” for the action response of the server,

as shown in Figure 6.

4.3 Modifictions to ECDH in

GuruxDLMS.c

ECDH is used for key agreement between client and

server, and the agreed key can be used in ECDSA for

authentication or in digital signature of COSEM data.

There are two crypto functions in ECDH:

getSharedSecret(), which computes the shared secret

Z, and the key derivation function

generateKeyKDF(), which generates the shared key.

These two functions can be implemented by invoking

ECC_GenerateSecretZ() in M2354, as in Figure 7.

Figure 7: Implementing ECDH using M2354.

4.4 Adding ECDSA as Authentication

Method to GuruxDLMS.c

As mentioned in Section II, HLS_ECDSA is the most

secure authentication method in DLMS/COSEM.

Table 1 shows the four passes of HLS_ECDSA

authentication (DLMS User Association, 2014). In

this subsection, we describe how ECDSA is

implemented using M2354 during AA.

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Table 1: The four passes of HLS_ECDSA Authentication

(DLMS User Association, 2014).

Legend:

- C: Client, S: Server, CtoS: Challenge client to server, StoC:

Challenge server to client

- xx.request / .response: xDLMS service primitives used to

access the reply_to_HLS authentication method of the

“Association SN / LN” object.

Figure 8: The server verifies the signature of the client.

In Pass 3, the client needs to generate its

authentication message and sign the message with its

private key using ECDSA. In Pass 4, the server first

verifies the received message from the client and then

generate its authentication message using ECDSA.

The processes of Pass 3 and Pass 4 are very similar,

so we only show the code for Pass 4.

Upon receiving the client's authentication

message, the server extracts the client's signature as

in lines 254–259 of Figure 8 and invokes

mbedecdsa_verify() in line 263 to verify the client.

After the client is verified, the server goes on to

generate its authentication message.

The server signs its signature by invoking

mbedecdsa_sign() as in Figure 9 and sends the

response to the client, which receives the correct

action response as in Figure 10.

The functions mbedecdsa_sign() and

mbedecdsa_verify() use the APIs provided by M2354

to call the hardware accelerators ECC_

GenerateSignature() and ECC_VerifySignature() in

M2354, respectively.

Figure 9: The server creates its signature.

Figure 10: The client verifies the server and gets the correct

action response.

Figure 11 shows the function mbedecdsa_sign().

In line 9, the hardware accelerator ECC is enabled.

The function mbedsha256_encrypt() defined in

Figure 5 is called in line 15 to compute the hash value,

and the function ECC_GenerateSignature() with

CURVE_P_256 specified as an argument is invoked

in line 41.

4.5 Adding General_ciphering() and

General_signing() to Protect

xDLMS APDU

An application protocol data unit (APDU) is a data

unit used by the application service of the DLMS

protocol with extensions (xDLMS). DLMS provides

two layers of protection to the APDU, signing and

ciphering. To apply encryption, authentication, or

authenticated encryption, the general-ciphering

APDU is used. To apply digital signature, the

general-signing APDU is used (DLMS User

Association, 2014). In our implementation, AES-

GCM-128 is the encryption algorithm for the general-

ciphering APDU. The client and the server need to

agree on a shared key for AES-GCM to encrypt and

decrypt the APDU. This is achieved by using the

ECDH algorithm in the general_ciphering() function.

For the general-signing APDU, the ECDSA

algorithm is used.

Suppose the client wants to read the value of one

COSEM object’s attributes. It will perform the

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following steps to create a GET-REQUEST service

APDU:

Figure 11: The function mbedecdsa_sign(), using hardware

accelerator.

1. use ECDSA to compute the signature of the client’s

request and generate a general-signing APDU;

2. use ECDH to get the agreed key;

3. use the agreed key to encrypt the general-signing

APDU;

4. send the general-ciphering APDU to the server.

Upon receiving the general-ciphering APDU of

the client, the server will perform the following steps

to generate a GET-RESPONSE APDU:

1. use ECDH to get the agreed key;

2. use the agreed key to decrypt the general-ciphering

APDU and get the general-ciphering APDU;

3. verify the signature of the client;

4. use ECDSA to compute the signature of the

server’s response and generate a general-signing

APDU;

5. use ECDH to get the agreed key;

6. use the agreed key to encrypt the general-signing

APDU and produce the general-ciphering APDU;

7. send the general-ciphering APDU to the client.

After receiving the general-ciphering APDU from

the server, the CTT successfully removes general

ciphering and general signing and verifies the

signature of the server.

4.6 Testing the Test Case

APPL_OPEN_1

The purpose of the test case APPL_OPEN_1 is to

verify that the implementation under test (IUT) is able

to establish an AA with the application context,

authentication mechanism, and xDLMS context

declared (DLMS User Association, 2018b).

APPL_OPEN_1 contains three subtests. Subtest 1 is

to establish an AA using the parameters declared,

returning PASSED if the AA is established. Subtest 2

is to check if the AA is in the associated state, in

which CTT issues a get-request command to read the

attributes of the Association LN object and tests the

protection of the APDU using the encryption and

authentication mechanisms declared. Subtest 3 is to

release the AA, returning FAILED if the procedure

fails. The test report shows that all three subtests with

HLS_ECDSA and Security Suite 1 declared are

passed.

5 CONCLUSIONS

Within the smart grid, smart meters can be thought of

as critical IoT devices in critical infrastructure. In a

world oriented toward net-zero energy

transformation, smart meters may be connected to

more and more services, resulting in increased

cyberattack surfaces.

In this research, we employ the hardware

accelerators of SHA-256, ECDH with P-256, and

ECDSA with P-256 in Nuvoton M2354 to provide

more secure authentication for smart meters. The

implementations are also tested using the

conformance test tool from DLMS UA. We anticipate

that in future development, smart meters will adopt

hardware security modules for more secure and

robust services.

It should be noted that ECDSA is a type of Public

Key Infrastructure (PKI) algorithm. The key pair of

each party should come from a trusted Certificate

Authority (CA). In our experiments, the key pairs of

client and server are embedded in the codes for easy

testing.

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ACKNOWLEDGEMENTS

This research was supported in part by the Taiwan

Information Security Center at NCHU

(TWISC@NCHU) and the Ministry of Science and

Technology, Taiwan, under grant numbers: MOST

109-2218-E-005-005 and MOST 111-2218-E-005-

006-MBK. The authors are very grateful to the

Taiwan Testing and Certification Center for

cooperation on testing smart meters using the

conformance test tool. We also like to express our

deep appreciation to Nuvoton Technology

Corporation for their technical support on NuMicro

M2354. Without the open-source project GuruX,

developing a smart meter program would be a huge

challenge. We owe many thanks to the many

contributors to the GuruX project.

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