Hardware Trojan(HT) refers to a special module intentionally implanted into a chip or an electronic system. The module can be exploited by the attacker to achieve destructive functions. Unfortunately the HT is difficu...Hardware Trojan(HT) refers to a special module intentionally implanted into a chip or an electronic system. The module can be exploited by the attacker to achieve destructive functions. Unfortunately the HT is difficult to detecte due to its minimal resource occupation. In order to achieve an accurate detection with high efficiency, a HT detection method based on the electromagnetic leakage of the chip is proposed in this paper. At first, the dimensionality reduction and the feature extraction of the electromagnetic leakage signals in each group(template chip, Trojan-free chip and target chip) were realized by principal component analysis(PCA). Then, the Mahalanobis distances between the template group and the other groups were calculated. Finally, the differences between the Mahalanobis distances and the threshold were compared to determine whether the HT had been implanted into the target chip. In addition, the concept of the HT Detection Quality(HTDQ) was proposed to analyze and compare the performance of different detection methods. Our experiment results indicate that the accuracy of this detection method is 91.93%, and the time consumption is 0.042s in average, which shows a high HTDQ compared with three other methods.展开更多
Traffic hijacking is a common attack perpetrated on networked systems, where attackers eavesdrop on user transactions, manipulate packet data, and divert traffic to illegitimate locations. Similar attacks can also be ...Traffic hijacking is a common attack perpetrated on networked systems, where attackers eavesdrop on user transactions, manipulate packet data, and divert traffic to illegitimate locations. Similar attacks can also be unleashed in a NoC (Network on Chip) based system where the NoC comes from a third-party vendor and can be engrafted with hardware Trojans. Unlike the attackers on a traditional network, those Trojans are usually small and have limited capacity. This paper targets such a hardware Trojan;Specifically, the Trojan aims to divert traffic packets to unauthorized locations on the NoC. To detect this kind of traffic hijacking, we propose an authentication scheme in which the source and destination addresses are tagged. We develop a custom design for the packet tagging and authentication such that the implementation costs can be greatly reduced. Our experiments on a set of applications show that on average the detection circuitry incurs about 3.37% overhead in area, 2.61% in power, and 0.097% in performance when compared to the baseline design.展开更多
To generate test vector sets that can efficiently activate hardware Trojans and improve probability of the hardware Trojan activation,an efficient hardware Trojan activation method is proposed based on greedy algorith...To generate test vector sets that can efficiently activate hardware Trojans and improve probability of the hardware Trojan activation,an efficient hardware Trojan activation method is proposed based on greedy algorithm for combinatorial hardware Trojans. Based on the greedy algorithm and the recursive construction method in the combination test,the method formulates appropriate and useful greedy strategy and generates test vector sets with different combinatorial correlation coefficients to activate hardware Trojans in target circuits. The experiment was carried out based on advanced encryption standard（ AES） hardware encryption circuit,different combinatorial hardware Trojans were implanted in AES as target circuits,the experiment of detecting hardware Trojans in target circuits was performed by applying the proposed method and different combinatorial hardware Trojans in target circuits were activated successfully many times in the experiment. The experimental results showthat the test vector sets generated using the proposed method could effectively activate combinatorial hardware Trojans,improve the probability of the hardware Trojan being activated,and also be applied to practice.展开更多
Hardware Trojans(HTs)have drawn increasing attention in both academia and industry because of their significant potential threat.In this paper,we propose HTDet,a novel HT detection method using information entropybase...Hardware Trojans(HTs)have drawn increasing attention in both academia and industry because of their significant potential threat.In this paper,we propose HTDet,a novel HT detection method using information entropybased clustering.To maintain high concealment,HTs are usually inserted in the regions with low controllability and low observability,which will result in that Trojan logics have extremely low transitions during the simulation.This implies that the regions with the low transitions will provide much more abundant and more important information for HT detection.The HTDet applies information theory technology and a density-based clustering algorithm called Density-Based Spatial Clustering of Applications with Noise(DBSCAN)to detect all suspicious Trojan logics in the circuit under detection.The DBSCAN is an unsupervised learning algorithm,that can improve the applicability of HTDet.In addition,we develop a heuristic test pattern generation method using mutual information to increase the transitions of suspicious Trojan logics.Experiments on circuit benchmarks demonstrate the effectiveness of HTDet.展开更多
基金supported by the Special Funds for Basic Scientific Research Business Expenses of Central Universities No. 2014GCYY0the Beijing Natural Science Foundation No. 4163076the Fundamental Research Funds for the Central Universities No. 328201801
文摘Hardware Trojan(HT) refers to a special module intentionally implanted into a chip or an electronic system. The module can be exploited by the attacker to achieve destructive functions. Unfortunately the HT is difficult to detecte due to its minimal resource occupation. In order to achieve an accurate detection with high efficiency, a HT detection method based on the electromagnetic leakage of the chip is proposed in this paper. At first, the dimensionality reduction and the feature extraction of the electromagnetic leakage signals in each group(template chip, Trojan-free chip and target chip) were realized by principal component analysis(PCA). Then, the Mahalanobis distances between the template group and the other groups were calculated. Finally, the differences between the Mahalanobis distances and the threshold were compared to determine whether the HT had been implanted into the target chip. In addition, the concept of the HT Detection Quality(HTDQ) was proposed to analyze and compare the performance of different detection methods. Our experiment results indicate that the accuracy of this detection method is 91.93%, and the time consumption is 0.042s in average, which shows a high HTDQ compared with three other methods.
文摘Traffic hijacking is a common attack perpetrated on networked systems, where attackers eavesdrop on user transactions, manipulate packet data, and divert traffic to illegitimate locations. Similar attacks can also be unleashed in a NoC (Network on Chip) based system where the NoC comes from a third-party vendor and can be engrafted with hardware Trojans. Unlike the attackers on a traditional network, those Trojans are usually small and have limited capacity. This paper targets such a hardware Trojan;Specifically, the Trojan aims to divert traffic packets to unauthorized locations on the NoC. To detect this kind of traffic hijacking, we propose an authentication scheme in which the source and destination addresses are tagged. We develop a custom design for the packet tagging and authentication such that the implementation costs can be greatly reduced. Our experiments on a set of applications show that on average the detection circuitry incurs about 3.37% overhead in area, 2.61% in power, and 0.097% in performance when compared to the baseline design.
文摘To generate test vector sets that can efficiently activate hardware Trojans and improve probability of the hardware Trojan activation,an efficient hardware Trojan activation method is proposed based on greedy algorithm for combinatorial hardware Trojans. Based on the greedy algorithm and the recursive construction method in the combination test,the method formulates appropriate and useful greedy strategy and generates test vector sets with different combinatorial correlation coefficients to activate hardware Trojans in target circuits. The experiment was carried out based on advanced encryption standard（ AES） hardware encryption circuit,different combinatorial hardware Trojans were implanted in AES as target circuits,the experiment of detecting hardware Trojans in target circuits was performed by applying the proposed method and different combinatorial hardware Trojans in target circuits were activated successfully many times in the experiment. The experimental results showthat the test vector sets generated using the proposed method could effectively activate combinatorial hardware Trojans,improve the probability of the hardware Trojan being activated,and also be applied to practice.
文摘Hardware Trojans(HTs)have drawn increasing attention in both academia and industry because of their significant potential threat.In this paper,we propose HTDet,a novel HT detection method using information entropybased clustering.To maintain high concealment,HTs are usually inserted in the regions with low controllability and low observability,which will result in that Trojan logics have extremely low transitions during the simulation.This implies that the regions with the low transitions will provide much more abundant and more important information for HT detection.The HTDet applies information theory technology and a density-based clustering algorithm called Density-Based Spatial Clustering of Applications with Noise(DBSCAN)to detect all suspicious Trojan logics in the circuit under detection.The DBSCAN is an unsupervised learning algorithm,that can improve the applicability of HTDet.In addition,we develop a heuristic test pattern generation method using mutual information to increase the transitions of suspicious Trojan logics.Experiments on circuit benchmarks demonstrate the effectiveness of HTDet.
