An Approach for Safe and Secure Software Protection Supported by Symbolic Execution

• URL: http://arxiv.org/abs/2603.10608v1
• Date: Wed, 11 Mar 2026 10:14:37 GMT
• Title: An Approach for Safe and Secure Software Protection Supported by Symbolic Execution
• Abstract summary: We introduce a novel copy-protection method for industrial control software.<n>With our method, a program executes correctly only on its target hardware and behaves differently on other machines.
• Score: 1.5721850801772976
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We introduce a novel copy-protection method for industrial control software. With our method, a program executes correctly only on its target hardware and behaves differently on other machines. The hardware-software binding is based on Physically Unclonable Functions (PUFs). We use symbolic execution to guarantee the preservation of safety properties if the software is executed on a different machine, or if there is a problem with the PUF response. Moreover, we show that the protection method is also secure against reverse engineering.

Related papers

• Software-Hardware Binding for Protection of Sensitive Data in Embedded Software [0.0]
  We present a novel protection mechanism that combines hardware fingerprints with Boolean logic.<n>Unlike usual copy-protection approaches, unauthorised copies of the software still run on cloned devices but suboptimally.<n>Our approach does not require additional hardware, relying only on relatively simple updates to the software.
  arXiv  Detail & Related papers  (2026-03-12T09:33:42Z)
• Indirect Prompt Injections: Are Firewalls All You Need, or Stronger Benchmarks? [58.48689960350828]
  We show that a simple, modular and model-agnostic defense operating at the agent--tool interface achieves perfect security with high utility.<n>We employ a defense based on two firewalls: a Tool-Input Firewall (Minimizer) and a Tool-Output Firewall (Sanitizer)
  arXiv  Detail & Related papers  (2025-10-06T18:09:02Z)
• Automatic Selection of Protections to Mitigate Risks Against Software Applications [2.5874041837241304]
  This paper introduces a novel approach for the automated selection of software protections to mitigate MATE risks.<n>We formalize the key elements involved in protection decision-making and frame the protection process through a game-theoretic model.<n>We validate our approach through a proof-of-concept implementation and expert evaluations.
  arXiv  Detail & Related papers  (2025-06-23T10:11:23Z)
• Automated Hardware Logic Obfuscation Framework Using GPT [3.1789948141373077]
  We introduce Obfus-chat, a novel framework leveraging Generative Pre-trained Transformer (GPT) models to automate the obfuscation process. The proposed framework accepts hardware design netlists and key sizes as inputs, and autonomously generates obfuscated code tailored to enhance security.
  arXiv  Detail & Related papers  (2024-05-20T17:33:00Z)
• Secure Synthesis of Distributed Cryptographic Applications (Technical Report) [1.9707603524984119]
  We advocate using secure program partitioning to synthesize cryptographic applications. This approach is promising, but formal results for the security of such compilers are limited in scope. We develop a compiler security proof that handles subtleties essential for robust, efficient applications.
  arXiv  Detail & Related papers  (2024-01-06T02:57:44Z)
• DASICS White Paper: Enhancing Memory Protection with Dynamic Compartmentalization [7.552283050007595]
  We present the DASICS (Dynamic in-Address-Space Isolation by Code Segments) secure processor design.<n>It offers dynamic and flexible security protection across multiple privilege levels, addressing data flow protection, control flow protection, and secure system calls.<n>We have implemented hardware FPGA prototypes and software QEMU simulator prototypes based on DASICS, along with necessary modifications to system software for adaptability.
  arXiv  Detail & Related papers  (2023-10-10T09:05:29Z)
• Certifying LLM Safety against Adversarial Prompting [70.96868018621167]
  Large language models (LLMs) are vulnerable to adversarial attacks that add malicious tokens to an input prompt.<n>We introduce erase-and-check, the first framework for defending against adversarial prompts with certifiable safety guarantees.
  arXiv  Detail & Related papers  (2023-09-06T04:37:20Z)
• Approximate Model-Based Shielding for Safe Reinforcement Learning [83.55437924143615]
  We propose a principled look-ahead shielding algorithm for verifying the performance of learned RL policies. Our algorithm differs from other shielding approaches in that it does not require prior knowledge of the safety-relevant dynamics of the system. We demonstrate superior performance to other safety-aware approaches on a set of Atari games with state-dependent safety-labels.
  arXiv  Detail & Related papers  (2023-07-27T15:19:45Z)
• DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness [58.23214712926585]
  We develop a certified defense, DRSM (De-Randomized Smoothed MalConv), by redesigning the de-randomized smoothing technique for the domain of malware detection. Specifically, we propose a window ablation scheme to provably limit the impact of adversarial bytes while maximally preserving local structures of the executables. We are the first to offer certified robustness in the realm of static detection of malware executables.
  arXiv  Detail & Related papers  (2023-03-20T17:25:22Z)
• ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients [65.52888259961803]
  We introduce ROPUST, a simple and efficient method to leverage robust pre-trained models and increase their robustness. We test our method on nine different models against four attacks in RobustBench, consistently improving over state-of-the-art performance. We show that even with state-of-the-art phase retrieval techniques, ROPUST remains an effective defense.
  arXiv  Detail & Related papers  (2021-07-06T12:03:36Z)
• Quantum copy-protection of compute-and-compare programs in the quantum random oracle model [48.94443749859216]
  We introduce a quantum copy-protection scheme for a class of evasive functions known as " compute-and-compare programs" We prove that our scheme achieves non-trivial security against fully malicious adversaries in the quantum random oracle model (QROM) As a complementary result, we show that the same scheme fulfils a weaker notion of software protection, called "secure software leasing"
  arXiv  Detail & Related papers  (2020-09-29T08:41:53Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.