Statistical screening for IC Trojan detection

We present statistical screening of test vectors for detecting a Trojan, malicious circuitry hidden inside an integrated circuit (IC). When applied a test vector, a Trojan-embedded chip draws extra leakage current that is unfortunately too small for the detector in most cases and concealed by process variation related to chip fabrication. To remedy the problem, we formulate a statistical approach that can screen and select test vectors in detecting Trojans. We validate our approach analytically and with gate-level simulations and show that our screening method leads to a substantial reduction in false positives and false negatives when detecting IC Trojans of various sizes.Engineering and Applied Science

A Chip Architecture for Compressive Sensing Based Detection of IC Trojans

We present a chip architecture for a compressive sensing based method that can be used in conjunction with the JTAG standard to detect IC Trojans. The proposed architecture compresses chip output resulting from a large number of test vectors applied to a circuit under test (CUT). We describe our designs in sensing leakage power, computing random linear combinations under compressive sensing, and piggybacking these new functionalities on JTAG. Our architecture achieves approximately a 10× speedup and 1000× reduction in output bandwidth while incurring a small area overhead.Engineering and Applied Science

Characteristic Reassignment for Hardware Trojan Detection

With the current business model and increasing complexity of hardware designs, third-party Intellectual Properties (IPs) are prevalently incorporated into first-party designs. However, the use of third-party IPs increases security concerns related to hardware Trojans inserted by attackers. A core threat posed by Hardware Trojans is the difficulty in detecting such malicious insertions/alternations in order to prevent the damage. This thesis work provides major improvements on a soft IP analysis methodology and tool known as the Structural Checking tool, which analyzes Register-Transfer Level (RTL) soft IPs for determining their functionalities and screening for hardware Trojans. This is done by breaking down primary ports and internal signals into assigned assets that are spread out into six characteristics. Using characteristics based on the external primary ports and the internal signals connected to them, reassignment of assets can be used to match against entries using coarse-grained-to-coarse-grained matching against a subset of known-IPs to classify an unknown soft IP. After determining the soft IP’s functionality, asset reassignment occurs within the Golden Reference Library (GRL), a library consisting of known Trojan-free and Trojan-infested entries. A fine-grained-to-fine-grained asset reassignment is used against the GRL to contain the most up-to-date assets based on the unknown soft IP, where the matching process is used to determine if the soft IP is Trojan-free or Trojan-infested. With the increasing size of the GRL, the need to decrease computational resources while also maintaining high accuracy between unknown soft IPs and GRL entries is vital

Improvement of the high-accuracy O 17 ( p , α ) N 14 reaction-rate measurement via the Trojan Horse method for application to O 17 nucleosynthesis

The ^{17}\text{O}(p,\ensuremath{\alpha})^{14}\text{N} and ^{17}\text{O}(p,\ensuremath{\gamma})^{18}\text{F} reactions are of paramount importance for the nucleosynthesis in a number of stellar sites, including red giants (RGs), asymptotic giant branch (AGB) stars, massive stars, and classical novae. In particular, they govern the destruction of $^{17}\text{O}$ and the formation of the short-lived radioisotope $^{18}\text{F}$, which is of special interest for \ensuremath{\gamma}-ray astronomy. At temperatures typical of the above-mentioned astrophysical scenario, $T=0.01$--0.1 GK for RG, AGB, and massive stars and $T=0.1$--0.4 GK for a classical nova explosion, the ^{17}\text{O}(p,\ensuremath{\alpha})^{14}\text{N} reaction cross section is dominated by two resonances: one at about ${E}_{R}^{cm}=65$ keV above the $^{18}\text{F}$ proton threshold energy, corresponding to the ${E}_{X}=5.673$ MeV level in $^{18}\text{F}$, and another one at ${E}_{R}^{cm}=183$ keV $({E}_{X}=5.786$ MeV). We report on the indirect study of the ^{17}\text{O}(p,\ensuremath{\alpha})^{14}\text{N} reaction via the Trojan Horse method by applying the approach recently developed for extracting the strength of narrow resonance at ultralow energies. The mean value of the strengths obtained in the two measurements was calculated and compared with the direct data available in literature. This value was used as input parameter for reaction-rate determination and its comparison with the result of the direct measurement is also discussed in the light of the electron screening effect

Improvement of the high-accuracy O 17 (p,α) N 14 reaction-rate measurement via the Trojan Horse method for application to O 17 nucleosynthesis

The O17(p,α)N14 and O17(p,γ)F18 reactions are of paramount importance for the nucleosynthesis in a number of stellar sites, including red giants (RGs), asymptotic giant branch (AGB) stars, massive stars, and classical novae. In particular, they govern the destruction of O17 and the formation of the short-lived radioisotope F18, which is of special interest for γ-ray astronomy. At temperatures typical of the above-mentioned astrophysical scenario, T=0.01-0.1 GK for RG, AGB, and massive stars and T=0.1-0.4 GK for a classical nova explosion, the O17(p,α)N14 reaction cross section is dominated by two resonances: one at about ERcm=65 keV above the F18 proton threshold energy, corresponding to the EX=5.673 MeV level in F18, and another one at ERcm=183 keV (EX=5.786 MeV). We report on the indirect study of the O17(p,α)N14 reaction via the Trojan Horse method by applying the approach recently developed for extracting the strength of narrow resonance at ultralow energies. The mean value of the strengths obtained in the two measurements was calculated and compared with the direct data available in literature. This value was used as input parameter for reaction-rate determination and its comparison with the result of the direct measurement is also discussed in the light of the electron screening effect

A Survey of hardware protection of design data for integrated circuits and intellectual properties

International audienceThis paper reviews the current situation regarding design protection in the microelectronics industry. Over the past ten years, the designers of integrated circuits and intellectual properties have faced increasing threats including counterfeiting, reverse-engineering and theft. This is now a critical issue for the microelectronics industry, mainly for fabless designers and intellectual properties designers. Coupled with increasing pressure to decrease the cost and increase the performance of integrated circuits, the design of a secure, efficient, lightweight protection scheme for design data is a serious challenge for the hardware security community. However, several published works propose different ways to protect design data including functional locking, hardware obfuscation, and IC/IP identification. This paper presents a survey of academic research on the protection of design data. It concludes with the need to design an efficient protection scheme based on several properties

The G67E mutation in hMLH1 is associated with an unusual presentation of Lynch syndrome

Germline mutations in the mismatch repair (MMR) genes are associated with Lynch syndrome, also known as hereditary non-polyposis colorectal cancer (HNPCC) syndrome. Here, we characterise a variant of hMLH1 that confers a loss-of-function MMR phenotype. The mutation changes the highly conserved Gly67 residue to a glutamate (G67E) and is reminiscent of the hMLH1-p.Gly67Arg mutation, which is present in several Lynch syndrome cohorts. hMLH1-Gly67Arg has previously been shown to confer loss-of-function (Shimodaira et al, 1998), and two functional assays suggest that the hMLH1-Gly67Glu protein fails to sustain normal MMR functions. In the first assay, hMLH1-Gly67Glu abolishes the protein's ability to interfere with MMR in yeast. In the second assay, mutation of the analogous residue in yMLH1 (yMLH1-Gly64Glu) causes a loss-of-function mutator phenotype similar to yMLH1-Gly64Arg. Despite these molecular similarities, an unusual spectrum of tumours is associated with hMLH1-Gly67Glu, which is not typical of those associated with Lynch syndrome and differs from those found in families carrying the hMLH1-Gly67Arg allele. This suggests that hMLH1 may have different functions in certain tissues and/or that additional factors may modify the influence of hMLH1 mutations in causing Lynch syndrome

Integrated Circuit Wear-out Prediction and Recycling Detection using Radio-Frequency Distinct Native Attribute Features

Radio Frequency Distinct Native Attribute (RF-DNA) has shown promise for detecting differences in Integrated Circuits(IC) using features extracted from a devices Unintentional Radio Emissions (URE). This ability of RF-DNA relies upon process variation imparted to a semiconductor device during manufacturing. However, internal components in modern ICs electronically age and wear out over their operational lifetime. RF-DNA techniques are adopted from prior work and applied to MSP430 URE to address the following research goals: 1) Does device wear-out impact RF-DNA device discriminability?, 2) Can device age be continuously estimated by monitoring changes in RF-DNA features?, and 3) Can device age state (e.g., new vs. used) be reliably estimated? Conclusions include: 1) device wear-out does impact RF-DNA, with up to a 16 change in discriminability over the range of accelerated ages considered, 2) continuous(hour-by-hour) age estimation was most challenging and generally not supported, and 3) binary new vs. used age estimation was successful with 78.7 to 99.9 average discriminability for all device-age combinations considered