Abdulraqeb Alhammadi^1,*, Zaid Ahmed Shamsan², Arijit De³

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1889-1905, 2024, DOI:10.32604/cmc.2024.051487 - 15 August 2024

Abstract Indoor localization systems are crucial in addressing the limitations of traditional global positioning system (GPS) in indoor environments due to signal attenuation issues. As complex indoor spaces become more sophisticated, indoor localization systems become essential for improving user experience, safety, and operational efficiency. Indoor localization methods based on Wi-Fi fingerprints require a high-density location fingerprint database, but this can increase the computational burden in the online phase. Bayesian networks, which integrate prior knowledge or domain expertise, are an effective solution for accurately determining indoor user locations. These networks use probabilistic reasoning to model relationships among… More >

Di Wang, Yuefei Zhu, Jinlong Fei^*, Maohua Guo

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2253-2276, 2024, DOI:10.32604/cmc.2024.049504 - 15 May 2024

Abstract Website fingerprinting, also known as WF, is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination, even when using the Tor anonymity network. While advanced attacks based on deep neural network (DNN) can perform feature engineering and attain accuracy rates of over 98%, research has demonstrated that DNN is vulnerable to adversarial samples. As a result, many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success. However, these methods suffer from high bandwidth overhead or require access to the target… More >

Haifeng Lin^1,2, Xiangfeng Liu², Chen Chen², Zhibo Liu², Dexin Zhao³, Yiwen Zhang⁴, Weizhuang Li⁴, Mingsheng Cao^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 939-956, 2024, DOI:10.32604/cmes.2023.028656 - 22 September 2023

Abstract Identifying a device and detecting a change in its position is critical for secure devices management in the Internet of Things (IoT). In this paper, a device management system is proposed to track the devices by using audio-based location distinction techniques. In the proposed scheme, traditional cryptographic techniques, such as symmetric encryption algorithm, RSA-based signcryption scheme, and audio-based secure transmission, are utilized to provide authentication, non-repudiation, and confidentiality in the information interaction of the management system. Moreover, an audio-based location distinction method is designed to detect the position change of the devices. Specifically, the audio… More >

Jianmao Xiao¹, Ridong Huang¹, Jiangyu Wang¹, Zhean Zhong¹, Chenyu Liu¹, Yuanlong Cao^1,*, Chuying Ouyang²

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2815-2834, 2023, DOI:10.32604/csse.2023.039716 - 09 November 2023

Abstract Audio copyright is a crucial issue in the music industry, as it protects the rights and interests of creators and distributors. This paper studies the current situation of digital music copyright certification and proposes a music copyright certification framework based on “blockchain + edge computing mode,” abbreviated as MBE, by integrating edge computing into the Hyperledger Fabric system. MBE framework compresses and splits the audio into small chunks, performs Fast Fourier Transform (FFT) to extract the peak points of each frequency and combines them to obtain unique audio fingerprint information. After being confirmed by various… More >

Hyeon Park¹, SeoYeon Kim², Seok Min Ko¹, TaeGuen Kim^2,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1891-1909, 2023, DOI:10.32604/cmc.2023.039464 - 30 August 2023

Abstract The rapid growth of modern vehicles with advanced technologies requires strong security to ensure customer safety. One key system that needs protection is the passive key entry system (PKES). To prevent attacks aimed at defeating the PKES, we propose a novel radio frequency (RF) fingerprinting method. Our method extracts the cepstral coefficient feature as a fingerprint of a radio frequency signal. This feature is then analyzed using a convolutional neural network (CNN) for device identification. In evaluation, we conducted experiments to determine the effectiveness of different cepstral coefficient features and the convolutional neural network-based model. More >

Yun Fen Yong^1,*, Chee Keong Tan¹, Ian Kim Teck Tan², Su Wei Tan¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1801-1818, 2023, DOI:10.32604/cmc.2023.032710 - 22 September 2022

Abstract A robust radio map is essential in implementing a fingerprint-based indoor positioning system (IPS). However, the offline site survey to manually construct the radio map is time-consuming and labour-intensive. Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys. This paper presents a novel fingerprint interpolator using a multi-path loss model (M-PLM) to create the virtual fingerprints from the collected sample data based on different signal paths from different access points (APs). Based on the historical signal data, the poor signal paths are… More >

Edgar Scavino^1,*, Mohd Amiruddin Abd Rahman¹, Zahid Farid²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 379-397, 2023, DOI:10.32604/cmc.2023.023824 - 22 September 2022

Abstract Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting… More >

Zhiguo Lu¹, Yuhong Zheng^1,*, Pengchong Zhang², Boyuan Fan³, Aimin Yu⁴, Li Fu^3,*

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2549-2558, 2022, DOI:10.32604/phyton.2022.021288 - 12 July 2022

Abstract In this communication, we used electrochemical sensor for recording the electrochemical profiles of eleven species of Yulania spp. from leaf extract. Two solvents and two buffer conditions were used for electrochemical fingerprints collection. Their electrochemical fingerprints can be converted to different patterns and consequently for species recognition. The results indicate the pattern recognition is much convenient than that of the recognition of species directly using voltammetric signal. The current information in electrochemical fingerprinting represents the type and amount of electrochemically active molecules, which linked to the genetic differences among the plants. Therefore, the electrochemical fingerprints were More >

Muhammad Waleed Pasha¹, Mir Yasir Umair¹, Alina Mirza^1,*, Faizan Rao¹, Abdul Wakeel¹, Safia Akram¹, Fazli Subhan², Wazir Zada Khan³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1631-1652, 2021, DOI:10.32604/cmc.2021.018205 - 21 July 2021

Abstract Due to the inability of the Global Positioning System (GPS) signals to penetrate through surfaces like roofs, walls, and other objects in indoor environments, numerous alternative methods for user positioning have been presented. Amongst those, the Wi-Fi fingerprinting method has gained considerable interest in Indoor Positioning Systems (IPS) as the need for line-of-sight measurements is minimal, and it achieves better efficiency in even complex indoor environments. Offline and online are the two phases of the fingerprinting method. Many researchers have highlighted the problems in the offline phase as it deals with huge datasets and validation… More >

Riaz Ahmad¹, Muhammad Akbar Anjum^1,*, Safina Naz¹, Rashad Mukhtar Balal²

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 17-34, 2021, DOI:10.32604/phyton.2020.011680 - 20 November 2020

Abstract Selection and use of molecular markers for evaluation of DNA polymorphism in plants are couple of the most important approaches in the field of molecular genetics. The assessment of genetic diversity using morphological markers is not sufficient due to little differentiating traits among the species, genera or their individuals. Morphological markers are not only highly influenced by environmental factors but skilled assessment is also prerequisite to find the variations in plant genetic resources. Therefore, molecular markers are considered as efficient tools for detailed DNA based characterization of fruit crops. Molecular markers provide new directions to More >