web3_metadata_security
Web3 Rolled in on the Wave of Decentralization
Decentralized applications (DApps) grew by 74% in 2024 and individual wallets by 485%, with total value locked (TVL) in decentralized finance (DeFi) closing at a near-record high of $214 billion. However, the industry is heading straight for a state of capture if it does not wake up.
As Elon Musk has teased the idea of placing the US Treasury on blockchain—however poorly thought out—the tides are turning as crypto is deregulated. But when that happens, is Web3 ready to “protect [user] data,” as Musk’s surrogates pledge? If not, we are all on the brink of a global data security crisis.
Metadata is the New Frontier of Surveillance
The crisis boils down to a vulnerability at the heart of the digital world: the metadata surveillance of all existing networks, even the decentralized ones of Web3. AI technologies are now at the foundation of surveillance systems and serve as accelerants. Anonymity networks offer a way out of this state of capture. But this must begin with metadata protections across the board.
Metadata is the overlooked raw material of AI surveillance. Compared to payload data, metadata is lightweight and thus easy to process en masse. Here, AI systems excel. Aggregated metadata can reveal much more than encrypted contents: patterns of behaviors, networks of contacts, personal desires, and ultimately, predictability. And legally, it remains unprotected in many regions, unlike end-to-end (E2E) encrypted communications.
The Limits of Blockchain
Protecting the metadata of transactions was an afterthought of blockchain technology. Crypto does not offer full privacy despite its association with illicit trade. It allows the ability to hold tokens in a wallet with a chosen name.
“As all chain transactions are public, anyone running a full node can have a panoptic view of chain activity. Further, metadata like IP addresses attached to pseudonymous wallets can be used to identify people’s locations and identities if tracking technologies are sophisticated enough.” – Harry Halpin & Ania Piotrowska
This is the core problem of metadata surveillance in blockchain economics: Surveillance systems can effectively de-anonymize financial traffic by any capable party.
Knowledge is Also an Insecurity
Knowledge is not just power—it is also the basis on which we are exploited and disempowered. There are at least three general metadata risks across Web3:
- Fraud: The most serious hacks, thefts, or scams depend on accumulated knowledge about a target: their assets, transaction histories, and identities. DappRadar estimates a $1.3-billion loss due to “hacks and exploits” like phishing attacks in 2024 alone.
- Leaks: Wallets permitting access to decentralized tokenomics rely on leaky centralized infrastructures. Studies show the prevalence of IP leaks: “The existing wallet infrastructure is not in favor of users’ privacy. Websites abuse wallets to fingerprint users online, and DApps and wallets leak the user’s wallet address to third parties.”
- Chain consensus: A potential point of attack. Celestia, for example, is adding an anonymity layer to obscure validator metadata to prevent disruptions in its Data Availability Sampling (DAS) process.
Securing Web3 Through Anonymity
As Web3 continues to grow, so does the amount of metadata about people’s activities being offered up to newly empowered surveillance systems.
Beyond VPNs
VPN technology is decades old and has largely remained centralized. Networks like Tor and Dandelion offer decentralized solutions but remain vulnerable to surveillance by adversaries using “timing analysis” via control of entry and exit nodes.
Noise Networks
All surveillance looks for patterns in a network full of noise. By obscuring communication patterns and de-linking metadata like IPs from traffic-generated metadata, attack vectors can be reduced. Some VPNs, like Mullvad, have introduced programs like DAITA (Defense Against AI-guided Traffic Analysis), which seeks to add “distortion” to its VPN network.
Scrambling the Codes
Whether it is defending against future cyber threats or securing on-chain transactions, new anonymity networks are needed to scramble metadata, preventing it from being exploited.
The state of capture is already here. Machine learning is feeding off our data. Instead of leaving people’s data unprotected, Web3 and anonymity systems must ensure that what ends up in AI’s grasp is effectively garbage.
This article is for general information purposes and is not intended to be legal or investment advice. The views expressed here are the author’s alone and do not necessarily reflect those of Cointelegraph.
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