Search arXivSearch

arXiv · 2207.14128

Analysis of Polkadot: Architecture, Internals, and Contradictions

Abstract

Polkadot is a network protocol launched in 2020 with the ambition of unlocking the full potential of blockchain technologies. Its novel multi-chain protocol allows arbitrary data to be transferred across heterogeneous blockchains, enabling the implementation of a wide range of novel use cases. The Polkadot architecture is based on the principles of sharding, which promises to solve scalability and interoperability shortcomings that encumber many existing blockchain-based systems. Lured by these impressive features, investors immediately appreciated the Polkadot project, which is now firmly ranked among the top 10 cryptocurrencies by capitalization (around 20 Billions USD). However, Polkadot has not received the same level of attention from academia that other proposals in the crypto domain have received so far, like Bitcoin, Ethereum, and Algorand, to cite a few. Polkadot architecture is described and discussed only in the grey literature, and very little is known about its internals. In this paper, we provide the first systematic study on the Polkadot environment, detailing its protocols, governance, and economic model. Then, we identify several limitations -- supported by an empirical analysis of its ledger -- that could severely affect the scalability and overall security of the network. Finally, based on our analysis, we provide future directions to inspire researchers to investigate further the Polkadot ecosystem and its pitfalls in terms of performance, security, and network aspects.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hanaa Abbas, Maurantonio Caprolu, Roberto Di Pietro. 2022-07-28. Analysis of Polkadot: Architecture, Internals, and Contradictions. https://arxiv.org/abs/2207.14128

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

KEEP EXPLORING

Related papers

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

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

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