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Breaking the Black Box: Securing and Auditing Edge-Deployed LLMs via Shard Traceability
by
Gururaj Shinde,
Ritu Kuklani,
Varad Vishwarupe
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 27 |
| Year of Publication: 2025 |
| Authors: Gururaj Shinde, Ritu Kuklani, Varad Vishwarupe |
10.5120/ijca2025925483
|
Gururaj Shinde, Ritu Kuklani, Varad Vishwarupe . Breaking the Black Box: Securing and Auditing Edge-Deployed LLMs via Shard Traceability. International Journal of Computer Applications. 187, 27 ( Aug 2025), 44-49. DOI=10.5120/ijca2025925483
@article{
10.5120/ijca2025925483,
author = {
Gururaj Shinde,
Ritu Kuklani,
Varad Vishwarupe
},
title = { Breaking the Black Box: Securing and Auditing Edge-Deployed LLMs via Shard Traceability },
journal = {
International Journal of Computer Applications
},
issue_date = { Aug 2025 },
volume = { 187 },
number = { 27 },
month = { Aug },
year = { 2025 },
issn = { 0975-8887 },
pages = {
44-49
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume187/number27/breaking-the-black-box-securing-and-auditing-edge-deployed-llms-via-shard-traceability/
},
doi = { 10.5120/ijca2025925483 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-08-02T01:56:29.635261+05:30
%A Gururaj Shinde
%A Ritu Kuklani
%A Varad Vishwarupe
%T Breaking the Black Box: Securing and Auditing Edge-Deployed LLMs via Shard Traceability
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 27
%P 44-49
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract
EdgeShard represents a significant advancement in edge-based large language model (LLM) inference, enabling efficient, accurate, and privacy-preserving deployment by intelligently partitioning and scheduling computation across multiple edge devices. This collaborative approach outperforms traditional quantization and unstable cloud-edge methods. However, distributing inference across heterogeneous and potentially unreliable devices introduces new risks for robustness - such as increased vulnerability to device failures and attacks, and challenges for auditability, including fragmented execution logs and difficulties in tracing and verifying the end-to-end inference process.
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Index Terms
Computer Science
Information Sciences
Keywords