The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. ...
The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API security, protect user data, and bolster application resilience.
The study explores various 2D feature representations including spectrogram, MFCC spectrogram, log Mel-spectrogram, and the perceptual weighted log Mel-spectrogram (PW-LMSP) for acoustic scene classification (ASC). Th...
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ISBN:
(数字)9798350386844
ISBN:
(纸本)9798350386851
The study explores various 2D feature representations including spectrogram, MFCC spectrogram, log Mel-spectrogram, and the perceptual weighted log Mel-spectrogram (PW-LMSP) for acoustic scene classification (ASC). These 2D feature representations were classified using a bottom-up broadcast neural network (BBNN). The experimental results have shown that PW-LMSP outperforms other 2D representations. Further, the proposed method (PW-LMSP with BBNN) achieves accuracies of 91.2% and 91.6% respectively on the DCASE2018 and DCASE2019 development datasets, outperforming all the submissions in DCASE2018 and DCASE2019, as well as state-of-the-art approaches.
computer vision algorithms can quickly analyze numerous images and identify useful information with high accuracy. Recently, computer vision has been used to identify 2D materials in microscope images. 2D materials ha...
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The work presents a novel wavy channel nanosheet field effect transistor (WCNSFET) and its circuit-level performance. In this work, a single nanosheet is transformed into a wave-like structure to enhance the physical ...
The work presents a novel wavy channel nanosheet field effect transistor (WCNSFET) and its circuit-level performance. In this work, a single nanosheet is transformed into a wave-like structure to enhance the physical device area, thus showing an improvement in device performance. The device and circuit level performances are analyzed using 3D TCAD simulation tools. Furthermore, the wavy channel nanosheet FETs are analyzed with different number of waves in a single sheet and compared with flat sheet-based transistors for different channel materials (Ge and GaAs). The results reveal the improvement in drive current, low propagation delay, a smooth voltage transfer characteristic, high noise margin, and low energy. The results achieved with this novel device make the device a promising candidate for next-generation low power CMOS applications.
Study on the identification and classification of fish is challenging and valuable because of its role in advancing the marine and agricultural fields. This research has benefits interms of monitoring fish populations...
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An intelligent and self-sufficient robot is essential across a wide range of fields, including transportation, industry, space exploration, and defense. Mobile robots possess the capability to undertake diverse tasks ...
An intelligent and self-sufficient robot is essential across a wide range of fields, including transportation, industry, space exploration, and defense. Mobile robots possess the capability to undertake diverse tasks such as handling materials, aiding in disaster scenarios, conducting patrols, and executing rescue operations. As a result, the development of an autonomous robot that can navigate through both unchanging and ever-changing surroundings has become important. The primary objective of mobile robot navigation revolves around ensuring the seamless and secure traversal of the robot through complex environments, starting from an initial position, and reaching a designated goal position. This paper presents the design and implementation of a Jetson Nano powered robot car which uses local sensors to interact with an unknown environment. Object following, obstacle avoidance, and wall following features are built for the car to navigate to reach its desired destinations.
Magnetic induction tomography (MIT) is a technique used for imaging electromagnetic properties of objects using eddy current effects. The non-linear characteristics had led to more difficulties with its solution espec...
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This work demonstrates the development of a prototype system that could improve urban and digital accessibility for People with Disability - PwD. The research involves using an academic questionnaire to enable a wider...
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ISBN:
(数字)9798350362053
ISBN:
(纸本)9798350362060
This work demonstrates the development of a prototype system that could improve urban and digital accessibility for People with Disability - PwD. The research involves using an academic questionnaire to enable a wider perspective of the central subject and assessing the effectiveness of the proposed solution. The main goal is to help social integration and make the future solution implementable for smart cities through an experiment in an academic campus. The dissertation is related to technological and social issues that might be used as a resource by researchers, public or private bodies interested in more profound studies. The document recognizes the lack of studies on this subject, especially in Brazil because there are few available articles. The prototype system is designed to tackle the issues faced by persons with disability in urban settings through platforms, applications and mobile phones as it proposes a comprehensive set of solutions when addressing accessibility for PwDs. In turn, this research fosters knowledge advancements in the field of urban accessibility and provides vital recommendations for developing inclusive technologies and policies.
The concept of Digital Twin has been widely used by researchers to represent physical entities in computer-generated reality in the metaverse. In this research, a novel concept of “Mobile Twin” is coined. Mobile Twi...
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ISBN:
(数字)9798350349719
ISBN:
(纸本)9798350349726
The concept of Digital Twin has been widely used by researchers to represent physical entities in computer-generated reality in the metaverse. In this research, a novel concept of “Mobile Twin” is coined. Mobile Twin serves as a replica of a mobile device in the virtual environment enabling communication. The purpose of introducing Mobile Twin in the metaverse is to bring mobility and benefits similar to tangible mobile devices while eliminating the need for individual energy sources, storage limitations, resource usage, and efficiency. The true benefits of a mobile twin can be achieved with an architecture where computing nodes are decentralized, data processing is near the network's edge with faster response times and reduced latency. For this purpose, the mobile twin-based applications of metaverse are built over edge computing-based network architecture. This idea introduced the aspect of “Revolutionary Ultra-low latency (RULL)” in the metaverse.
The current study used cutting-edge techniques to experimentally test the early diagnosis of diabetes via retinal scans. The goal was to enable effective disease prediction and management by facilitating quick and pre...
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ISBN:
(数字)9798350378511
ISBN:
(纸本)9798350378528
The current study used cutting-edge techniques to experimentally test the early diagnosis of diabetes via retinal scans. The goal was to enable effective disease prediction and management by facilitating quick and precise medical diagnostics. Three processes were involved in the development of a Diabetic Retinopathy (DR) diagnosis tool: feature extraction, feature reduction, and image classification. The research employed Apache Spark, a distributed computing framework, to manage large datasets and enhance the performance of the multilayer perceptron (MLP) model via hyperparameter tuning and cross validation. Utilizing resources more effectively and achieving faster training times were made possible by Apache Spark. To support data-driven decision-making, the study also emphasized the significance of distributed platforms for analyzing large amounts of real-time diabetic data. To produce discriminative features for classification, the VGG16 architecture was employed for feature extraction. In the last epoch, the MLP model performed remarkably well, with an accuracy of 97%. The study also underlined the value of distributed platforms for data-driven decision-making by analyzing substantial volumes of real-time diabetes data.
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