276 lines
11 KiB
Python
276 lines
11 KiB
Python
# -*- coding: utf-8 -*-
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"""Final consistency check: every headline number vs its raw CSV.
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A quoted value that goes stale during a revision is the failure mode this
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guards against, so each assertion recomputes from data/ rather than from
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another quoted value. The manuscript-side assertions are skipped when
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main.tex is absent, which is the case in the reproducibility package.
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"""
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import csv
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import math
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import re
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from pathlib import Path
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base = Path(__file__).resolve().parents[1]
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_tex_path = base / "main.tex"
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HAVE_TEX = _tex_path.exists()
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tex = _tex_path.read_text(encoding="utf-8") if HAVE_TEX else ""
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def rows(name):
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with open(base / "data" / name) as f:
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return list(csv.DictReader(f))
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def col(name, k):
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return [float(r[k]) for r in rows(name) if r[k] != "nan"]
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ok = True
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def chk(label, cond, detail, needs_tex=False):
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global ok
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if needs_tex and not HAVE_TEX:
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print(" SKIP " + label + " :: main.tex not in this package")
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return
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print((" PASS " if cond else " FAIL ") + label + " :: " + detail)
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if not cond:
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ok = False
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print("headline numbers vs raw data")
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# --- Fig. 2: the proposal is below OMA -------------------------------
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sn = rows("sec_snr.csv")
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lg = [float(x["legit"]) for x in sn]
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om = [float(x["oma"]) for x in sn]
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rel = [(a - b) / b * 100 for a, b in zip(lg, om)]
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chk("legit below OMA at every SNR", max(rel) < 0, "max relative %+.2f%%" % max(rel))
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chk("gain 24 to 35 percent",
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round(-max(rel)) == 24 and round(-min(rel)) == 35,
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"%.2f to %.2f percent" % (-max(rel), -min(rel)))
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chk("24 and 35 in tex", "$24$ to\n$35$~percent" in tex or "$24$ to $35$~percent" in tex,
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"searched tex", needs_tex=True)
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ew = [float(x["eve_wrong"]) for x in sn]
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ch = float(sn[0]["chance"])
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dev = max(abs(x - ch) for x in ew)
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chk("outsider at chance to 3.5e-4", dev < 3.6e-4, "max deviation %.2e" % dev)
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chk("3.5e-4 in tex", "$3.5\\times10^{-4}$" in tex, "searched tex",
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needs_tex=True)
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# the main configuration's legitimate rate, the reference every later
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# assertion compares against; taken from the curve the main
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# configuration produced rather than looked up by key length
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MAIN_LEGIT = [float(x["legit"]) for x in sn if float(x["snr_db"]) == 10][0]
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chk("main legitimate 0.053", round(MAIN_LEGIT, 3) == 0.053,
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"%.4f" % MAIN_LEGIT)
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# --- Fig. 3: key-length ratio ----------------------------------------
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k = rows("sec_keylen.csv")
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r64 = [x for x in k if int(x["L"]) == 64][0]
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ratio = float(r64["oma"]) / float(r64["legit_ser"])
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chk("key-length ratio 1.52", round(ratio, 2) == 1.52, "%.4f" % ratio)
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chk("1.52 in tex", tex.count("1.52") >= 2, "%d occurrences" % tex.count("1.52"),
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needs_tex=True)
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chk("keys exactly orthogonal in the sweep",
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max(float(x["mask_xcorr"]) for x in k) < 1e-6,
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"max xcorr %.2e" % max(float(x["mask_xcorr"]) for x in k))
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# --- Fig. 4: jamming --------------------------------------------------
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g = col("sec_jam_gap.csv", "gap_db")
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chk("gap 10.1-11.1 dB", round(min(g), 1) == 10.1 and round(max(g), 1) == 11.1,
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"%.3f to %.3f" % (min(g), max(g)))
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lin = (10 ** (min(g) / 10), 10 ** (max(g) / 10))
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chk("more than ten times power", lin[0] > 10.0, "%.2f to %.2f" % lin)
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j = rows("sec_jam_cmp.csv")
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dmax = max(abs(float(r["blind"]) - float(r["perm_blind"])) for r in j)
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chk("within 0.002", dmax <= 0.002, "%.5f" % dmax)
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chk("no stale 8.1 dB", "$8.1$~dB" not in tex, "searched tex", needs_tex=True)
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# --- Fig. 6: brute force ---------------------------------------------
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b = rows("sec_brute_cmp.csv")
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sm = float(b[-1]["ser_mask"])
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chk("brute 0.67 at 1e6", round(sm, 2) == 0.67, "%.4f" % sm)
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chk("0.67 in tex", "$0.67$" in tex, "searched tex", needs_tex=True)
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closed = (ch - sm) / (ch - MAIN_LEGIT)
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chk("brute closes about a third", 0.30 < closed < 0.40, "%.3f" % closed)
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bf = float(b[-1]["best_frac"]) * 100
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chk("permutation 3.4 percent of positions", round(bf, 1) == 3.4, "%.2f" % bf)
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pad0 = next((x["K"] for x in b if float(x["ser_pad"]) < 0.1), None)
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chk("index cipher collapses at 65536", pad0 == "65536", str(pad0))
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# --- Fig. 7: known plaintext -----------------------------------------
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kp = rows("kpa.csv")
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legit = MAIN_LEGIT
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thr = legit * 1.02
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first20 = next((x["n_frames"] for x in kp
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if int(x["snr_db"]) == 20 and float(x["eve_ser"]) <= thr), None)
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first10 = next((x["n_frames"] for x in kp
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if int(x["snr_db"]) == 10 and float(x["eve_ser"]) <= thr), None)
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chk("KPA three frames at 20 dB", first20 == "3", "first N = %s" % first20)
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chk("KPA ten frames at 10 dB", first10 == "10", "first N = %s" % first10)
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kp0 = [x for x in kp if int(x["snr_db"]) == 0]
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w0 = float(kp0[-1]["eve_ser"]) / legit
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chk("0 dB no longer holds", w0 < 1.03, "64 frames reach %.3f of legitimate" % w0)
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pk = rows("pkpa.csv")
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p6 = float([x for x in pk if x["n_frames"] == "6"][0]["eve_ser"])
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chk("perm KPA at N=6 near its own legitimate",
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abs(p6 - MAIN_LEGIT) < 0.005, "%.4f" % p6)
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# --- refresh ----------------------------------------------------------
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rs = {x["scheme"]: x for x in rows("refresh_summary.csv")}
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chk("refresh 364.6 bits",
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round(float(rs["Invariant"]["entropy_bits"]), 1) == 364.6,
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"%.3f" % float(rs["Invariant"]["entropy_bits"]))
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chk("fixed key 23.8 bits",
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round(float(rs["None (fixed key)"]["entropy_bits"]), 1) == 23.8,
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"%.4f" % float(rs["None (fixed key)"]["entropy_bits"]))
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chk("invariant refresh free",
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abs(float(rs["Invariant"]["legit"]) - float(rs["None (fixed key)"]["legit"]))
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< 0.001, "%.4f vs %.4f" % (float(rs["Invariant"]["legit"]),
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float(rs["None (fixed key)"]["legit"])))
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# --- real tokens ------------------------------------------------------
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import json
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st = json.loads((base / "data" / "real_sec_stats.json").read_text())
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rec = st["recovery"]["28"]
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chk("headline recovery 96 vs 93 percent",
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round(rec["legit"] * 100) == 96 and round(rec["oma"] * 100) == 93,
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"%.1f vs %.1f" % (rec["legit"] * 100, rec["oma"] * 100))
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chk("legit leads OMA at every point",
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all(st["recovery"][s]["legit"] > st["recovery"][s]["oma"]
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for s in st["recovery"]),
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"checked %d points" % len(st["recovery"]))
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# --- the room argument of Fig. 2 and its evidence in Fig. 3 -----------
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kl = {int(r["L"]): r for r in rows("sec_keylen.csv")}
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r8 = kl[8]
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chk("L=8 crowding, proposal behind OMA",
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round(float(r8["legit_ser"]), 3) == 0.949
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and round(float(r8["oma"]), 3) == 0.685,
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"%.3f vs %.3f" % (float(r8["legit_ser"]), float(r8["oma"])))
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chk("0.949 and 0.685 in tex", "0.949" in tex and "0.685" in tex,
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"searched tex", needs_tex=True)
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# the OMA-to-proposed ratio the narration quotes
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sr = rows("sec_snr.csv")
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rt = [float(r["oma"]) / float(r["legit"]) for r in sr]
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chk("ratio spans 1.32 to 1.54", round(min(rt), 2) == 1.32
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and round(max(rt), 2) == 1.54, "%.3f to %.3f" % (min(rt), max(rt)))
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# the three secrets named in the setup
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chk("secret sizes: per-user direction, perm 256, pad 16",
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all(t in tex for t in ["length-$64$ key direction per user",
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"one permutation of $256$",
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"$16$ pad bits per user"]),
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"searched tex", needs_tex=True)
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chk("no stale d=64 configuration in tex",
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"$d=64$ real dimensions" not in tex and "$d/U=16$" not in tex,
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"searched tex", needs_tex=True)
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# Fig. 5 shows the permutation curve tracking the mask curve
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sc = rows("sec_sens_cmp.csv")
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dv = max(abs(float(r["ser_mask"]) - float(r["ser_perm"])) for r in sc)
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chk("permutation tracks mask in Fig. 5", dv < 0.06, "max gap %.3f" % dv)
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# --- the audit round's corrected quantities ---------------------------
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mf = {r["family"]: r for r in rows("sec_maskfam.csv")}
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fam_pct = (float(mf["random"]["legit_ser"])
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/ float(mf["hadamard"]["legit_ser"]) - 1) * 100
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chk("continuous family 29 percent worse", round(fam_pct) == 29,
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"%.1f percent" % fam_pct)
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chk("no stale 2.5 factor in tex", "factor of $2.5$" not in tex,
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"searched tex", needs_tex=True)
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sc2 = rows("sec_sens_cmp.csv")
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worst04 = min(min(float(r["ser_mask"]), float(r["ser_perm"]),
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float(r["ser_pad"])) for r in sc2
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if float(r["frac"]) <= 0.4)
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chk("all three above 0.95 to 40 percent of key", worst04 > 0.95,
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"min %.4f" % worst04)
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rf = rows("refresh.csv")
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res = max(1 - float(r["eve_invariant"]) for r in rf)
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chk("refresh residual below 2.4e-3", res < 2.4e-3, "max %.2e" % res)
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rk = rows("refresh_kpa.csv")
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nb = max(0.9999847412 - float(r["ser_next_block"]) for r in rk)
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chk("next block within 6e-4 of chance", nb < 6e-4, "max %.2e" % nb)
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bc = rows("sec_brute_cmp.csv")
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pm = min(float(r["ser_perm"]) for r in bc)
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chk("permutation floor 0.9996", pm > 0.9996, "min %.5f" % pm)
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md = {r["family"]: r for r in rows("maskdegen.csv")}
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ks = [int(x) for x in md["learned"]["support99_per_key"].split("/")]
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chk("learned keys degenerate: 5 to 8 of 64 entries",
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min(ks) == 5 and max(ks) == 8 and int(md["learned"]["L"]) == 64,
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md["learned"]["support99_per_key"])
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chk("learned support overlap 0.10",
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round(float(md["learned"]["mean_overlap"]), 2) == 0.10,
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md["learned"]["mean_overlap"])
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chk("degeneracy numbers in tex",
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"$5$ to $8$ of the $64$ entries" in tex
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and "overlapping by $0.10$ on average over user pairs" in " ".join(tex.split()),
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"searched tex", needs_tex=True)
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# --- why the permutation key is granted a shared permutation ---------
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pv = {r["variant"]: float(r["legit_ser"]) for r in rows("perm_variant.csv")}
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chk("shared permutation legitimate rate", abs(pv["shared"] - 0.053) < 1e-3,
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"%.5f" % pv["shared"])
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chk("per-user permutation legitimate rate",
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abs(pv["per_user"] - 0.129) < 1e-3, "%.5f" % pv["per_user"])
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if HAVE_TEX:
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chk("quoted permutation cost in tex",
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"from $0.053$ to $0.129$" in " ".join(tex.split()),
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"searched tex", needs_tex=True)
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# --- key-length sweep floor ------------------------------------------
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# The eavesdropper column is an average over eight substitute-key draws,
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# so the quoted floor must track the data and not one lucky draw.
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kl = rows("sec_keylen.csv")
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floor = min(float(r["eve_ser"]) for r in kl)
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chk("eavesdropper floor over key length", abs(floor - 0.9984) < 5e-4,
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"%.6f" % floor)
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if HAVE_TEX:
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chk("quoted eavesdropper floor in tex", "$0.9984$" in tex,
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"searched tex", needs_tex=True)
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# --- tables against their generator -----------------------------------
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# Every printed table cell must be the one make_tables.py derives from
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# data/, so a rerun that moves a number cannot leave the manuscript behind.
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if HAVE_TEX:
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import io
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import contextlib
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import make_tables
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buf = io.StringIO()
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with contextlib.redirect_stdout(buf):
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make_tables.compare_table()
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make_tables.maskfam_table()
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make_tables.refresh_tables()
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rows = [r.strip() for r in buf.getvalue().split("\n")
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if r.rstrip().endswith(r"\\")]
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flat = " ".join(tex.split())
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lost = [r for r in rows if " ".join(r.split()) not in flat]
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chk("table rows match the generator", not lost,
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"%d rows, %d missing" % (len(rows), len(lost)), needs_tex=True)
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for r in lost:
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print(" missing:", r[:78])
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# --- abstract ---------------------------------------------------------
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a = (tex.split(r"\begin{abstract}")[1].split(r"\end{abstract}")[0].strip()
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if HAVE_TEX else "")
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w = len(re.split(r"\s+", a)) if a else 0
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chk("abstract <= 250 words", w <= 250, "%d words" % w, needs_tex=True)
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chk("abstract has no abbreviations",
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not re.findall(r"\b[A-Z]{2,}\b", a), str(re.findall(r"\b[A-Z]{2,}\b", a)),
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needs_tex=True)
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print()
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print("ALL CONSISTENT" if ok else "INCONSISTENCIES FOUND")
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