Visible to the public Biblio

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2019-05-09
Sokolov, A. N., Barinov, A. E., Antyasov, I. S., Skurlaev, S. V., Ufimtcev, M. S., Luzhnov, V. S..  2018.  Hardware-Based Memory Acquisition Procedure for Digital Investigations of Security Incidents in Industrial Control Systems. 2018 Global Smart Industry Conference (GloSIC). :1-7.
The safety of industrial control systems (ICS) depends not only on comprehensive solutions for protecting information, but also on the timing and closure of vulnerabilities in the software of the ICS. The investigation of security incidents in the ICS is often greatly complicated by the fact that malicious software functions only within the computer's volatile memory. Obtaining the contents of the volatile memory of an attacked computer is difficult to perform with a guaranteed reliability, since the data collection procedure must be based on a reliable code (the operating system or applications running in its environment). The paper proposes a new instrumental method for obtaining the contents of volatile memory, general rules for implementing the means of collecting information stored in memory. Unlike software methods, the proposed method has two advantages: firstly, there is no problem in terms of reading the parts of memory, blocked by the operating system, and secondly, the resulting contents are not compromised by such malicious software. The proposed method is relevant for investigating security incidents of ICS and can be used in continuous monitoring systems for the security of ICS.
Ivanov, A. V., Sklyarov, V. A..  2018.  The Urgency of the Threats of Attacks on Interfaces and Field-Layer Protocols in Industrial Control Systems. 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE). :162-165.
The paper is devoted to analysis of condition of executing devices and sensors of Industrial Control Systems information security. The work contains structures of industrial control systems divided into groups depending on system's layer. The article contains the analysis of analog interfaces work and work features of data transmission protocols in industrial control system field layer. Questions about relevance of industrial control systems information security, both from the point of view of the information security occurring incidents, and from the point of view of regulators' reaction in the form of normative legal acts, are described. During the analysis of the information security systems of industrial control systems a possibility of leakage through technical channels of information leakage at the field layer was found. Potential vectors of the attacks on devices of field layer and data transmission network of an industrial control system are outlined in the article. The relevance analysis of the threats connected with the attacks at the field layer of an industrial control system is carried out, feature of this layer and attractiveness of this kind of attacks is observed.
Li, Y., Liu, X., Tian, H., Luo, C..  2018.  Research of Industrial Control System Device Firmware Vulnerability Mining Technology Based on Taint Analysis. 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS). :607-610.
Aiming at the problem that there is little research on firmware vulnerability mining and the traditional method of vulnerability mining based on fuzzing test is inefficient, this paper proposed a new method of mining vulnerabilities in industrial control system firmware. Based on taint analysis technology, this method can construct test cases specifically for the variables that may trigger vulnerabilities, thus reducing the number of invalid test cases and improving the test efficiency. Experiment result shows that this method can reduce about 23 % of test cases and can effectively improve test efficiency.
Lu, G., Feng, D..  2018.  Network Security Situation Awareness for Industrial Control System Under Integrity Attacks. 2018 21st International Conference on Information Fusion (FUSION). :1808-1815.
Due to the wide implementation of communication networks, industrial control systems are vulnerable to malicious attacks, which could cause potentially devastating results. Adversaries launch integrity attacks by injecting false data into systems to create fake events or cover up the plan of damaging the systems. In addition, the complexity and nonlinearity of control systems make it more difficult to detect attacks and defense it. Therefore, a novel security situation awareness framework based on particle filtering, which has good ability in estimating state for nonlinear systems, is proposed to provide an accuracy understanding of system situation. First, a system state estimation based on particle filtering is presented to estimate nodes state. Then, a voting scheme is introduced into hazard situation detection to identify the malicious nodes and a local estimator is constructed to estimate the actual system state by removing the identified malicious nodes. Finally, based on the estimated actual state, the actual measurements of the compromised nodes are predicted by using the situation prediction algorithm. At the end of this paper, a simulation of a continuous stirred tank is conducted to verify the efficiency of the proposed framework and algorithms.
2019-03-25
Ferres, E., Immler, V., Utz, A., Stanitzki, A., Lerch, R., Kokozinski, R..  2018.  Capacitive Multi-Channel Security Sensor IC for Tamper-Resistant Enclosures. 2018 IEEE SENSORS. :1–4.
Physical attacks are a serious threat for embedded devices. Since these attacks are based on physical interaction, sensing technology is a key aspect in detecting them. For highest security levels devices in need of protection are placed into tamper-resistant enclosures. In this paper we present a capacitive multi-channel security sensor IC in a 350 nm CMOS technology. This IC measures more than 128 capacitive sensor nodes of such an enclosure with an SNR of 94.6 dB across a 16×16 electrode matrix in just 19.7 ms. The theoretical sensitivity is 35 aF which is practically limited by noise to 460 aF. While this is similar to capacitive touch technology, it outperforms available solutions of this domain with respect to precision and speed.
2019-03-15
Hossain, F. S., Shintani, M., Inoue, M., Orailoglu, A..  2018.  Variation-Aware Hardware Trojan Detection through Power Side-Channel. 2018 IEEE International Test Conference (ITC). :1-10.
A hardware Trojan (HT) denotes the malicious addition or modification of circuit elements. The purpose of this work is to improve the HT detection sensitivity in ICs using power side-channel analysis. This paper presents three detection techniques in power based side-channel analysis by increasing Trojan-to-circuit power consumption and reducing the variation effect in the detection threshold. Incorporating the three proposed methods has demonstrated that a realistic fine-grain circuit partitioning and an improved pattern set to increase HT activation chances can magnify Trojan detectability.
Cozzi, M., Galliere, J., Maurine, P..  2018.  Exploiting Phase Information in Thermal Scans for Stealthy Trojan Detection. 2018 21st Euromicro Conference on Digital System Design (DSD). :573-576.
Infrared thermography has been recognized for its ability to investigate integrated circuits in a non destructive way. Coupled to lock-in correlation it has proven efficient in detecting thermal hot spots. Most of the state of the Art measurement systems are based on amplitude analysis. In this paper we propose to investigate weak thermal hot spots using the phase of infrared signals. We demonstrate that phase analysis is a formidable alternative to amplitude to detect small heat signatures. Finally, we apply our measurement platform and its detection method to the identification of stealthy hardware Trojans.
Martin, H., Entrena, L., Dupuis, S., Natale, G. Di.  2018.  A Novel Use of Approximate Circuits to Thwart Hardware Trojan Insertion and Provide Obfuscation. 2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS). :41-42.
Hardware Trojans have become in the last decade a major threat in the Integrated Circuit industry. Many techniques have been proposed in the literature aiming at detecting such malicious modifications in fabricated ICs. For the most critical circuits, prevention methods are also of interest. The goal of such methods is to prevent the insertion of a Hardware Trojan thanks to ad-hoc design rules. In this paper, we present a novel prevention technique based on approximation. An approximate logic circuit is a circuit that performs a possibly different but closely related logic function, so that it can be used for error detection or error masking where it overlaps with the original circuit. We will show how this technique can successfully detect the presence of Hardware Trojans, with a solution that has a smaller impact than triplication.
2019-03-06
Kawanishi, Y., Nishihara, H., Souma, D., Yoshida, H., Hata, Y..  2018.  A Study on Quantitative Risk Assessment Methods in Security Design for Industrial Control Systems. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). :62-69.

In recent years, there has been progress in applying information technology to industrial control systems (ICS), which is expected to make the development cost of control devices and systems lower. On the other hand, the security threats are becoming important problems. In 2017, a command injection issue on a data logger was reported. In this paper, we focus on the risk assessment in security design for data loggers used in industrial control systems. Our aim is to provide a risk assessment method optimized for control devices and systems in such a way that one can prioritize threats more preciously, that would lead work resource (time and budget) can be assigned for more important threats than others. We discuss problems with application of the automotive-security guideline of JASO TP15002 to ICS risk assessment. Consequently, we propose a three-phase risk assessment method with a novel Risk Scoring Systems (RSS) for quantitative risk assessment, RSS-CWSS. The idea behind this method is to apply CWSS scoring systems to RSS by fixing values for some of CWSS metrics, considering what the designers can evaluate during the concept phase. Our case study with ICS employing a data logger clarifies that RSS-CWSS can offer an interesting property that it has better risk-score dispersion than the TP15002-specified RSS.

2019-02-08
Isaacson, D. M..  2018.  The ODNI-OUSD(I) Xpress Challenge: An Experimental Application of Artificial Intelligence Techniques to National Security Decision Support. 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC). :104-109.
Current methods for producing and disseminating analytic products contribute to the latency of relaying actionable information and analysis to the U.S. Intelligence Community's (IC's) principal customers, U.S. policymakers and warfighters. To circumvent these methods, which can often serve as a bottleneck, we report on the results of a public prize challenge that explored the potential for artificial intelligence techniques to generate useful analytic products. The challenge tasked solvers to develop algorithms capable of searching and processing nearly 15,000 unstructured text files into a 1-2 page analytic product without human intervention; these analytic products were subsequently evaluated and scored using established IC methodologies and criteria. Experimental results from this challenge demonstrate the promise for the ma-chine generation of analytic products to ensure that the IC warns and informs in a more timely fashion.
2019-01-21
Laszka, A., Abbas, W., Vorobeychik, Y., Koutsoukos, X..  2018.  Synergistic Security for the Industrial Internet of Things: Integrating Redundancy, Diversity, and Hardening. 2018 IEEE International Conference on Industrial Internet (ICII). :153–158.
As the Industrial Internet of Things (IIot) becomes more prevalent in critical application domains, ensuring security and resilience in the face of cyber-attacks is becoming an issue of paramount importance. Cyber-attacks against critical infrastructures, for example, against smart water-distribution and transportation systems, pose serious threats to public health and safety. Owing to the severity of these threats, a variety of security techniques are available. However, no single technique can address the whole spectrum of cyber-attacks that may be launched by a determined and resourceful attacker. In light of this, we consider a multi-pronged approach for designing secure and resilient IIoT systems, which integrates redundancy, diversity, and hardening techniques. We introduce a framework for quantifying cyber-security risks and optimizing IIoT design by determining security investments in redundancy, diversity, and hardening. To demonstrate the applicability of our framework, we present a case study in water-distribution systems. Our numerical evaluation shows that integrating redundancy, diversity, and hardening can lead to reduced security risk at the same cost.
2018-12-10
Shathanaa, R., Ramasubramanian, N..  2018.  Improving Power amp; Latency Metrics for Hardware Trojan Detection During High Level Synthesis. 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–7.
The globalization and outsourcing of the semiconductor industry has raised serious concerns about the trustworthiness of the hardware. Importing Third Party IP cores in the Integrated Chip design has opened gates for new form of attacks on hardware. Hardware Trojans embedded in Third Party IPs has necessitated the need for secure IC design process. Design-for-Trust techniques aimed at detection of Hardware Trojans come with overhead in terms of area, latency and power consumption. In this work, we present a Cuckoo Search algorithm based Design Space Exploration process for finding low cost hardware solutions during High Level Synthesis. The exploration is conducted with respect to datapath resource allocation for single and nested loops. The proposed algorithm is compared with existing Hardware Trojan detection mechanisms and experimental results show that the proposed algorithm is able to achieve 3x improvement in Cost when compared existing algorithms.
2018-09-28
Brandauer, C., Dorfinger, P., Paiva, P. Y. A..  2017.  Towards scalable and adaptable security monitoring. 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC). :1–6.

A long time ago Industrial Control Systems were in a safe place due to the use of proprietary technology and physical isolation. This situation has changed dramatically and the systems are nowadays often prone to severe attacks executed from remote locations. In many cases, intrusions remain undetected for a long time and this allows the adversary to meticulously prepare an attack and maximize its destructiveness. The ability to detect an attack in its early stages thus has a high potential to significantly reduce its impact. To this end, we propose a holistic, multi-layered, security monitoring and mitigation framework spanning the physical- and cyber domain. The comprehensiveness of the approach demands for scalability measures built-in by design. In this paper we present how scalability is addressed by an architecture that enforces geographically decentralized data reduction approaches that can be dynamically adjusted to the currently perceived context. A specific focus is put on a robust and resilient solution to orchestrate dynamic configuration updates. Experimental results based on a prototype implementation show the feasibility of the approach.

2018-07-18
Vávra, J., Hromada, M..  2017.  Anomaly Detection System Based on Classifier Fusion in ICS Environment. 2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT). :32–38.

The detection of cyber-attacks has become a crucial task for highly sophisticated systems like industrial control systems (ICS). These systems are an essential part of critical information infrastructure. Therefore, we can highlight their vital role in contemporary society. The effective and reliable ICS cyber defense is a significant challenge for the cyber security community. Thus, intrusion detection is one of the demanding tasks for the cyber security researchers. In this article, we examine classification problem. The proposed detection system is based on supervised anomaly detection techniques. Moreover, we utilized classifiers algorithms in order to increase intrusion detection capabilities. The fusion of the classifiers is the way how to achieve the predefined goal.

Yusheng, W., Kefeng, F., Yingxu, L., Zenghui, L., Ruikang, Z., Xiangzhen, Y., Lin, L..  2017.  Intrusion Detection of Industrial Control System Based on Modbus TCP Protocol. 2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS). :156–162.

Modbus over TCP/IP is one of the most popular industrial network protocol that are widely used in critical infrastructures. However, vulnerability of Modbus TCP protocol has attracted widely concern in the public. The traditional intrusion detection methods can identify some intrusion behaviors, but there are still some problems. In this paper, we present an innovative approach, SD-IDS (Stereo Depth IDS), which is designed for perform real-time deep inspection for Modbus TCP traffic. SD-IDS algorithm is composed of two parts: rule extraction and deep inspection. The rule extraction module not only analyzes the characteristics of industrial traffic, but also explores the semantic relationship among the key field in the Modbus TCP protocol. The deep inspection module is based on rule-based anomaly intrusion detection. Furthermore, we use the online test to evaluate the performance of our SD-IDS system. Our approach get a low rate of false positive and false negative.

Terai, A., Abe, S., Kojima, S., Takano, Y., Koshijima, I..  2017.  Cyber-Attack Detection for Industrial Control System Monitoring with Support Vector Machine Based on Communication Profile. 2017 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :132–138.

Industrial control systems (ICS) used in industrial plants are vulnerable to cyber-attacks that can cause fatal damage to the plants. Intrusion detection systems (IDSs) monitor ICS network traffic and detect suspicious activities. However, many IDSs overlook sophisticated cyber-attacks because it is hard to make a complete database of cyber-attacks and distinguish operational anomalies when compared to an established baseline. In this paper, a discriminant model between normal and anomalous packets was constructed with a support vector machine (SVM) based on an ICS communication profile, which represents only packet intervals and length, and an IDS with the applied model is proposed. Furthermore, the proposed IDS was evaluated using penetration tests on our cyber security test bed. Although the IDS was constructed by the limited features (intervals and length) of packets, the IDS successfully detected cyber-attacks by monitoring the rate of predicted attacking packets.

Feng, C., Li, T., Chana, D..  2017.  Multi-level Anomaly Detection in Industrial Control Systems via Package Signatures and LSTM Networks. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :261–272.

We outline an anomaly detection method for industrial control systems (ICS) that combines the analysis of network package contents that are transacted between ICS nodes and their time-series structure. Specifically, we take advantage of the predictable and regular nature of communication patterns that exist between so-called field devices in ICS networks. By observing a system for a period of time without the presence of anomalies we develop a base-line signature database for general packages. A Bloom filter is used to store the signature database which is then used for package content level anomaly detection. Furthermore, we approach time-series anomaly detection by proposing a stacked Long Short Term Memory (LSTM) network-based softmax classifier which learns to predict the most likely package signatures that are likely to occur given previously seen package traffic. Finally, by the inspection of a real dataset created from a gas pipeline SCADA system, we show that an anomaly detection scheme combining both approaches can achieve higher performance compared to various current state-of-the-art techniques.

2018-06-11
Guo, X., Dutta, R. G., He, J., Jin, Y..  2017.  PCH framework for IP runtime security verification. 2017 Asian Hardware Oriented Security and Trust Symposium (AsianHOST). :79–84.

Untrusted third-party vendors and manufacturers have raised security concerns in hardware supply chain. Among all existing solutions, formal verification methods provide powerful solutions in detection malicious behaviors at the pre-silicon stage. However, little work have been done towards built-in hardware runtime verification at the post-silicon stage. In this paper, a runtime formal verification framework is proposed to evaluate the trust of hardware during its execution. This framework combines the symbolic execution and SAT solving methods to validate the user defined properties. The proposed framework has been demonstrated on an FPGA platform using an SoC design with untrusted IPs. The experimentation results show that the proposed approach can provide high-level security assurance for hardware at runtime.

Chen, X., Qu, G., Cui, A., Dunbar, C..  2017.  Scan chain based IP fingerprint and identification. 2017 18th International Symposium on Quality Electronic Design (ISQED). :264–270.
Digital fingerprinting refers to as method that can assign each copy of an intellectual property (IP) a distinct fingerprint. It was introduced for the purpose of protecting legal and honest IP users. The unique fingerprint can be used to identify the IP or a chip that contains the IP. However, existing fingerprinting techniques are not practical due to expensive cost of creating fingerprints and the lack of effective methods to verify the fingerprints. In the paper, we study a practical scan chain based fingerprinting method, where the digital fingerprint is generated by selecting the Q-SD or Q'-SD connection during the design of scan chains. This method has two major advantages. First, fingerprints are created as a post-silicon procedure and therefore there will be little fabrication overhead. Second, altering the Q-SD or Q'-SD connection style requires the modification of test vectors for each fingerprinted IP in order to maintain the fault coverage. This enables us to verify the fingerprint by inspecting the test vectors without opening up the chip to check the Q-SD or Q'-SD connection styles. We perform experiment on standard benchmarks to demonstrate that our approach has low design overhead. We also conduct security analysis to show that such fingerprints are robust against various attacks.
2018-05-30
Su, W., Antoniou, A., Eagle, C..  2017.  Cyber Security of Industrial Communication Protocols. 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). :1–4.
In this paper, an industrial testbed is proposed utilizing commercial-off-the-shelf equipment, and it is used to study the weakness of industrial Ethernet, i.e., PROFINET. The investigation is based on observation of the principles of operation of PROFINET and the functionality of industrial control systems.
2018-05-24
Maraj, A., Rogova, E., Jakupi, G., Grajqevci, X..  2017.  Testing Techniques and Analysis of SQL Injection Attacks. 2017 2nd International Conference on Knowledge Engineering and Applications (ICKEA). :55–59.

It is a well-known fact that nowadays access to sensitive information is being performed through the use of a three-tier-architecture. Web applications have become a handy interface between users and data. As database-driven web applications are being used more and more every day, web applications are being seen as a good target for attackers with the aim of accessing sensitive data. If an organization fails to deploy effective data protection systems, they might be open to various attacks. Governmental organizations, in particular, should think beyond traditional security policies in order to achieve proper data protection. It is, therefore, imperative to perform security testing and make sure that there are no holes in the system, before an attack happens. One of the most commonly used web application attacks is by insertion of an SQL query from the client side of the application. This attack is called SQL Injection. Since an SQL Injection vulnerability could possibly affect any website or web application that makes use of an SQL-based database, the vulnerability is one of the oldest, most prevalent and most dangerous of web application vulnerabilities. To overcome the SQL injection problems, there is a need to use different security systems. In this paper, we will use 3 different scenarios for testing security systems. Using Penetration testing technique, we will try to find out which is the best solution for protecting sensitive data within the government network of Kosovo.

2018-05-01
Arafin, M. T., Stanley, A., Sharma, P..  2017.  Hardware-Based Anti-Counterfeiting Techniques for Safeguarding Supply Chain Integrity. 2017 IEEE International Symposium on Circuits and Systems (ISCAS). :1–4.
Counterfeit integrated circuits (ICs) and systems have emerged as a menace to the supply chain of electronic goods and products. Simple physical inspection for counterfeit detection, basic intellectual property (IP) laws, and simple protection measures are becoming ineffective against advanced reverse engineering and counterfeiting practices. As a result, hardware security-based techniques have emerged as promising solutions for combating counterfeiting, reverse engineering, and IP theft. However, these solutions have their own merits and shortcomings, and therefore, these options must be carefully studied. In this work, we present a comparative overview of available hardware security solutions to fight against IC counterfeiting. We provide a detailed comparison of the techniques in terms of integration effort, deployability, and security matrices that would assist a system designer to adopt any one of these security measures for safeguarding the product supply chain against counterfeiting and IP theft.
2018-04-11
Hasegawa, K., Yanagisawa, M., Togawa, N..  2017.  Trojan-Feature Extraction at Gate-Level Netlists and Its Application to Hardware-Trojan Detection Using Random Forest Classifier. 2017 IEEE International Symposium on Circuits and Systems (ISCAS). :1–4.

Recently, due to the increase of outsourcing in IC design, it has been reported that malicious third-party vendors often insert hardware Trojans into their ICs. How to detect them is a strong concern in IC design process. The features of hardware-Trojan infected nets (or Trojan nets) in ICs often differ from those of normal nets. To classify all the nets in netlists designed by third-party vendors into Trojan ones and normal ones, we have to extract effective Trojan features from Trojan nets. In this paper, we first propose 51 Trojan features which describe Trojan nets from netlists. Based on the importance values obtained from the random forest classifier, we extract the best set of 11 Trojan features out of the 51 features which can effectively detect Trojan nets, maximizing the F-measures. By using the 11 Trojan features extracted, the machine-learning based hardware Trojan classifier has achieved at most 100% true positive rate as well as 100% true negative rate in several TrustHUB benchmarks and obtained the average F-measure of 74.6%, which realizes the best values among existing machine-learning-based hardware-Trojan detection methods.

Khalid, F., Hasan, S. R., Hasan, O., Awwadl, F..  2017.  Behavior Profiling of Power Distribution Networks for Runtime Hardware Trojan Detection. 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS). :1316–1319.

Runtime hardware Trojan detection techniques are required in third party IP based SoCs as a last line of defense. Traditional techniques rely on golden data model or exotic signal processing techniques such as utilizing Choas theory or machine learning. Due to cumbersome implementation of such techniques, it is highly impractical to embed them on the hardware, which is a requirement in some mission critical applications. In this paper, we propose a methodology that generates a digital power profile during the manufacturing test phase of the circuit under test. A simple processing mechanism, which requires minimal computation of measured power signals, is proposed. For the proof of concept, we have applied the proposed methodology on a classical Advanced Encryption Standard circuit with 21 available Trojans. The experimental results show that the proposed methodology is able to detect 75% of the intrusions with the potential of implementing the detection mechanism on-chip with minimal overhead compared to the state-of-the-art techniques.

Hossain, F. S., Yoneda, T., Shintani, M., Inoue, M., Orailoglo, A..  2017.  Intra-Die-Variation-Aware Side Channel Analysis for Hardware Trojan Detection. 2017 IEEE 26th Asian Test Symposium (ATS). :52–57.

High detection sensitivity in the presence of process variation is a key challenge for hardware Trojan detection through side channel analysis. In this work, we present an efficient Trojan detection approach in the presence of elevated process variations. The detection sensitivity is sharpened by 1) comparing power levels from neighboring regions within the same chip so that the two measured values exhibit a common trend in terms of process variation, and 2) generating test patterns that toggle each cell multiple times to increase Trojan activation probability. Detection sensitivity is analyzed and its effectiveness demonstrated by means of RPD (relative power difference). We evaluate our approach on ISCAS'89 and ITC'99 benchmarks and the AES-128 circuit for both combinational and sequential type Trojans. High detection sensitivity is demonstrated by analysis on RPD under a variety of process variation levels and experiments for Trojan inserted circuits.