Detecting Hardware Trojans Inserted by Untrusted Foundry Using Physical Inspection and Advanced Image Processing
Detecting Hardware Trojans Inserted by Untrusted Foundry Using Physical Inspection and Advanced Image Processing
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使用物理检查和高级图像处理检测由不受信任的代工厂插入的硬件木马
DOI：
10.1007/s41635-018-0055-0
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Tehranipoor, Mark
中科院分区：
文献类型：
--
作者：
Vashistha, Nidish;Rahman, M. Tanjidur;Shen, Haoting;Woodard, Damon L.;Asadizanjani, Navid;Tehranipoor, Mark
硬件木马是在设计和制造过程的不同阶段对集成电路（ic）设计进行的恶意更改。检测木马程序的方法不同，即无损检测和破坏性检测。然而，之前开发的方法都不能用于检测所有类型的木马，因为它们存在检测速度慢、准确性低、置信度低、木马类型覆盖率低等缺点。在IC中实现的大多数硬件木马都会在活动层留下足迹。在本文中，我们提出了一种基于快速背面扫描电镜成像和先进的计算机视觉算法的新技术，以检测晶体管有源区域的任何细微变化，这些变化可以显示硬件木马的存在。这里，我们只关注不受信任的代工厂问题，假设攻击者可以访问IC的黄金布局/图像。对于那些完全设计了IC但需要访问不受信任的代工厂进行制造的组织来说，这是一个常见的威胁模型。将背面薄化金色集成电路的扫描电镜图像与低质量认证下集成电路的扫描电镜图像进行了比较。我们对黄金IC和IUA图像进行图像处理以去除噪声。我们已经开发了一个基于计算机视觉的框架来检测基于其结构相似性的硬件木马。结果表明，我们的技术在检测木马方面非常有效，并且比全芯片逆向工程快得多。我们的技术的主要优点之一是它不依赖于电路的功能，而是依赖于真实的物理结构来检测由不受信任的铸造厂执行的恶意更改。
Hardware Trojans are malicious changes to the design of integrated circuits (ICs) at different stages of the design and fabrication process. Different approaches have been developed to detect Trojans namely non-destructive and destructive testing. However, none of the previously developed methods can be used to detect all types of Trojans as they suffer from a number of disadvantages such as low speed of detection, low accuracy, low confidence level, and poor coverage of Trojan types. Majority of the hardware Trojans implemented in an IC will leave a footprint at the active layer. In this paper, we propose a new technique based on rapid backside SEM imaging and advanced computer vision algorithms to detect any subtle changes at the active region of transistors that can show the existence of a hardware Trojan. Here, we are only concerned with untrusted foundry problem, where it is assumed the attacker has access to a golden layout/image of the IC. This is a common threat model for those organizations that fully design their IC but need access to untrusted foundry for fabrication. SEM image from a backside thinned golden IC is compared with a low-quality SEM image of an IC under authentication (IUA). We perform image processing to both golden IC and IUA images to remove noise. We have developed a computer vision-based framework to detect hardware Trojans based on their structural similarity. The results demonstrate that our technique is quite effective at detecting Trojans and significantly faster than full chip reverse engineering. One of the major advantages of our technique is that it does not rely on the functionality of the circuit, rather the real physical structure to detect malicious changes performed by the untrusted foundry.
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DOI：
10.1007/978-1-4471-6684-9
发表时间：
2016-03
期刊：
--
影响因子：
--
作者：
W. Burger;M. Burge
通讯作者：
W. Burger;M. Burge
IDDQ 趋势为半导体故障的先兆
DOI：
--
发表时间：
2008
期刊：
International Conference on Prognostics and Health Management
影响因子：
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作者：
Guangfan Zhang;D. Das;R. Xu;M. Pecht
通讯作者：
M. Pecht
标准单元的 DFM 指标
DOI：
--
发表时间：
2006
期刊：
IEEE International Symposium on Quality Electronic Design
影响因子：
--
作者：
R. Aitken
通讯作者：
R. Aitken
影响因子：
20.6
作者：
Bhunia, Swarup;Hsiao, Michael S.;Narasimhan, Seetharam
通讯作者：
Narasimhan, Seetharam