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  1. Cyber-physical systems (CPS) have been increasingly attacked by hackers. CPS are especially vulnerable to attackers that have full knowledge of the system's configuration. Therefore, novel anomaly detection algorithms in the presence of a knowledgeable adversary need to be developed. However, this research is still in its infancy due to limited attack data availability and test beds. By proposing a holistic attack modeling framework, we aim to show the vulnerability of existing detection algorithms and provide a basis for novel sensor-based cyber-attack detection. Stealthy Attack GEneration (SAGE) for CPS serves as a tool for cyber-risk assessment of existing systems and detection algorithms for practitioners and researchers alike. Stealthy attacks are characterized by malicious injections into the CPS through input, output, or both, which produce bounded changes in the detection residue. By using the SAGE framework, we generate stealthy attacks to achieve three objectives: (i) Maximize damage, (ii) Avoid detection, and (iii) Minimize the attack cost. Additionally, an attacker needs to adhere to the physical principles in a CPS (objective iv). The goal of SAGE is to model worst-case attacks, where we assume limited information asymmetries between attackers and defenders (e.g., insider knowledge of the attacker). Those worst-case attacks are the hardest to detect, but common in practice and allow understanding of the maximum conceivable damage. We propose an efficient solution procedure for the novel SAGE optimization problem. The SAGE framework is illustrated in three case studies. Those case studies serve as modeling guidelines for the development of novel attack detection algorithms and comprehensive cyber-physical risk assessment of CPS. The results show that SAGE attacks can cause severe damage to a CPS, while only changing the input control signals minimally. This avoids detection and keeps the cost of an attack low. This highlights the need for more advanced detection algorithms and novel research in cyber-physical security. 
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  2. Abstract

    Sb‐doped and GeTe‐alloyed n‐type thermoelectric materials that show an excellent figure of meritZTin the intermediate temperature range (400–800 K) are reported. The synergistic effect of favorable changes to the band structure resulting in high Seebeck coefficient and enhanced phonon scattering by point defects and nanoscale precipitates resulting in reduction of thermal conductivity are demonstrated. The samples can be tuned as single‐phase solid solution (SS) or two‐phase system with nanoscale precipitates (Nano) based on the annealing processes. The GeTe alloying results in band structure modification by widening the bandgap and increasing the density‐of‐states effective mass of PbTe, resulting in significantly enhanced Seebeck coefficients. The nanoscale precipitates can improve the power factor in the low temperature range and further reduce the lattice thermal conductivity (κlat). Specifically, the Seebeck coefficient of Pb0.988Sb0.012Te–13%GeTe–Nano approaches −280 µV K−1at 673 K with a low κlatof 0.56 W m−1K−1at 573 K. Consequently, a peakZTvalue of 1.38 is achieved at 623 K. Moreover, a high averageZTavgvalue of ≈1.04 is obtained in the temperature range from 300 to 773 K for n‐type Pb0.988Sb0.012Te–13%GeTe–Nano.

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