A High Efficiency Hardware Trojan Detection Technique Based on Fast SEM Imaging

Courbon, Franck; Loubet-Moundi, Philippe; Fournier, Jacques; Tria, Assia

doi:10.7873/date.2015.1104

Cited by 50 publications

(19 citation statements)

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“…This results in an impractical technique of reading out the complete memory of several mm 2 . Whereas in the security community, Scanning Electron Microscopy has been recently used for hardware trojan detection [21] [5] and for spatially resolved laser fault injection [4]. Following those investigations, we show in this paper how Flash EEPROM contents commonly thought unreachable are retrieved using artefact free backside sample preparation, fined tuned SEM acquisitions (Voltage Contrast mode) and efficient image processing.…”

Section: Introductionmentioning

confidence: 83%

Reverse Engineering Flash EEPROM Memories Using Scanning Electron Microscopy

Courbon

Skorobogatov

Woods³

2017

Lecture Notes in Computer Science

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In this article, a methodology to extract Flash EEPROM memory contents is presented. Samples are first backside prepared to expose the tunnel oxide of floating gate transistors. Then, a Scanning Electron Microscope (SEM) in the so called Passive Voltage Contrast (PVC) mode allows distinguishing '0' and '1' bit values stored in individual memory cell. Using SEM operator-free acquisition and standard image processing technique we demonstrate the possible automating of such technique over a full memory. The presented fast, efficient and low cost technique is successfully implemented on 0.35µm technology node microcontrollers and on a 0.21µm smart card type integrated circuit. The technique is at least two orders of magnitude faster than state-of-the-art Scanning Probe Microscopy (SPM) methods. Without adequate protection an adversary could obtain the full memory array content within minutes. The technique is a first step for reverse engineering secure embedded systems.

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Section: Introductionmentioning

confidence: 83%

Reverse Engineering Flash EEPROM Memories Using Scanning Electron Microscopy

Courbon

Skorobogatov

Woods³

2017

Lecture Notes in Computer Science

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“…Destructive detection is also called reverse analysis [20]. Courbon et al [21] proposed a high-efficiency hardware Trojan detection technique based on fast scanning electron microscope(SEM) imaging. However, this method came at the cost of destroying the circuit, and could only detect the circuit in a specific area.…”

Section: A Hardware Trojans Detectionmentioning

confidence: 99%

An Unsupervised Detection Approach for Hardware Trojans

et al. 2020

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With the booming development of the cyber-physical system, human society is much more dependent on information technology. Unfortunately, like software, hardware is not trusted at all, due to so many third parties involved in the separated integrated circuit's (IC) design and manufacturing stages for the high profit. The malicious circuits (named Hardware Trojans) can be implanted during any stage of the ICs' design and manufacturing process. However, the existing pre-silicon approaches based on machine learning theory have good performance, they all belong to supervised learning methods, which have a key prerequisite that is numerous already known information. Meanwhile, hardware Trojans are even more unimaginable because today's ICs are becoming more complicated. The known information is even harder to gain. Furthermore, the training process for supervised learning methods tends to be time-consuming and generally requires a huge amount of balanced training data. Therefore, this paper proposes an unsupervised hardware Trojans detection approach by combined the principal component analysis (PCA) and local outlier factor (LOF) algorithm, called PL-HTD. We firstly visualize the distribution features of normal nets and Trojan nets, and then reveal the differences between the two types of nets to reduce the dimension of the feature set. According to the outliers of each net, the abnormal nets are selected and verified by professionals later to confirm whether it is a true Trojan relative to the host circuit to realize the detection. The experiments show that the proposed method can detect hardware Trojans effectively and reduce the cost of manual secondary detection. For the Trust-HUB benchmarks, the PL-HTD achieves up to 73.08% TPR and 97.52% average TNR, moreover, it achieves average 96.00% accuracy, which shows the feasibility and efficiency of hardware Trojans detecting by employing a method without the guidance of class label information. INDEX TERMS hardware security, hardware Trojan detection, integrated circuit, unsupervised machine learning, LOF

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“…Courbon et al [ 107 ] proposed an efficient HT detection method with electron microscopy scanning imaging. This method uses the electron microscope to scan imagery for the single-layer structure in a chip and compares it with the standard design circuit, find out what has changed, which can accurately detect any modification, replacement, removal, or the addition of circuit door.…”

Section: Hardware Trojans Protectionmentioning

confidence: 99%

Hardware Trojans in Chips: A Survey for Detection and Prevention

Dong

Liu

et al. 2020

Sensors

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Diverse and wide-range applications of integrated circuits (ICs) and the development of Cyber Physical System (CPS), more and more third-party manufacturers are involved in the manufacturing of ICs. Unfortunately, like software, hardware can also be subjected to malicious attacks. Untrusted outsourced manufacturing tools and intellectual property (IP) cores may bring enormous risks from highly integrated. Attributed to this manufacturing model, the malicious circuits (known as Hardware Trojans, HTs) can be implanted during the most designing and manufacturing stages of the ICs, causing a change of functionality, leakage of information, even a denial of services (DoS), and so on. In this paper, a survey of HTs is presented, which shows the threatens of chips, and the state-of-the-art preventing and detecting techniques. Starting from the introduction of HT structures, the recent researches in the academic community about HTs is compiled and comprehensive classification of HTs is proposed. The state-of-the-art HT protection techniques with their advantages and disadvantages are further analyzed. Finally, the development trends in hardware security are highlighted.

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A High Efficiency Hardware Trojan Detection Technique Based on Fast SEM Imaging

Cited by 50 publications

References 0 publications

Reverse Engineering Flash EEPROM Memories Using Scanning Electron Microscopy

Reverse Engineering Flash EEPROM Memories Using Scanning Electron Microscopy

An Unsupervised Detection Approach for Hardware Trojans

Hardware Trojans in Chips: A Survey for Detection and Prevention

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