%% You should probably cite draft-helmprotocol-tttps-06 instead of this revision.
@techreport{helmprotocol-tttps-01,
    number =    {draft-helmprotocol-tttps-01},
    type =      {Internet-Draft},
    institution =   {Internet Engineering Task Force},
    publisher = {Internet Engineering Task Force},
    note =      {Work in Progress},
    url =       {https://datatracker.ietf.org/doc/draft-helmprotocol-tttps/01/},
    author =    {장동호},
    title =     {{The TLS TimeToken Secure Protocol (tttps://)}},
    pagetotal = 28,
    year =      ,
    month =     ,
    day =       ,
    abstract =  {This document specifies the TLS TimeToken Secure Protocol (tttps://), a protocol extension that augments TLS 1.3 {[}RFC8446{]} with cryptographically verifiable temporal ordering. Internet infrastructure assumes that channels are passive: noise is random and channel operators have no ordering preferences. This assumption is structurally violated when ordering has economic value -- NTP servers, BGP routing authorities, DNS resolvers, and transaction sequencers all have incentive to misrepresent ordering. This document formalises the problem as the Strategic Channel Controller Problem (SCCP), absent from classical information theory. Temporal ordering attacks are structurally more acute for autonomous AI agents than for human participants: as agent reaction times converge toward symmetry, ordering advantage can no longer be earned through superior human latency. No existing protocol -- including O(n\textasciicircum{}2) BFT consensus, which tolerates but does not eliminate Byzantine nodes -- provides a cryptographic pre-ingestion defense for this case. TTTPS introduces Proof-of-Time (PoT): a multi-source synthesised timestamp protected by the GRG integrity pipeline (Golomb-Rice -\textgreater{} Reed-Solomon -\textgreater{} Golay(23,12,7) -\textgreater{} HMAC), whose stage ordering is mathematically necessary (Theorems 1-3 of the companion paper {[}POT2026{]}). PoT achieves Byzantine temporal elimination at O(1) per record, independent of network size. An AdaptiveSwitch mechanism makes ordering manipulation economically self-defeating; the equilibrium threshold is derived in closed form and empirically calibrated from deployed data (Section 6.4). Deployment on Base Sepolia produces 70,000+ verified records; 55\% are generated by autonomous AI agents -- an unanticipated finding that confirms the structural severity of the ordering problem in agent economies. This document has Experimental status. The GRG pipeline specification will be published upon conclusion of pending patent proceedings (Section 12).},
}