The Uppsala Foundation aims to build Sentinel Protocol, a cybersecurity intelligence platform integrated with blockchain technology, to protect individuals’ cryptocurrency assets from frauds, hacks, & scams. Sentinel Protocol is for everyone because it can be integrated with exchanges (traditional & decentralized), payments, & wallets. The project emphasizes on using a Collective Intelligence System to generate a decentralized cybersecurity database that consists of comprehensive information on malicious threats. In order to keep a constantly updated pool of cybersecurity information; the Sentinel Protocol deploys The Sentinels, uses “sandboxing” technique to test & simulate attacks, & uses their Security Wallet (S-Wallet) which is infused with Machine Learning technology.

Sentinel Protocol can help prevent scams, like the one shown above, by utilizing The Sentinels & Machine (AI) Learning technology.

The Sentinels, also dubbed as the “International Cybercrime Police Force”, is a group of certified cybersecurity experts & white hat hackers whose job is to investigate & analyze attacks. They would then upload their findings on the Threat Reputation Database (TRDB), which is a transparent decentralized database that can be accessed by any individual, exchanges, organizations, etc. & is constantly, collaboratively updated in real-time. To prevent false or manipulated reports of attacks, Sentinels are incentivized based on their work’s merit with UPP tokens. Their work’s integrity is also measured through a reputation system.

Sentinel Protocol implements distributed-sandboxing, which is a method where an individual or Sentinel uses a remote virtual machine to simulate attacks and/or test programs or files that might contain malware. This technique prevents the individual’s system from being harmed because the untested program or file is quarantined from the rest of the host’s system. The findings in these tests are then analyzed & uploaded into TRDB to prevent and/or properly prepare for future attacks.

The project’s wallet (S-Wallet) is equipped with Machine Learning technology. Machine Learning uses an algorithm that keeps track of “normal” behavioral patterns & reports anomalies when detected. S-Wallet is also equipped with a filtering system that filters possible malicious URLs, malware, & wallet addresses. Once these features detects a potential threat; the threat would be flagged & a threat level would be determined, the threat is sent to Sentinels, & eventually is sent to the TRDB in order to alarm users about the scam addresses, corrupted files, or phishing website.