Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2408.10796

Honeyquest: Rapidly Measuring the Enticingness of Cyber Deception Techniques with Code-based Questionnaires

Mario Kahlhofer·Stefan Achleitner·Stefan Rass·René Mayrhofer
View original source ↗Read source document ↗Export metadata ↓

Abstract

Fooling adversaries with traps such as honeytokens can slow down cyber attacks and create strong indicators of compromise. Unfortunately, cyber deception techniques are often poorly specified. Also, realistically measuring their effectiveness requires a well-exposed software system together with a production-ready implementation of these techniques. This makes rapid prototyping challenging. Our work translates 13 previously researched and 12 self-defined techniques into a high-level, machine-readable specification. Our open-source tool, Honeyquest, allows researchers to quickly evaluate the enticingness of deception techniques without implementing them. We test the enticingness of 25 cyber deception techniques and 19 true security risks in an experiment with 47 humans. We successfully replicate the goals of previous work with many consistent findings, but without a time-consuming implementation of these techniques on real computer systems. We provide valuable insights for the design of enticing deception and also show that the presence of cyber deception can significantly reduce the risk that adversaries will find a true security risk by about 22% on average.

Explore related subjects

cs.CRcs.CY

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mario Kahlhofer, Stefan Achleitner, Stefan Rass, René Mayrhofer. 2024-08-20. Honeyquest: Rapidly Measuring the Enticingness of Cyber Deception Techniques with Code-based Questionnaires. https://doi.org/10.1145/3678890.3678897

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

MIRANDA: short signatures from a leakage-free full-domain-hash scheme

We present $\mathsf{Miranda}$, the first family of full-domain-hash signatures based on matrix codes. This signature scheme fulfils the paradigm of Gentry, Peikert and Vaikuntanathan ($\mathsf{GPV}$), which gives strong security guarantees. Our trapdoor is very simple and generic: if we propose it with matrix codes, it can actually be instantiated in many other ways since it only involves a subcode of a decodable code (or lattice) in a unique decoding regime of parameters. Though $\mathsf{Miranda}$ signing algorithm relies on a decoding task where there is exactly one solution, there are many possible signatures given a message to sign and we ensure that signatures are not leaking information on their underlying trapdoor by means of a very simple procedure involving the drawing of a small number of uniform bits. In particular $\mathsf{Miranda}$ does not use a rejection sampling procedure which makes its implementation a very simple task contrary to other $\mathsf{GPV}$-like signatures schemes such as $\mathsf{Falcon}$ or even $\mathsf{Wave}$. We instantiate $\mathsf{Miranda}$ with the famous family of Gabidulin codes represented as spaces of matrices and we study thoroughly its security (in the EUF-CMA security model). For~$128$ bits of classical security, the signature sizes are as low as~$90$ bytes and the public key sizes are in the order of~$2.6$ megabytes.

cs.CR↗
arXiv2026

SteganoBackdoor: Evading Data-Poisoning Defenses via Steganographic Backdoors

Transformer-based models are highly susceptible to backdoor attacks via supervised fine-tuning (SFT). To red-team existing data-poisoning defenses, prior work has increasingly focused on stylized triggers, synthetic artifacts, and token-level perturbations designed to evade detection. However, this trend has shifted threat models away from naturally occurring semantic triggers and realistic low-budget poisoning settings. Addressing this gap, we introduce SteganoBackdoor, an optimization-based framework that transforms semantic-trigger seeds through autoregressive token replacement, sequentially minimizing embedding overlap with the inference-time trigger while preserving a strong per-sample training-time payload. The resulting SteganoPoisons maintain linguistic fluency and encode the payload across ordinary tokens, such that no individual token carries a concentrated signal and the full payload instead emerges from their exact combination and ordering. Across 18 encoder-based and decoder-only models spanning 120M to 14B parameters, SteganoBackdoor achieves high attack success under sub-percent poisoning budgets and exposes limitations in existing data-poisoning defenses.

cs.CR↗
arXiv2026

Foundations and Design Principles of Lightweight Cryptography for IoT Systems

The successful deployment of the Internet of Things (IoT) applications relies heavily on their robust security, and lightweight cryptography is considered an emerging solution in this context. While existing surveys have been examining lightweight cryptographic techniques from the perspective of hardware and software implementations or performance evaluation, there is a significant gap in addressing different security aspects, such as design principles, specific to the IoT environment. This study aims to bridge this gap. This research presents an examination with focusing on the security evaluation of symmetric lightweight ciphers commonly used in IoT systems. The objective of this study is to provide a concise overview of lightweight ciphers with emphasizing on their security challenges which is an essential consideration for real-time and resource-constrained applications.

cs.CR↗