CPA

CPA_AES_analyze(sample_function, leakage_model)

Performs a CPA attack against AES, where traces are collected from a specified function.

Arguments

• sample_function: single-argument function that takes an input AES input (MVector{16, UInt8}) and returns a power trace as an array of numbers for this input.
• leakage_model: a function reducing a processed value $R$ to their estimated side-channel emissions $W_R$

Returns

The recovered AES key

CPA_AES_analyze_manual(plaintexts::Vector, traces::Matrix, leakage_model)

Performs a CPA attack against AES on given traces.

Arguments

• plaintexts: A vector of size N, where N is the number of power traces sampled.
• traces: A matrix of size M * N, where M is the number of samples per trace. Power traces are stored in column-major order, i.e. it is expected that traces[:,i] refers to the powertrace generated with plaintexts[i]
• leakage_model: a function reducing a processed value $R$ to their estimated side-channel emissions $W_R$

Returns

The recovered AES key

CPA_AES_analyze_manual(plaintexts::Vector, traces::Matrix, power_estimate)

Performs a CPA attack against AES on given traces.

Arguments

• plaintexts: A vector of size N, where N is the number of power traces sampled.
• traces: A matrix of size M * N, where M is the number of samples per trace. Power traces are stored in column-major order, i.e. it is expected that traces[:,i] refers to the powertrace generated with plaintexts[i]
• power_estimate: A function that takes a plaintext::MVector{16, UInt6}, a key index (1 <= key_guess_index <= 16), and a key guess (0 <= key_guess <= 255) and returns an hypothesis on power consumption. For example, a classical implementation of this function for AES with Hamming weight would be power_estimate(plaintext, key_guess_index, key_guess) = Base.count_ones(AES.c_sbox[(plaintext[key_guess_index] ⊻ key_guess)+1])

CPA_SPECK_analyze(sample_function)

Performs a CPA attack against SPECK.

Arguments

• sample_function: a single-argument function that takes a SPECK input (Tuple{UInt64, UInt64}) and returns a power trace (array of numbers) for this input.
• leakage_model: a function reducing a processed value $R$ to their estimated side-channel emissions $W_R$
• N: the amount of traces to collect

Returns

The reconstructed SPECK key as a Tuple{UInt64, UInt64}

CPA_SPECK_analyze_traces(plaintexts::Vector, traces::Matrix, leakage_model)

Perform a CPA attack against SPECK on the provided traces.

Arguments

• plaintexts: A Vector of size N, where N is the number of power traces sampled.
• traces: A Matrix of size M * N, where M is the number of samples per trace.

Power traces are stored in column-major order, i.e. it is expected that traces[i,:] refers to the powertrace generated with plaintexts[i]

• leakage_model: a function reducing a processed value $R$ to their estimated side-channel emissions $W_R$

Returns

The reconstructed SPECK key as a Tuple{UInt64, UInt64}