Maximum Utilization Multiple HORS (MUM-HORS): A Post-Quantum Hash-Based Signature Scheme for Heterogeneous IoT Systems

Conceitos essenciais

MUM-HORS is a new multiple-time, hash-based digital signature scheme designed for resource-constrained IoT devices, offering post-quantum security, fast signing, short signatures, and high key utilization for an extended lifespan.

Resumo

• Bibliographic Information: Sedghighadikolaei, K., Yavuz, A. A., & Nouma, S. E. (2024). Signer-Optimal Multiple-Time Post-Quantum Hash-Based Signature for Heterogeneous IoT Systems. Preprint submitted to peer-reviewed journal. arXiv:2411.01380v1 [cs.CR].
• Research Objective: This paper introduces MUM-HORS, a novel multiple-time hash-based signature scheme addressing the need for efficient and secure digital signatures in resource-constrained Internet of Things (IoT) devices facing threats from quantum computers.
• Methodology: The authors developed MUM-HORS based on the HORS signature scheme, incorporating a two-dimensional bitmap for efficient key management and an optimized weak message mitigation strategy. They evaluated MUM-HORS's performance on various hardware platforms, including an 8-bit AVR ATmega2560 microcontroller, a Raspberry Pi 4 with a Quad-core Cortex-A72, and a desktop computer with an Intel i9-11900K processor. The evaluation focused on signature generation and verification speed, signature size, private and public key sizes, and energy consumption.
• Key Findings: MUM-HORS demonstrates significant performance advantages over existing post-quantum signature schemes, particularly in signing speed and key utilization. It achieves up to 40 times better utilization with the same signing capacity compared to multiple-time HORS, while being significantly faster than NIST PQC-secure schemes like Dilithium and Falcon-512. MUM-HORS also maintains a compact key management data structure, ensuring its suitability for resource-constrained devices.
• Main Conclusions: MUM-HORS presents a practical and efficient solution for post-quantum secure digital signatures in heterogeneous IoT systems, particularly for applications prioritizing signer efficiency and long-term security, such as wearable medical devices. Its compact data structures, fast signing, and high key utilization make it well-suited for resource-limited IoT devices.
• Significance: This research contributes significantly to the field of lightweight cryptography by providing an efficient and practical post-quantum signature scheme tailored for the resource constraints of IoT devices. It addresses the growing need for secure communication in IoT while considering the emerging threat of quantum computers.
• Limitations and Future Research: The paper primarily focuses on signer-side optimization, relying on an offline/online public-key model where the verifier manages larger public keys. Future research could explore more balanced approaches or investigate the feasibility of MUM-HORS in resource-constrained verifier settings. Additionally, exploring the integration of MUM-HORS into existing IoT security frameworks and protocols would be beneficial.

Estatísticas

On an ARM Cortex A-72, MUM-HORS is 24x faster than Falcon-512 in signature generation.
On an ARM Cortex A-72, MUM-HORS is 200x faster than Dilithium-II in signature generation.
On an ARM Cortex A-72, MUM-HORS is 3900x faster than SPHINCS+ in signature generation.
MUM-HORS achieves up to 40x better key utilization compared to multiple-time HORS.
The size of MUM-HORS's key management data structure is limited to 1.4KB for a signing capacity of 220 signatures with 128-bit security.
Dilithium requires 113KB of storage on an ARM Cortex-M4.
Falcon-512 requires 117KB of storage on an ARM Cortex-M4.
MUM-HORS's verifier storage is 40x smaller than HORS.
MUM-HORS's signature size is 3x smaller than Dilithium-II.
MUM-HORS's signature size is 21x smaller than SPHINCS+.
MUM-HORS is 665x faster than XMSSMT in signature generation on a commodity device.
MUM-HORS is 118x faster than XMSSMT in signature verification on a commodity device.
MUM-HORS is 1.75x slower than HORS in signature generation on an ARM Cortex A-72.

Citações

"There is a significant need for lightweight PQ-secure digital signatures that respect the resource constraints of low-end IoTs."
"These features make MUM-HORS ideal multiple-time PQ-secure signature for heterogeneous IoTs."

Principais Insights Extraídos De

Signer-Optimal Multiple-Time Post-Quantum Hash-Based Signature for Heterogeneous IoT Systems

by Kiarash Sedg... às arxiv.org 11-05-2024

https://arxiv.org/pdf/2411.01380.pdf

Perguntas Mais Profundas

How will the increasing deployment of edge computing in IoT ecosystems impact the suitability of MUM-HORS, considering potential shifts in resource availability at the edge?

The increasing deployment of edge computing in IoT ecosystems presents both opportunities and challenges for MUM-HORS. Let's break down the potential impacts:
Opportunities:

Reduced reliance on cloud verifier: Edge computing brings computational resources closer to data sources. This could enable the deployment of more resourceful edge nodes capable of acting as verifiers for MUM-HORS signatures. This reduces the reliance on centralized cloud verifiers, potentially decreasing latency and improving system resilience.
Hierarchical verification: Edge computing facilitates hierarchical architectures. MUM-HORS's offline/online model could be adapted to a multi-tiered system where less resourceful devices offload verification to nearby edge nodes, which in turn, could interact with a central cloud verifier for final validation or aggregation.
Improved scalability: Edge computing enhances the scalability of IoT systems. MUM-HORS's focus on efficient signing for individual devices aligns well with this, enabling a larger number of devices to securely participate in the ecosystem.
Challenges:

Heterogeneity at the edge: Edge computing environments are inherently heterogeneous, with varying resource availability across nodes. This necessitates careful consideration when deploying MUM-HORS, ensuring that chosen edge verifiers possess sufficient resources for public key storage and verification operations.
Security of edge nodes: While edge nodes offer increased resources compared to constrained devices, they might not be as secure as well-protected cloud environments. This raises concerns if an edge verifier in MUM-HORS's model is compromised, potentially jeopardizing the authenticity and integrity of data.
Dynamic network topology: Edge computing environments often exhibit dynamic network topologies. This could disrupt the communication between signers and verifiers in MUM-HORS, requiring mechanisms for efficient discovery and handover of verification responsibilities.
Adaptation Strategies for MUM-HORS:

Flexible deployment: Design MUM-HORS implementations to be flexible, allowing deployment on various edge nodes with different resource capabilities.
Lightweight verification optimizations: Further research into optimizing the verification process for resource-constrained edge nodes could be beneficial.
Hybrid schemes: Explore hybrid approaches that combine MUM-HORS with other lightweight signature schemes or authentication mechanisms to adapt to varying resource constraints and security requirements at the edge.
In conclusion, the increasing adoption of edge computing in IoT ecosystems presents a mixed landscape for MUM-HORS. While it offers advantages like reduced reliance on cloud verifiers and improved scalability, challenges related to edge resource heterogeneity and security need careful consideration. Adapting MUM-HORS through flexible deployment, further optimization, and exploration of hybrid approaches will be crucial for its successful integration into evolving edge-centric IoT environments.

Could the reliance on a resourceful verifier in MUM-HORS's offline/online model potentially introduce new vulnerabilities, particularly in scenarios where the verifier's security is compromised?

Yes, the reliance on a resourceful verifier in MUM-HORS's offline/online model does introduce potential vulnerabilities, especially if the verifier's security is compromised. Here's a breakdown of the risks:
Vulnerabilities Stemming from Verifier Compromise:

Forgery of Signatures: If an attacker gains control of the verifier, they could potentially forge signatures for arbitrary messages. Since the verifier possesses the pre-computed public keys, a successful compromise grants the attacker the ability to generate valid signatures without knowledge of the signer's private key.
Denial of Service (DoS): An attacker could manipulate the verifier to reject legitimate signatures, disrupting the authentication process and causing a denial of service for legitimate signers.
Data Modification: Depending on the system's architecture and the extent of the verifier's role, a compromised verifier might be able to modify data without detection, as it can manipulate the verification process to accept tampered data as authentic.
Key Exposure: A compromised verifier could potentially expose the stored public keys. While this doesn't directly lead to the compromise of signer private keys, it could weaken the long-term security of the system, especially if an attacker can exploit weaknesses in the underlying hash function used in MUM-HORS.
Mitigating Risks Associated with Verifier Compromise:

Secure Verifier Infrastructure: Employ robust security measures to protect the verifier infrastructure, including strong access controls, intrusion detection systems, and regular security audits.
Distributed Verification: Instead of relying on a single verifier, explore distributed verification approaches where multiple entities participate in the verification process. This makes it significantly harder for an attacker to compromise a sufficient number of verifiers to forge signatures or manipulate data.
Threshold Cryptography: Implement threshold cryptography techniques where the verification process requires the participation of a threshold number of verifiers. This ensures that a single compromised verifier cannot single-handedly forge signatures or tamper with data.
Secure Enclaves: Consider utilizing secure enclaves (e.g., Intel SGX) or Trusted Execution Environments (TEEs) to isolate the verification process and protect the verifier's code and data from external access, even if the underlying operating system is compromised.
Trade-offs and Considerations:
It's important to acknowledge that implementing these mitigation strategies introduces trade-offs, often increasing complexity and potentially impacting performance. The choice of mitigation techniques should be based on a careful risk assessment, considering the specific security requirements and constraints of the target IoT application.
In summary, while MUM-HORS's offline/online model offers advantages in terms of signer efficiency, the reliance on a resourceful verifier introduces potential vulnerabilities if the verifier's security is compromised. Implementing appropriate mitigation strategies, such as secure verifier infrastructure, distributed verification, or secure enclaves, is crucial to address these risks and ensure the long-term security of the system.

If quantum-resistant blockchain technologies become prevalent in IoT, how might MUM-HORS's focus on efficient signing for individual devices need to adapt to the demands of securing transactions within a distributed ledger?

The rise of quantum-resistant blockchain technologies in IoT presents both interesting synergies and adaptation needs for MUM-HORS.
Synergies:

Shared Focus on Device Efficiency: Both MUM-HORS and quantum-resistant blockchains prioritize efficiency for resource-constrained devices. MUM-HORS achieves this through its lightweight signing process, while blockchain aims for lightweight participation in consensus mechanisms.
Complementary Security: MUM-HORS provides post-quantum security for individual data points, while quantum-resistant blockchains ensure the integrity and immutability of the entire ledger. This combination offers robust protection against both data tampering and unauthorized modifications to the transaction history.
Adaptation Needs for MUM-HORS:

Transaction-Level Signing: MUM-HORS, in its current form, focuses on signing individual data points. In a blockchain context, it needs adaptation to efficiently sign entire transactions, which may include multiple data fields, timestamps, and other relevant metadata.
Integration with Consensus Mechanisms: MUM-HORS would need to integrate seamlessly with the consensus mechanisms employed by the specific quantum-resistant blockchain. This might involve adapting the signature scheme to work with Proof-of-Work (PoW), Proof-of-Stake (PoS), or other consensus algorithms.
Scalability and Throughput: Blockchain systems often handle a high volume of transactions. MUM-HORS's efficiency would need to be assessed and potentially optimized to ensure it doesn't become a bottleneck for transaction throughput on the blockchain.
Key Management on the Blockchain: The offline/online model of MUM-HORS might require adjustments to fit within the decentralized framework of a blockchain. Securely managing and updating public keys on the blockchain while preserving the efficiency of the scheme would be crucial.
Potential Adaptation Strategies:

Batch Signing: Explore batch signing techniques to allow a single MUM-HORS signature to authenticate multiple transactions, potentially improving efficiency in high-throughput blockchain environments.
Lightweight Merkle Tree Integration: Integrate MUM-HORS with lightweight Merkle tree structures to enable efficient signing of transaction blocks, leveraging the blockchain's inherent Merkle tree properties for verification.
Decentralized Key Management: Investigate decentralized key management solutions that align with the blockchain's principles while ensuring the secure storage and update of MUM-HORS public keys.
Challenges and Considerations:

Complexity: Integrating MUM-HORS with quantum-resistant blockchains adds complexity to both the signature scheme and the blockchain implementation.
Standardization: The lack of standardized quantum-resistant blockchain technologies might pose challenges for interoperability and widespread adoption of MUM-HORS in such environments.
In conclusion, the prevalence of quantum-resistant blockchain technologies in IoT presents exciting opportunities for MUM-HORS. Adapting the scheme to efficiently sign transactions, integrate with consensus mechanisms, and address scalability concerns will be crucial for its successful deployment in blockchain-based IoT ecosystems. Further research and development efforts are needed to explore these adaptations and ensure MUM-HORS remains a viable and efficient post-quantum signature solution in the evolving landscape of secure and decentralized IoT systems.