Distributed Ledger for Spammers' Resume

TitleDistributed Ledger for Spammers' Resume
Publication TypeConference Paper
Year of Publication2019
AuthorsMuttavarapu, A, Dantu, R, Thompson, M
Conference Name2019 IEEE Conference on Communications and Network Security (CNS)
Date PublishedJune
Keywordsblockchain, Peer-to-peer, Robocalls, smart contract, Spam detection
Abstract

Unsolicited, and most likely spoofed, robot calls are not just an annoyance, but also carry a potential threat with the onset of automation, impersonation, and even voice manipulation technologies as malicious elements attempt to use deception to steal sensitive information or invoke action. Despite steps taken to protect consumers, the issue appears to be far from under control. In this paper, we propose a solution to use blockchain as a platform to share spam transactions through a peer-to-peer mechanism that will maintain a global database of reported spam transactions in order to identify and trace spam activity effectively. Storing spam transactions on a distributed ledger with consensus-based approval of transactions adds reliability to the data and can optimize the data points that will be available to spam detection algorithms in order to fight spam effectively. As this is peer to peer-based sharing, there is no need to rely on third-party providers for storing and sharing this data to the users. Every spam call received will be added as a detailed transaction on the blockchain to execute a smart contract that will calculate the trustworthiness of the caller. Call records are used to identify spam transactions while the blockchain ledgers store this data. We discuss the relevance and advantages of a distributed ledger to store these transactions. This paper does not aim at solving the spam problem with an optimized detection algorithm but evaluates the characteristics and performance of the blockchain as a distributed ledger and its relevance to serve as a platform for peer-to-peer spam detection mechanisms. We evaluate different blockchain metrics like transaction processing rates, gas costs and ledger sizes and discuss how they scale in order to store the spam reports data on the blockchain.

DOI10.1109/CNS.2019.8802789

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