[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82779-en":3,"doc-seo-82779-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},82779,137441390410,"Hazel","https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984",8,"Research & Report","Energy-Aware System-Level Evaluation of Post-Quantum TLS on Embedded User Equipment over a Disaggregated 5G Network","Energy-Aware System-Level Evaluation of post-quantum security for next-generation mobile networks, focused on integrating NIST-standardized PQC into TLS handshakes over a disaggregated 5G architecture. The study evaluates classical and PQ signature/KEM combinations on Raspberry Pi 5 as embedded UE platforms using direct on-device power measurements. Experiments show a strong latency-energy coupling where execution time dominates energy cost; hash-based signatures cause up to 4× higher latency and 2× energy than lattice-based methods.","Energy-Aware System-Level Evaluation of Post-Quantum TLS on Embedded User Equipment over a Disaggregated 5G Network  \nSanzida Hoque, Abdullah Aydeger  \nFlorida Institute of Technology, Melbourne, FL, USA, 32901  \nEmails: shoque2023@my.fit.edu, aaydeger@fit.edu  \narXiv :2607 .03988v 1 [ cs .CR] 4 Jul 2026  \nAbstract—The transition to quantum-resistant security is a critical priority for the next generation of mobile networks, particularly within the disaggregated architecture of 5G. This paper presents an energy-aware system-level evaluation of PostQuantum Cryptography (PQC) integrated into the Transport Layer Security (TLS) handshake on embedded User Equipment (UE). Using Raspberry Pi 5s as representative embedded processing platforms, we evaluate the performance of NIST-standardized combinations of classical and post-quantum signature and key exchange mechanisms (KEM), incorporating direct on-device power measurements to estimate per-handshake energy consumption. Results experimentally validate a strong coupling between latency and energy consumption, indicating that execution time is the dominant contributor to energy cost. Hash-based signature schemes incur up to 4x higher latency and 2x energy compared to lattice-based alternatives, while the impact of KEMs is comparatively smaller. The analysis further reveals that overall system performance is primarily constrained by cryptographic computation and concurrency-induced contention rather than network transport effects. These findings provide practical guidance for PQC deployment in mobile environments and demonstrate that lattice-based signatures offer a more favorable balance between security, efficiency, and scalability for 5G systems.  \nIndex Terms—Post-quantum cryptography, TLS, 5G, user equipment, performance evaluation, testbed, energy efficiency, latency, embedded systems  \nI. INTRODUCTION  \nThe emergence of quantum computing poses a fundamental threat to widely deployed public-key cryptographic systems, including Rivest–Shamir–Adleman (RSA) and elliptic curve cryptography (ECC) . These schemes form the foundation of secure communication protocols such as Transport Layer Security (TLS), which are extensively used in modern cellular networks [1] . In 5G systems, secure communication between user equipment (UE), the radio access network, and the core infrastructure is essential for ensuring data confidentiality and integrity. Consequently, the transition to post-quantum cryptography (PQC) has become a critical requirement for futureproofing mobile communication systems [2] .  \nRecent standardization efforts by the National Institute of Standards and Technology (NIST) [3], [4] have identified several promising PQC algorithms, including lattice-based and hash-based schemes. While these algorithms provide resistance against quantum adversaries, they introduce additional computational complexity compared to classical approaches,  \nthis raises concerns regarding their deployment in resourceconstrained environments such as mobile devices, where latency, energy efficiency, and processing capability are tightly constrained.  \nExisting research on PQC performance has largely focused on isolated cryptographic benchmarks or protocol-level evaluations in controlled environments. While valuable, these studies often overlook system-level interactions in real-world deployments, including network stacks, protocol implementations, and device-level power consumption. In 5G, where strict performance and energy requirements must be met, these factors are crucial to assessing the practical feasibility of PQC adoption.  \nTo address this gap, this paper presents a system-level evaluation of PQC-enabled TLS handshakes on an end-to-end 5G testbed integrating embedded UE devices, an emulated NGRAN, and a standards-compliant 5G core. This setup enablesend-to-end experimentation under controlled yet representative conditions. Furthermore, the use of onboard power monitoring allows direct observat","cbCaifVhrGc5aej6","https://ap.wps.com/l/cbCaifVhrGc5aej6","pdf",5490853,1,9,"English","en",105,"# Introduction\n# Related Work\n# System Architecture and Design\n# Experimental Methodology, Results, and Discussion\n# Conclusion and Future Work","[{\"question\":\"What does the paper evaluate in relation to post-quantum security for 5G?\",\"answer\":\"It evaluates PQC-enabled Transport Layer Security (TLS) handshakes integrated into embedded user equipment within a disaggregated 5G network testbed.\"},{\"question\":\"How is energy consumption measured for the embedded UE during TLS handshakes?\",\"answer\":\"The study uses on-device power monitoring with PMIC measurements to estimate UE-side power and per-handshake energy without external instrumentation.\"},{\"question\":\"Which factor most strongly drives energy cost in the evaluated PQC-enabled TLS handshakes?\",\"answer\":\"Execution time is identified as the dominant contributor, showing a strong coupling between latency and energy 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does the paper evaluate in relation to post-quantum security for 5G?","Question",{"text":75,"@type":76},"It evaluates PQC-enabled Transport Layer Security (TLS) handshakes integrated into embedded user equipment within a disaggregated 5G network testbed.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is energy consumption measured for the embedded UE during TLS handshakes?",{"text":80,"@type":76},"The study uses on-device power monitoring with PMIC measurements to estimate UE-side power and per-handshake energy without external instrumentation.",{"name":82,"@type":73,"acceptedAnswer":83},"Which factor most strongly drives energy cost in the evaluated PQC-enabled TLS handshakes?",{"text":84,"@type":76},"Execution time is identified as the dominant contributor, showing a strong coupling between latency and energy 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