Model-less Is the Best Model: Generating Pure Code Implementations to Replace On-Device DL Models

Keskeiset käsitteet

CustomDLCoder enhances DL model security and efficiency by generating pure code implementations to replace on-device DL models.

Tiivistelmä

The content discusses the challenges faced in securing on-device DL models and proposes CustomDLCoder as a solution. It outlines the process of extracting computing units, configuring data analysis, dynamic configuration, and compilation. The effectiveness of CustomDLCoder in defending against attacks, its efficiency in model inference compared to TFLite, and its memory consumption benefits are evaluated.
Abstract:

Recent studies highlight vulnerabilities in deployed on-device DL models.
CustomDLCoder is proposed to automatically extract on-device model information and synthesize executable programs.
The method improves security by hiding model information and enhances performance by removing unnecessary steps.
Introduction:

Mobile applications leverage DL capabilities but face security risks due to easily extractable models.
Traditional protection methods have limitations; CustomDLCoder aims to address these challenges.
Data Extraction:

"CustomDLCoder improves model security by disabling on-device model sniffing."
"Our method can accelerate model inference by 21.0% and 24.3% on x86-64 and ARM64 platforms."
"It can significantly reduce memory consumption by 68.8% and 36.0% on x86-64 and ARM64 platforms."

Tilastot

CustomDLCoder improves model security by disabling on-device model sniffing.
Our method can accelerate model inference by 21.0% and 24.3% on x86-64 and ARM64 platforms.
It can significantly reduce memory consumption by 68.8% and 36.0% on x86-64 and ARM64 platforms.

Lainaukset

"Our experimental results show that CustomDLCoder improves model security by disabling on-device model sniffing."
"Compared with the original TFLite platform, our method can accelerate model inference by 21.0% and 24.3% on x86-64 and ARM64 platforms."
"It can significantly reduce memory consumption by 68.8% and 36.0% on x86-64 and ARM64 platforms."

Tärkeimmät oivallukset

Model-less Is the Best Model

by Mingyi Zhou,... klo arxiv.org 03-26-2024

https://arxiv.org/pdf/2403.16479.pdf

Syvällisempiä Kysymyksiä

How does CustomDLCoder compare with other existing methods for securing DL models

CustomDLCoder outperforms other existing methods for securing DL models in several ways. Firstly, it provides a higher level of security by encoding model file information directly into the generated code and obfuscating this code to prevent easy identification of DL components. This approach effectively mitigates attacks that rely on parsing semantic information from model files or representations. In contrast, traditional methods like model obfuscation may introduce overheads and still leave the model representation vulnerable to certain types of attacks. Additionally, CustomDLCoder accelerates model inference compared to original TFLite models, making it more efficient in terms of performance.

What are the potential drawbacks or limitations of using pure code implementations for DL models

While using pure code implementations for DL models offers advantages in terms of security and efficiency, there are potential drawbacks and limitations to consider. One limitation is the complexity and manual effort required for extracting computing units from the DL library and configuring them into a complete program for diverse DL algorithms. This process can be challenging for large or complex models with numerous operators. Another drawback is that dynamic configurations may be needed for unknown status parameters which could increase computational complexity during deployment.

How might advancements in code obfuscation impact the effectiveness of CustomDLCoder in the future

Advancements in code obfuscation techniques could impact the effectiveness of CustomDLCoder positively in the future by enhancing its ability to secure DL models further. As code obfuscation methods evolve and become more sophisticated, they can provide additional layers of protection by concealing not only semantic information but also intricate details within the generated executable programs produced by CustomDLCoder. This enhanced level of obfuscation would make it even harder for attackers to reverse engineer or extract sensitive information from deployed on-device DL models secured using CustomDLCoder's pure code implementations.