Hardcoded vulnerability detection approach for IoT device firmware by Chao MU, Xin WANG, Ming YANG, Heng ZHANG, Zhenya CHEN, Xiaoming WU

“…With the popularization of IoT devices, more and more valuable data is generated.Analyzing and mining big data based on IoT devices has become a hot topic in the academic and industrial circles in recent years.However, due to the lack of necessary detection and protection methods, many IoT devices have serious information security risks.In particular, device hard-coded information is closely related to system encryption and decryption, identity authentication and other functions, which can provide confidentiality protection for core data.Once this information is exploited by malicious attackers, serious consequences such as sensitive information leakage, backdoor attacks, and unauthorized logins will occur.In response to this problem, a multi-type character recognition and positioning scheme was designed and a hard-coded vulnerability detection method in executable files was proposed based on the study of the characteristics of hard-coded vulnerabilities in IoT devices.The proposed method extracted the firmware of IoT devices and filtered all executable files as the source to be analyzed.Then, a solution to identify and locate three types of hard-coded characters was provided.Further, the reachability of the function, where the hard-coded character was located, was analyzed according to the function call relationship.Meanwhile, the instruction heterogeneity was mitigated by an intermediate representation (IR) model.The character and parameter hard-coded values was obtained through a data flow analysis approach.A symbolic execution method was devised to determine the trigger conditions of the hard-coded vulnerabilities, and then the vulnerability detection result was output.On the one hand, the proposed method introduced the method of symbolic execution based on the use of the intermediate representation model, which eliminated the dependency of instruction architecture and reduces the false positive rate of vulnerabilities; On the other hand, this method can integrate characters, files, and cryptographic implementation to realize the different characteristics of three types of hard-coded characters, which increased the coverage of vulnerability detection and improves the versatility of the detection method.The experimental results show that the proposed method can effectively detect three types of hard-coded vulnerabilities of characters, files and cryptographic implementation in various IoT devices, and has good detection accuracy, which can provide certain guidance for the deployment of subsequent security protection technologies.…”
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Bias‐Independent True Random Number Generator Circuit using Memristor Noise Signals as Entropy Source by Jinwoo Park, Hyunjoong Kim, Hyungjin Kim

“…Finally, the performance of the designed TRNG circuit is evaluated using autocorrelation functions and National Institute of Standards and Technology tests, confirming its capability to produce random number bitstreams.…”
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Merging Surface Plasmon Optical Detection with Electronic Sensing by Wolfgang Knoll

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Image Processing for Laser Impact Detection in Shooting Simulators by José Antonio García Torres, Daniel Guzmán Pérez, Jhon Fredy Rincón Morantes, Daniel Felipe Molina Martínez, Cristian Camilo García Rodríguez, Jhonnatan Eduardo Zamudio Palacios

“…Moreover, wired setups limit their use in outdoor environments due to the lack of access to a power source. This study developed an image-processing-based method to replace live ammunition with a laser-emitting device. …”
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An AI-Based Open-Source Software for <i>Varroa</i> Mite Fall Analysis in Honeybee Colonies by Jesús Yániz, Matías Casalongue, Francisco Javier Martinez-de-Pison, Miguel Angel Silvestre, Beeguards Consortium, Pilar Santolaria, Jose Divasón

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Infrared Satellite Detection Limits for Monitoring Atmospheric Ammonia by Mark W. Shephard, Shailesh K. Kharol, Enrico Dammers, Christopher E. Sioris, Andrew Bell, Rik Jansen, Jerome Caron, Ralph Snel, Emanuela Palombo, Karen E. Cady-Pereira, Chris A. McLinden, Erik Lutsch, Robert O. Knuteson

“…Information on the frequency of a given detection limit, and the cumulative probability of detection, are provided as a function of instrument spectral resolution and noise. …”
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High-Quality and Enhanced-Resolution Single-Pixel Imaging Based on Spiral Line Array Laser Source by Guozhong Lei, Haolong Jia, Wenchang Lai, Wenhui Wang, Wenda Cui, Yan Wang, Hao Liu, Kai Han

“…We propose a spiral line array laser source which can generate random illumination light fields without periodicity in the normalized second-order correlation function <italic>g</italic>⁽²⁾. …”
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Distributed Decision Making for Electromagnetic Radiation Source Localization Using Multi-Agent Deep Reinforcement Learning by Jiteng Chen, Zehui Zhang, Dan Fan, Chaoqun Hou, Yue Zhang, Teng Hou, Xiangni Zou, Jun Zhao

“…The detection and localization of radiation sources in urban areas present significant challenges in electromagnetic spectrum operations, particularly with the proliferation of small UAVs. …”
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BASSET: Bandpass-adaptive Single-pulse Search Toolkit—Optimized Subband Pulse Search Strategies for Faint Narrowband Fast Radio Bursts by J. H Cao, P. Wang, D. Li, Q. H. Pan, K. Mao, C. H. Niu, Y. K. Zhang, Q. Y. Qu, W. J. Lu, J. S. Zhang, Y. H. Zhu, Y. D. Wang, H. X. Chen, X. L. Chen, J. H. Fang, Y. Feng, H. Gao, Y. F. Huang, J. Li, C. C. Miao, C. W. Tsai, J. M. Yao, S. P. You, R. S. Zhao, Q. Z. Liu, S. M. Weng, S. H. Yew, J. Zhang, L. Zhang, E. Gügercinoğlu, D. K. Zhou, W. W. Zhu

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YOLO-PEL: The Efficient and Lightweight Vehicle Detection Method Based on YOLO Algorithm by Zhi Wang, Kaiyu Zhang, Fei Wu, Hongxiang Lv

“…YOLOv8-PEL shows outstanding performance in detection accuracy, computational efficiency, and generalization capability, making it suitable for real-time and resource-constrained applications. …”
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Multiepoch Observations of the Nearby Spiral Galaxy NGC 3938 with the Chandra X-Ray Observatory by Siddhi Raut, Eric M. Schlegel, Thomas G. Pannuti, Brannon W. Jones, Jacobo Matallana

“…A total of 47 discrete merged sources from both epochs were detected at the ≈3 σ level or greater with the D25 radius. …”
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Potential Source Regions and Transportation Pathways of Reactive Gases at a Regional Background Site in Northwestern China by Quanwei Zhao, Qing He, Lili Jin, Jianlin Wang

“…Wind rose, cluster analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) methods were adopted for identifying the transport pathways and potential source regions of these atmosphere components at Akedala. …”
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The molecular prevalence of Theileria equi in the Arabian stallion in Egypt with special reference to biochemical parameters by Noora F. Thabet, Omaima M. Kandil, Omnia M. Kandil, Khalid M. Fararh

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DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

“…Improved attention, loss function, and suppression enhance detection accuracy, while lightweight C3 module reduces computation time. …”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

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Are Your kidneys ok? Detect early to protect kidney health by Joseph A. Vassalotti, Anna Francis, Augusto Cesar Soares Dos Santos Jr, Ricardo Correa-Rotter, Dina Abdellatif, Li-Li Hsiao, Stefanos Roumeliotis, Agnes Haris, Latha A. Kumaraswami, Siu-Fai Lui, Alessandro Balducci, Vassilios Liakopoulos

“…using serum creatinine to estimate kidney function and urine albumin to assess for kidney and endothelial damage. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. …”
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Toward global rooftop PV detection with Deep Active Learning by Matthias Zech, Hendrik-Pieter Tetens, Joseph Ranalli

“…It is crucial to know the location of rooftop PV systems to monitor the regional progress toward sustainable societies and to ensure the integration of decentralized energy resources into the electricity grid. However, locations of PV are often unknown, which is why a large number of studies have proposed variants of Deep Learning to detect PV panels in remote sensing data using supervised Deep Learning. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…Objective With technological advancements and the increasing demand for water resource exploration, water surface target detection plays a crucial role in various applications, such as ship navigation and maritime safety. …”
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Are Your Kidneys Ok? Detect Early to Protect Kidney Health by Joseph A. Vassalotti, Anna Francis, Augusto Cesar Soares Dos Santos Jr, Ricardo Correa-Rotter, Dina Abdellatif, Li-Li Hsiao, Stefanos Roumeliotis, Agnes Haris, Latha A. Kumaraswami, Siu-Fai Lui, Alessandro Balducci, Vassilios Liakopoulos

“…using serum creatinine to estimate kidney function and urine albumin to assess for kidney and endothelial damage. …”
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