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Trust or Bust: A Survey of Threats in Decentralized Wireless Networks

Hetvi Shastri, Akanksha Atrey, Andre Beck, Nirupama Ravi

TL;DR

The paper investigates security threats in decentralized wireless (DeWi) networks, where trust is not embedded by a central operator. It presents a taxonomy of adversarial behaviors spanning provider-, user-, and third-party-driven attacks, classified by confidentiality, integrity, and capacity impacts, and quantifies a case study showing provider-driven bandwidth throttling can dramatically boost profits. The authors review existing countermeasures, conclude they largely address confidentiality but not integrity or capacity, and advocate for trustless authentication and real-time performance verification. The work highlights critical security challenges in DeWi and calls for robust, generalizable defenses to enable secure, scalable decentralized connectivity.

Abstract

The recent emergence of decentralized wireless networks empowers individual entities to own, operate, and offer subscriptionless connectivity services in exchange for monetary compensation. While traditional connectivity providers have built trust over decades through widespread adoption, established practices, and regulation, entities in a decentralized wireless network, lacking this foundation, may be incentivized to exploit the service for their own advantage. For example, a dishonest hotspot operator can intentionally violate the agreed upon connection terms in an attempt to increase their profits. In this paper, we examine and develop a taxonomy of adversarial behavior patterns in decentralized wireless networks. Our case study finds that provider-driven attacks can potentially more than triple provider earnings. We conclude the paper with a discussion on the critical need to develop novel techniques to detect and mitigate adversarial behavior in decentralized wireless networks.

Trust or Bust: A Survey of Threats in Decentralized Wireless Networks

TL;DR

The paper investigates security threats in decentralized wireless (DeWi) networks, where trust is not embedded by a central operator. It presents a taxonomy of adversarial behaviors spanning provider-, user-, and third-party-driven attacks, classified by confidentiality, integrity, and capacity impacts, and quantifies a case study showing provider-driven bandwidth throttling can dramatically boost profits. The authors review existing countermeasures, conclude they largely address confidentiality but not integrity or capacity, and advocate for trustless authentication and real-time performance verification. The work highlights critical security challenges in DeWi and calls for robust, generalizable defenses to enable secure, scalable decentralized connectivity.

Abstract

The recent emergence of decentralized wireless networks empowers individual entities to own, operate, and offer subscriptionless connectivity services in exchange for monetary compensation. While traditional connectivity providers have built trust over decades through widespread adoption, established practices, and regulation, entities in a decentralized wireless network, lacking this foundation, may be incentivized to exploit the service for their own advantage. For example, a dishonest hotspot operator can intentionally violate the agreed upon connection terms in an attempt to increase their profits. In this paper, we examine and develop a taxonomy of adversarial behavior patterns in decentralized wireless networks. Our case study finds that provider-driven attacks can potentially more than triple provider earnings. We conclude the paper with a discussion on the critical need to develop novel techniques to detect and mitigate adversarial behavior in decentralized wireless networks.

Paper Structure

This paper contains 20 sections, 6 figures.

Figures (6)

  • Figure 1: A simplified view of DeWi networks.
  • Figure 2: Effect of reducing download bandwidth from 100Mbps on the provider's monetary benefits.
  • Figure 3: Effects of throttling bandwidth from 100Mbps to 50Mbps in random intervals of one, two, and three chunks.
  • Figure 4: Taxonomy of adversarial attacks in decentralized wireless networks.
  • Figure 5: Effect of reducing upload bandwidth from 100Mbps on the provider's monetary benefits.
  • ...and 1 more figures