Initial commit

break_script/break_aes.jl

@@ -0,0 +1,20 @@
+#!/usr/bin/env julia
+
+include("util.jl")
+include("sbox.jl")
+include("plotutils.jl")
+
+function break_aes()
+    plaintexts = load_file("plaintexts.dat", UInt8)[1:10_000, :]
+    timings = load_file("timings.dat", UInt32)[1:10_000]
+    t_values = Vector{Float64}(undef, 0x100)
+    for key=0:0xFF
+        msb_set = (sbox[(plaintexts[:, 1] .⊻ key) .+ 1] .& 0x80) .!= 0
+        group_slow = timings[msb_set]
+        group_fast = timings[msb_set.==false]
+        t_values[key + 1] = t_val(group_fast, group_slow)
+    end
+    plot_discrete_tval(0:0xFF, t_values, "key")
+end
+
+@time break_aes()

break_script/parse_csv.jl

@@ -0,0 +1,42 @@
+#!/usr/bin/env julia
+
+import CSV
+using Formatting
+
+function parse_csv(filename)
+    println("Starting parsing")
+    data = CSV.read(filename, header=0)
+    println("Parsing done")
+    plaintexts::Matrix{UInt8} = convert(Matrix{UInt8}, data[:, 1:16])
+    timings::Matrix{UInt32} = convert(Matrix{UInt32}, data[:, 17:17])
+    write_data("plaintexts.dat", plaintexts)
+    write_data("timings.dat", timings)
+end
+
+function write_data(destination, data)
+    open(destination, "w") do file
+        field_size::UInt8 = sizeof(eltype(data))
+        rows::UInt64 = size(data, 1)
+        cols::UInt64 = size(data, 2)
+        write(file, field_size);
+        write(file, rows)
+        write(file, cols)
+        write(file, data)
+    end
+end
+
+function load_file(filename, type::Type{T})::Matrix{T} where T
+    open(filename, "r") do file
+        field_size = read(file, UInt8)
+        if field_size != sizeof(T)
+            throw(ArgumentError(format("Expected type of size {:d} but passed type '{}' has size {:d}", field_size, T, sizeof(T))))
+        end
+        rows = read(file, UInt64)
+        cols = read(file, UInt64)
+        data = Matrix{T}(undef, rows, cols)
+        read!(file, data)
+        return data
+    end
+end
+
+@time parse_csv("timing.csv")

break_script/plotutils.jl

@@ -0,0 +1,14 @@
+#!/usr/bin/env julia
+
+using Plots
+
+function plot_discrete_tval(index, t_values, xlabel; size=(800, 533))
+    t_plot = plot(index, t_values, legend=false, minorgrid=true, xlabel=xlabel, ylabel="t-value", size=size)
+    hline!(t_plot, [4.5])
+    return t_plot
+end
+
+function plot_power_measurements(index, t_values; size=(800, 533), color=:auto)
+    t_plot = plot(index, t_values, legend=false, minorgrid=true, xlabel="time", ylabel="power comsumption", size=size, color=color, linealpha=0.5, dpi=250)
+    return t_plot
+end

break_script/sbox.jl

@@ -0,0 +1,19 @@
+#!/usr/bin/env julia
+
+const sbox = [
+    0x63, 0x7c, 0x77, 0x7b, 0xf2, 0x6b, 0x6f, 0xc5, 0x30, 0x01, 0x67, 0x2b, 0xfe, 0xd7, 0xab, 0x76,
+    0xca, 0x82, 0xc9, 0x7d, 0xfa, 0x59, 0x47, 0xf0, 0xad, 0xd4, 0xa2, 0xaf, 0x9c, 0xa4, 0x72, 0xc0,
+    0xb7, 0xfd, 0x93, 0x26, 0x36, 0x3f, 0xf7, 0xcc, 0x34, 0xa5, 0xe5, 0xf1, 0x71, 0xd8, 0x31, 0x15,
+    0x04, 0xc7, 0x23, 0xc3, 0x18, 0x96, 0x05, 0x9a, 0x07, 0x12, 0x80, 0xe2, 0xeb, 0x27, 0xb2, 0x75,
+    0x09, 0x83, 0x2c, 0x1a, 0x1b, 0x6e, 0x5a, 0xa0, 0x52, 0x3b, 0xd6, 0xb3, 0x29, 0xe3, 0x2f, 0x84,
+    0x53, 0xd1, 0x00, 0xed, 0x20, 0xfc, 0xb1, 0x5b, 0x6a, 0xcb, 0xbe, 0x39, 0x4a, 0x4c, 0x58, 0xcf,
+    0xd0, 0xef, 0xaa, 0xfb, 0x43, 0x4d, 0x33, 0x85, 0x45, 0xf9, 0x02, 0x7f, 0x50, 0x3c, 0x9f, 0xa8,
+    0x51, 0xa3, 0x40, 0x8f, 0x92, 0x9d, 0x38, 0xf5, 0xbc, 0xb6, 0xda, 0x21, 0x10, 0xff, 0xf3, 0xd2,
+    0xcd, 0x0c, 0x13, 0xec, 0x5f, 0x97, 0x44, 0x17, 0xc4, 0xa7, 0x7e, 0x3d, 0x64, 0x5d, 0x19, 0x73,
+    0x60, 0x81, 0x4f, 0xdc, 0x22, 0x2a, 0x90, 0x88, 0x46, 0xee, 0xb8, 0x14, 0xde, 0x5e, 0x0b, 0xdb,
+    0xe0, 0x32, 0x3a, 0x0a, 0x49, 0x06, 0x24, 0x5c, 0xc2, 0xd3, 0xac, 0x62, 0x91, 0x95, 0xe4, 0x79,
+    0xe7, 0xc8, 0x37, 0x6d, 0x8d, 0xd5, 0x4e, 0xa9, 0x6c, 0x56, 0xf4, 0xea, 0x65, 0x7a, 0xae, 0x08,
+    0xba, 0x78, 0x25, 0x2e, 0x1c, 0xa6, 0xb4, 0xc6, 0xe8, 0xdd, 0x74, 0x1f, 0x4b, 0xbd, 0x8b, 0x8a,
+    0x70, 0x3e, 0xb5, 0x66, 0x48, 0x03, 0xf6, 0x0e, 0x61, 0x35, 0x57, 0xb9, 0x86, 0xc1, 0x1d, 0x9e,
+    0xe1, 0xf8, 0x98, 0x11, 0x69, 0xd9, 0x8e, 0x94, 0x9b, 0x1e, 0x87, 0xe9, 0xce, 0x55, 0x28, 0xdf,
+    0x8c, 0xa1, 0x89, 0x0d, 0xbf, 0xe6, 0x42, 0x68, 0x41, 0x99, 0x2d, 0x0f, 0xb0, 0x54, 0xbb, 0x16 ];

break_script/util.jl

@@ -0,0 +1,51 @@
+#!/usr/bin/env julia
+
+using Statistics
+
+function t_val(group_fast, group_slow)
+    if size(group_fast, 1) == 0 || size(group_slow, 1) == 0
+        return 0
+    end
+    mean_slow = mean(group_slow)
+    mean_fast = mean(group_fast)
+    s_slow = var(group_slow, mean=mean_slow)
+    s_fast = var(group_fast, mean=mean_fast)
+    return (mean_slow - mean_fast) / sqrt(s_slow / size(group_slow, 1) + s_fast / size(group_fast, 1))
+end
+
+function filter_peaks(data::Matrix{T})::Matrix{T} where T
+    m = mean(data, dims=2)
+    blocks = data .> m
+    blocks = hcat(.!blocks[:, 1], blocks)
+    is_edge = blocks[:, 1:end-1] .!= blocks[:, 2:end]
+    no_peaks = maximum([count(is_edge[row, :]) - 1 for row=1:size(data, 1)])
+    peaks = zeros(T, size(data, 1), no_peaks)
+    @Threads.threads for row_no=1:size(data, 1)
+        row = data[row_no, :]
+        separators = findall(is_edge[row_no, :])
+        for block_no=1:size(separators, 1)-1
+            lsep, rsep = separators[block_no:block_no+1]
+            bm = mean(row[lsep:rsep])
+            if bm > m[row_no]
+                peaks[row_no, block_no] = maximum(row[lsep:rsep])
+            else
+                peaks[row_no, block_no] = minimum(row[lsep:rsep])
+            end
+        end
+    end
+    return peaks
+end
+
+function load_file(filename, type::Type{T})::Matrix{T} where T
+    open(filename, "r") do file
+        field_size = read(file, UInt8)
+        if field_size != sizeof(T)
+            throw(ArgumentError(format("Expected type of size {:d} but passed type '{}' has size {:d}", field_size, T, sizeof(T))))
+        end
+        rows = read(file, UInt64)
+        cols = read(file, UInt64)
+        data = Matrix{T}(undef, rows, cols)
+        read!(file, data)
+        return data
+    end
+end