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- ItemA Flashback on Control Logic Injection Attacks against Programmable Logic Controllers(Basel : MDPI, 2022) Alsabbagh, Wael; Langendörfer, PeterProgrammable logic controllers (PLCs) make up a substantial part of critical infrastructures (CIs) and industrial control systems (ICSs). They are programmed with a control logic that defines how to drive and operate critical processes such as nuclear power plants, petrochemical factories, water treatment systems, and other facilities. Unfortunately, these devices are not fully secure and are prone to malicious threats, especially those exploiting vulnerabilities in the control logic of PLCs. Such threats are known as control logic injection attacks. They mainly aim at sabotaging physical processes controlled by exposed PLCs, causing catastrophic damage to target systems as shown by Stuxnet. Looking back over the last decade, many research endeavors exploring and discussing these threats have been published. In this article, we present a flashback on the recent works related to control logic injection attacks against PLCs. To this end, we provide the security research community with a new systematization based on the attacker techniques under three main attack scenarios. For each study presented in this work, we overview the attack strategies, tools, security goals, infected devices, and underlying vulnerabilities. Based on our analysis, we highlight the current security challenges in protecting PLCs from such severe attacks and suggest security recommendations for future research directions.
- ItemRidge Gap Waveguide Based Liquid Crystal Phase Shifter(New York, NY : IEEE, 2020) Nickel, Matthias; Jiménez-Sáez, Alejandro; Agrawal, Prannoy; Gadallah, Ahmed; Malignaggi, Andrea; Schuster, Christian; Reese, Roland; Tesmer, Henning; Polat, Ersin; Schumacher, Peter; Jakoby, Rolf; Kissinger, Dietmar; Maune, HolgerIn this paper, the gap waveguide technology is examined for packaging liquid crystal (LC) in tunable microwave devices. For this purpose, a line based passive phase shifter is designed and implemented in a ridge gap waveguide (RGW) topology and filled with LC serving as functional material. The inherent direct current (DC) decoupling property of gap waveguides is used to utilize the waveguide surroundings as biasing electrodes for tuning the LC. The bed of nails structure of the RGW exhibits an E-field suppression of 76 dB in simulation, forming a completely shielded device. The phase shifter shows a maximum figure of merit (FoM) of 70 °/dB from 20 GHz to 30 GHz with a differential phase shift of 387° at 25 GHz. The insertion loss ranges from 3.5 dB to 5.5 dB depending on the applied biasing voltage of 0 V to 60 V. © 2013 IEEE.
- ItemDual-Band Transmitter and Receiver With Bowtie-Antenna in 0.13 μm SiGe BiCMOS for Gas Spectroscopy at 222 - 270 GHz(New York, NY : IEEE, 2021) Schmalz, Klaus; Rothbart, Nick; Gluck, Alexandra; Eissa, Mohamed Hussein; Mausolf, Thomas; Turkmen, Esref; Yilmaz, Selahattin Berk; Hubers, Heinz-WilhelmThis paper presents a transmitter (TX) and a receiver (RX) with bowtie-antenna and silicon lens for gas spectroscopy at 222-270 GHz, which are fabricated in IHP's 0.13 μm SiGe BiCMOS technology. The TX and RX use two integrated local oscillators for 222 - 256 GHz and 250 - 270 GHz, which are switched for dual-band operation. Due to its directivity of about 27 dBi, the single integrated bowtie-antenna with silicon lens enables an EIRP of about 25 dBm for the TX, and therefore a considerably higher EIRP for the 2-band TX compared to previously reported systems. The double sideband noise temperature of the RX is 20,000 K (18.5 dB noise figure) as measured by the Y-factor method. Absorption spectroscopy of gaseous methanol is used as a measure for the performance of the gas spectroscopy system with TX- and RX-modules.
- ItemA TOPSIS-Assisted Feature Selection Scheme and SOM-Based Anomaly Detection for Milling Tools Under Different Operating Conditions(New York, NY : IEEE, 2021) Assafo, Maryam; Langendorfer, PeterAnomaly detection modeled as a one-class classification is an essential task for tool condition monitoring (TCM) when only the normal data are available. To confront with the real-world settings, it is crucial to take the different operating conditions, e.g., rotation speed, into account when approaching TCM solutions. This work mainly addresses issues related to multi-operating-condition TCM models, namely the varying discriminability of sensory features with different operating conditions; the overlap between normal and anomalous data; and the complex structure of input data. A feature selection scheme is proposed in which the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is presented as a tool to aid the multi-objective selection of sensory features. In addition, four anomaly detection approaches based on Self-Organizing Map (SOM) are studied. To examine the stability of the four approaches, they are applied on different single-operating-condition models. Further, to examine their robustness when dealing with complex data structures, they are applied on multi-operating-condition models. The experimental results using the NASA Milling Data Set showed that all the studied anomaly detection approaches achieved a higher assessment accuracy with our feature selection scheme as compared to the Principal Component Analysis (PCA), Laplacian Score (LS), and extended LS in which we added a final step to the original LS method in order to eliminate redundant features.
- Item168-195 GHz Power Amplifier with Output Power Larger Than 18 dBm in BiCMOS Technology(New York, NY : IEEE, 2020) Ali, Abdul; Yun, Jongwon; Giannini, Franco; Ng, Herman Jalli; Kissinger, Dietmar; Colantonio, PaoloThis paper presents a 4-way combined G-band power amplifier (PA) fabricated with a 130-nm SiGe BiCMOS process. First, a single-ended PA based on the cascode topology (CT) is designed at 185 GHz, which consists of three stages to get an overall gain and an output power higher than 27 dB and 13 dBm, respectively. Then, a 4-way combiner/splitter was designed using low-loss transmission lines at 130-210 GHz. Finally, the combiner was loaded with four single-ended PAs to complete the design of a 4-way combined PA. The chip of the fabricated PA occupies an area of 1.35mm2. The realized PA shows a saturated output power of 18.1 dBm with a peak gain of 25.9 dB and power-added efficiency (PAE) of 3.5% at 185 GHz. A maximum output power of 18.7 dBm with PAE of 4.4% is achieved at 170 GHz. The 3-dB and 6-dB bandwidth of the PA are 27 and 42 GHz, respectively. In addition, the PA delivers a saturated output power higher than 18 dBm in the frequency range 140-186 GHz. To the best of our knowledge, the power reported in this paper is the highest for G-band SiGe BiCMOS PAs. © 2013 IEEE.
- ItemIn-Vitro Classification of Saliva Samples of COPD Patients and Healthy Controls Using Machine Learning Tools(New York, NY : IEEE, 2020) Zarrin, Pouya Soltani; Roeckendorf, Niels; Wenger, ChristianChronic Obstructive Pulmonary Disease (COPD) is a life-threatening lung disease and a major cause of morbidity and mortality worldwide. Although a curative therapy has yet to be found, permanent monitoring of biomarkers that refiect the disease progression plays a pivotal role for the effective management of COPD. The accurate examination of respiratory tract fiuids like saliva is a promising approach for staging disease and predicting its upcoming exacerbations in a Point-of-Care (PoC) environment. However, the concurrent consideration of patients' demographic and medical parameters is necessary for achieving accurate outcomes. Therefore, Machine Learning (ML) tools can play an important role for analyzing patient data and providing comprehensive results for the recognition of COPD in a PoC setting. As a result, the objective of this research work was to implement ML tools on data acquired from characterizing saliva samples of COPD patients and healthy controls as well as their demographic information for PoC recognition of the disease. For this purpose, a permittivity biosensor was used to characterize dielectric properties of saliva samples and, subsequently, ML tools were applied on the acquired data for classification. The XGBoost gradient boosting algorithm provided a high classification accuracy and sensitivity of 91.25% and 100%, respectively, making it a promising model for COPD evaluation. Integration of this model on a neuromorphic chip, in the future, will enable the real-time assessment of COPD in PoC, with low cost, low energy consumption, and high patient privacy. In addition, constant monitoring of COPD in a near-patient setup will enable the better management of the disease exacerbations.