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1. There's Waldo: PCB Tamper Forensic Analysis Using Explainable AI on Impedance Signatures

   https://doi.org/10.1109/EMCSIPI52291.2025.11170306  

   Safa, Maryam Saadat; Nouraniboosjin, Seyedmohammad; Ganji, Fatemeh; Tajik, Shahin (August 2025, IEEE EMC+SIPI)

   The security of printed circuit boards (PCBs) has become increasingly vital as supply chain vulnerabilities, including tampering, present significant risks to electronic systems. While detecting tampering on a PCB is the first step for verification, forensics is also needed to identify the modified component. One non-invasive and reliable PCB tamper detection technique with global coverage is the impedance characterization of PCB's power delivery network (PDN). However, it is an open question whether one can use the two-dimensional impedance signatures for forensics purposes. In this work, we introduce a novel PCB forensics approach, using explainable AI (XAI) on impedance signatures. Through extensive experiments, we replicate various PCB tamper events, generating a dataset used to develop an XAI algorithm capable of not only detecting tampering but also explaining why the algorithm makes a decision about whether a tamper event has happened. At the core of our XAI algorithm is a random forest classifier with an accuracy of 96.7%, sufficient to explain the algorithm's decisions. To understand the behavior of the classifier In the decision-making process, we utilized the SHAP values as an XAI tool to determine which frequency component influences the classifier's decision for a particular class the most. This approach enhances detection capabilities as well as advancing the verifier's ability to reverse-engineer and analyze two-dimensional impedance signatures for forensics. 

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2. Medical Image Tampering Detection: a New Dataset and Baseline

   Reichman, B; Jing, L; Akin, O; Tian, Y. (December 2020, International Workshop on Artificial Intelligence for Healthcare Applications (AIHA), 2020.)

   null (Ed.)

   The recent advances in algorithmic photo-editing and the vulnerability of hospitals to cyberattacks raises the concern about the tampering of medical images. This paper introduces a new large scale dataset of tampered Computed Tomography (CT) scans generated by different methods, LuNoTim-CT dataset, which can serve as the most comprehensive testbed for comparative studies of data security in healthcare. We further propose a deep learning-based framework, ConnectionNet, to automatically detect if a medical image is tampered. The proposed ConnectionNet is able to handle small tampered regions and achieves promising results and can be used as the baseline for studies of medical image tampering detection. 

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3. Excitation and detection of coherent sub-terahertz magnons in ferromagnetic and antiferromagnetic heterostructures

   https://doi.org/10.1038/s41524-022-00851-2  

   Zhuang, Shihao; Hu, Jia-Mian (August 2022, npj Computational Materials)

   Abstract Excitation of coherent high-frequency magnons (quanta of spin waves) is critical to the development of high-speed magnonic devices. Here we computationally demonstrate the excitation of coherent sub-terahertz (THz) magnons in ferromagnetic (FM) and antiferromagnetic (AFM) thin films by a photoinduced picosecond acoustic pulse. Analytical calculations are also performed to reveal the magnon excitation mechanism. Through spin pumping and spin-charge conversion, these magnons can inject sub-THz charge current into an adjacent heavy-metal film which in turn emits electromagnetic (EM) waves. Using a dynamical phase-field model that considers the coupled dynamics of acoustic waves, spin waves, and EM waves, we show that the emitted EM wave retains the spectral information of all the sub-THz magnon modes and has a sufficiently large amplitude for near-field detection. These predictions indicate that the excitation and detection of sub-THz magnons can be realized in rationally designed FM or AFM thin-film heterostructures via ultrafast optical-pump THz-emission-probe spectroscopy. 

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4. Integrated microwave acousto-optic frequency shifter on thin-film lithium niobate

   https://doi.org/10.1364/OE.397138  

   Shao, Linbo; Sinclair, Neil; Leatham, James; Hu, Yaowen; Yu, Mengjie; Turpin, Terry; Crowe, Devon; Lončar, Marko (July 2020, Optics Express)

   Electrically driven acousto-optic devices that provide beam deflection and optical frequency shifting have broad applications from pulse synthesis to heterodyne detection. Commercially available acousto-optic modulators are based on bulk materials and consume Watts of radio frequency power. Here, we demonstrate an integrated 3-GHz acousto-optic frequency shifter on thin-film lithium niobate, featuring a carrier suppression over 30 dB. Further, we demonstrate a gigahertz-spaced optical frequency comb featuring more than 200 lines over a 0.6-THz optical bandwidth by recirculating the light in an active frequency shifting loop. Our integrated acousto-optic platform leads to the development of on-chip optical routing, isolation, and microwave signal processing. 

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5. Non-malleability Against Polynomial Tampering

   Ball, Marshall; Chattopadhyay, Eshan; Liao, Jyun-Jie; Malkin, Tal; Tan, Li-Yang. (July 2020, CRYPTO)

   Micciancio, Daniele; Ristenpart, Thomas. (Ed.)

   We present the first explicit construction of a non-malleable code that can handle tampering functions that are bounded-degree polynomials. Prior to our work, this was only known for degree-1 polynomials (affine tampering functions), due to Chattopad- hyay and Li (STOC 2017). As a direct corollary, we obtain an explicit non-malleable code that is secure against tampering by bounded-size arithmetic circuits. We show applications of our non-malleable code in constructing non-malleable se- cret sharing schemes that are robust against bounded-degree polynomial tampering. In fact our result is stronger: we can handle adversaries that can adaptively choose the polynomial tampering function based on initial leakage of a bounded number of shares. Our results are derived from explicit constructions of seedless non-malleable ex- tractors that can handle bounded-degree polynomial tampering functions. Prior to our work, no such result was known even for degree-2 (quadratic) polynomials. 

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