Man-At-The-End attacks

We describe a side-channel attack on a substitution block, which is usually implemented as a table lookup operation. In particular, we have investigated smartcard implementations. The attack is based on the identifying equal intermediate results from power measurements while the actual values of these intermediates remain unknown. A powerful attack on substitution blocks can be mounted if the same table is used in multiple iterations and if cross-iteration comparisons are possible. Adversaries can use the method as a part of reverse engineering tools on secret algorithms. In addition to the described method, other methods have to be employed to completely restore the algorithm and its accompanying secret key. We have successfully used the method in a demonstration attack on a secret authentication and session-key generation algorithm implemented on SIM cards in GSM networks. The findings provide guidance for designing smartcard solutions that are secure against this kind of attack.

Side-channel attack on substitution blocks

The invention provides a hardware Trojan horse detection method and a hardware Trojan horse detection system. The method includes the following steps: collecting a by-pass signal of a to-be-detected integrated circuit; extracting features of the by-pass signal to form a feature collection; calculating mahalanobis distance values, including a mahalanobis value of a reference integrated circuit and a mahalanobis value of the to-be-detected integrated circuit, of the feature collection; comparing the mahalanobis value of the reference integrated circuit with that of the to-be-detected integrated circuit, and performing hardware Trojan horse detection according to a comparison result. By the hardware Trojan horse detection method and the hardware Trojan horse detection system which have the advantages of simple algorithm and short detection time, distinguishability and efficiency of hardware Trojan horse detection in integrated circuit testing are effectively improved, and any cost for hardware is not generated.

Hardware Trojan horse detection method and hardware Trojan horse detection system

The invention provides an integrated circuit hardware Trojan horse detection method and system. The method includes acquiring bypass information training samples of Trojan horse chips and non Trojan horse chips in the set numbers; performing main component analysis on the bypass information training samples of the non Trojan horse chips to acquire k-dimensional principal eigenvectors; calculating the feature projection of a chip to be detected of bypass information vectors of the chip to be detected on the k-dimensional principal eigenvectors of the non Trojan horse chips and the Trojan horse chip feature projection and non Trojan horse chip feature projection of the bypass information training samples of the Trojan horse chips and non Trojan horse chips on the k-dimensional principal eigenvectors of the non Trojan horse chips respectively; if K 3, judging the chip to be detected to be a Trojan horse chip or non Trojan horse chip according to the mahalanobis distance. The method is adaptive to the characteristic of uncertainty of the data dimension, the Trojan horse chip and non Trojan horse chip can be identified accurately, and the integrated circuit pattern identifying capability and efficiency are improved.

Integrated circuit hardware Trojan horse detection method and system

The invention provides a hardware Trojan horse recognition method based on a neural network. The problem that an existing recognition method does not need manual observation and is low in efficiency is solved, and recognition intelligentization of a hardware Trojan horse chip is achieved. The method comprises the following steps of first obtaining side channel information of a chip to be detected and performing data pre-processing; selecting a part of the chip to be detected to perform back subdivision analysis and confirming whether a back subdivision chip contains hardware Trojan horse or not; utilizing the back subdivision chip which does not contain the hardware Trojan horse to build a chip characteristic space through pro-processed side channel information; projecting all of chips to be detected into the characteristic space through a pro-processed side channel information matrix to obtain a side channel information characteristic data matrix; utilizing side channel information characteristic data of the back subdivision chip and a corresponding target output value to build and train the neural network; delivering the side channel information characteristic data of a tested chip to the trained neural network to be distinguished and output and achieving hardware Trojan horse recognition.

Hardware Trojan horse recognition method based on neural network

The invention relates to a characteristic value processing method for hardware Trojan detection without a clean circuit board for comparison. A system is established for processing characteristic values acquired for hardware Trojan detection, and accordingly abnormal data are detected without the clean circuit board for comparison. Moreover, the method provides two selectable detection schemes which are a model-free detection scheme and a model detection scheme respectively, wherein the model-free detection scheme includes the steps of circularly calling various parameters (including distance functions and a classification method) by the aid of an unsupervised clustering method to obtain a clustering-based strategy highest in evaluation function, and then classifying, the model-free detection scheme is high in speed, and the precision already meet primary demand; and the model detection scheme uses a unsupervised neural network algorithm which is low in speed but high in precision, serves as an selection of the detection schemes but is not necessary, and is applicable to situations high in requirement on precision.

Characteristic value processing method for hardware Trojan detection

The invention relates to a hardware Trojan horse detection system based on puf. The system adds the puf into a plurality of modules of an integrated chip (IC) in an original IC design file, sends the IC design file with the puf to a factory for production, performs data acquisition on an IC sample produced by the factory according to the IC design file with the puf under a test mode, analyzes the acquired data through a data analysis module and outputs a judgment result; and a user judges whether the original IC design in an original data storage module is modified according to original data judged by a data judgment module and judges whether to put the original data into production. The hardware Trojan horse detection system has the advantages that the shortcomings that the conventional detection method is complicated, high in test cost and long in time period, and the original design or the original IC is needed are overcome; whether hardware Trojan horses are contained can be stably and effectively detected; naturally, the fact that the Trojan horses are very difficult to trigger is not considered; the Trojan horses are detected physically; and therefore, most hardware Trojan horses can be detected.

Hardware Trojan horse detection system based on puf

The recent cryptanalysis on block ciphers has two major trends. Side channel analysis SCA has become a new threat to the hardware implementations of encryption algorithms. On the other hand, reverse engineering has been adopted to explore the unknown part of the encryption algorithms, which has become a new target of the cryptanalysis. Some drawbacks have been found in the existing methods of reverse engineering, which target on the special structures or utilize the flaws in the unknown parts. The major disadvantage is that the number of rounds to be analyzed is limited, and the complexity is high. The existing SCAs for reverse engineering depend on the leakage models in a large extent and mainly focus on the single component of the algorithms, whereas the other parts of the target algorithm are known. In this paper, we present a more general and feasible reverse analysis by combining the mathematical methods and the SCA methods. We use the strict avalanche criterion for the non-linear operations of block ciphers and apply the power analysis to reverse the structure parameters. We propose a new reverse analysis method to reduce the dependency on the leakage models, which can be combined with the structural cryptanalysis to reverse the internal parameters of the linear and non-linear operations. We finally achieve the reverse analysis on the unknown round function of block ciphers. Copyright © 2013 John Wiley & Sons, Ltd.

Power analysis based reverse engineering on the secret round function of block ciphers

The invention relates to a sensitive element device for a bypass signal of a sensing circuit and a detection method of the sensitive element device. The sensitive element device mainly comprises a shell, a counting module which is arranged in the shell, a sensing module which is connected with the counting module, an input port and an output module, which are connected with the counting module, and an interaction control port which is connected with the sensing module, wherein the counting module is mainly used for converting an output waveform of a sensing part into a characteristic value and outputting the characteristic value; the interaction control port is a connection device of a sensitive element for circuit reaction characteristic; a port comprises input and output external ports; the input external port controls the working state of the sensitive element; the output external port outputs the characteristic value which is acquired by the sensitive element; and the sensing module is a core part, employs a ring oscillator and a delayer and is mainly embodied in the output waveform of a certain point of the circuit. The electrical characteristic of the circuit can be conveniently obtained without an additional test tool, the obtained characteristic value is stable and non-fluctuant, and a great number of labor resources and material resources are saved.

Sun Weijin

Papers

Characteristic value processing method for hardware Trojan detection

Hardware Trojan horse detection system based on puf

Power analysis based reverse engineering on the secret round function of block ciphers

Sensitive element device for bypass signal of sensing circuit and detection method of sensitive element device