Implement TRNG attack
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d94acaa277
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2 changed files with 11 additions and 3 deletions
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@ -177,6 +177,14 @@
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"args": [],
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"args": [],
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"cwd": "${workspaceFolder:AES Intrinsic}",
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"cwd": "${workspaceFolder:AES Intrinsic}",
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"preLaunchTask": "Build AES Intrinsic Project"
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"preLaunchTask": "Build AES Intrinsic Project"
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},
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{
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"type": "python",
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"request": "launch",
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"name": "Run TRNG Attack",
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"program": "${workspaceFolder:TRNG Attack}/attack_student.py",
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"args": [],
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"cwd": "${workspaceFolder:TRNG Attack}"
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}
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}
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],
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],
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"compounds": []
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"compounds": []
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@ -14,14 +14,14 @@ if __name__ == '__main__':
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traces = np.reshape(traces, (traces.size//tracelen, tracelen)) # reshape of matrix, each row contains the trace for one RO
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traces = np.reshape(traces, (traces.size//tracelen, tracelen)) # reshape of matrix, each row contains the trace for one RO
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traces_bin = traces > 128 # conversion of waveforms to rectangles - everything below threshold is 0, otherwise 1 (they are boolean values actually)
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traces_bin = traces > 128 # conversion of waveforms to rectangles - everything below threshold is 0, otherwise 1 (they are boolean values actually)
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rising_edges = np.logical_not(traces[:,0:-2] & traces[:,1:-1]) & traces[:,2:] # finding rising edges, each rising edge is represented by True
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rising_edges = np.logical_not(traces_bin[:,0:-2]) & np.logical_not(traces_bin[:,1:-1]) & traces_bin[:,2:] # finding rising edges, each rising edge is represented by True
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cnt = np.count_nonzero(rising_edges, axis=1) # count the number of rising edges in rows
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cnt = np.count_nonzero(rising_edges, axis=1) # count the number of rising edges in rows
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# cnt is now a 1D vector
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# cnt is now a 1D vector
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cnt = cnt.reshape(TRNG_PAIR_CNT,2).min(axis=1) # Reshape of the count array into matrix, where each row contains 2 values - the number of rising edges for two ROs in a pair. Then we select the smaller value.
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cnt = cnt.reshape(TRNG_PAIR_CNT,2).min(axis=1) # Reshape of the count array into matrix, where each row contains 2 values - the number of rising edges for two ROs in a pair. Then we select the smaller value.
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#cnt_sel = cnt & ?x???? # select only the two least significant bits
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cnt_sel = cnt & 0x03 # select only the two least significant bits
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#estimate = ''.join([np.binary_repr(x, width=2) for x in cnt_sel]) # binary representation of the values (the last 2 bits) and joining them into one string
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estimate = ''.join([np.binary_repr(x, width=2) for x in cnt_sel]) # binary representation of the values (the last 2 bits) and joining them into one string
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print('{0:0>32x}'.format(int(estimate, 2)))
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print('{0:0>32x}'.format(int(estimate, 2)))
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print(trng_val) # from data_info, output of the RNG in FPGA
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print(trng_val) # from data_info, output of the RNG in FPGA
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