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9th International Conference on Cloud Computing and Internet of Things, CCIOT 2024

作者： Vu-Thanh, Trung He, Jing Duong-Bao, Ninh Thi, Luong Nguyen Lee, Seon-Woo Nguyen-Huu, Khanh College of Computer Science and Electronic Engineering Hunan University Changsha China Faculty of Mathematics and Informatics Dalat University Dalat Viet Nam Faculty of Information Technology Dalat University Dalat Viet Nam Division of Software Hallym University Chuncheon Korea Republic of Department of Electronics and Telecommunications Dalat University Dalat Viet Nam

ISBN: (纸本)9798400717161

Recently, WiFi Fingerprinting-based indoor positioning systems have gained significant attention due to the low cost of infrastructure deployment. In the data collection process, a higher density of reference points may lead to better positioning results. However, it makes this process time-consuming and laborious. To solve this problem, this study applies and compares different interpolation methods to enrich the fingerprint database without increasing the cost of the collection process. To evaluate the performance of the chosen methods, five interpolation methods are implemented in a multi-condition WiFi Fingerprinting dataset. Moreover, to check the robustness of the methods, different numbers of reference points are considered when creating the new interpolated fingerprint databases. According to the results, inverse distance weighting (IDW) is the most suitable interpolation method with low complexity and stable performance. The IDW-based database achieves an average interpolation error of less than 6 dBm compared to the original database. When applying this interpolated database to perform positioning tasks, it helps reduce the collection cost by 30% with slightly lower positioning results compared to the original database. This work demonstrates the feasibility of using interpolation to ease the data collection process of WiFi Fingerprinting, especially in complex and big areas such as airports or hospitals. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Wi-Fi

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Comprehensive Analysis and Remediation of Insecure Direct Object References (IDOR) Vulnerabilities in Android APIs 1

Comprehensive Analysis and Remediation of Insecure Direct Ob...

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1st IEEE International Conference on Cryptography, informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Abdullah, Roni Reza Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia National Institute of Science and Technology Faculty of Informatics Engineering Jakarta12630 Indonesia Bina Nusantara University Binus Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

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. © 2023 IEEE.

关键词： Sensitive data

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PIT Performance Measurement using NFD Pipeline Parameters in Named Data Networking (NDN)

PIT Performance Measurement using NFD Pipeline Parameters in...

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International Conference on Wireless and Telematics (ICWT)

作者： Adi Sucipto Syaiful Ahdan Iskandar Nana Rachmana Syambas School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Indonesia

ISBN: (数字)9798350377057

ISBN: (纸本)9798350377064

Although NDN is an entirely new architecture, its design principles are based on the success of the current Internet, they represent our knowledge of the advantages and disadvantages of the current Internet architecture, and they can be implemented gradually using the operations of the current Internet. The Pending Interest Table (PIT), the Forwarding Information Base (FIB), and the Content Store (CS) are the three data structures found inside the NDN router. Interest sent upstream to the content source is tracked by the Pending Interest Table (PIT), for data to be transmitted to requesters downstream. PIT is also used for measurement, loop detection, and the containment of recently satisfied interest. In this study, we did the simulation to measure and analyze the performance of PIT in NDN using NFD Pipeline Measurements. The NDNSim simulator was used in the research to observe PIT performance. The findings of the simulation and analysis indicated that in an NDN network, Satisfied Interest was influenced by the granularity of a prefix. At the number of interests 1000, the results showed a decrease in packets, including a decrease of around 21% in the Ininterest packet, and around 30% inSatisfiedInterest and InData. The effect of Prefix length also decreased in Ininterest ranging from 0.014-0.015%, while in inSatisfiedInterest and InData it ranged from 4.2-8.5%. The PIT’s performance was influenced by the length of the prefix and the number of interest messages the customer sent.

关键词： Wireless communication Simulation Pipelines Memory management Machine learning Telematics Data structures

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Random Load Balancing in Mini-NDN Using Modified Inherent Topology 9

Random Load Balancing in Mini-NDN Using Modified Inherent To...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Pratama, Cendika Sahid Arrachman, Muhammad Iqbal Nurrasyid, Muhammad Shafly Zaki Hamidi, Eki Ahmad Negara, Ridha Muldina Ahdan, Syaiful Mayasari, Ratna Syambas, Nana Rachmana School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Uin Sunan Gunung Djati Bandung Electrical Engineering Department Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia

ISBN: (纸本)9798350305029

Named Data Networking (NDN) is a newly developing networking method that focuses on information, compared to TCP/IP, which focuses on hosts. This study proposed a solution to the growing complexity of computer networks. The fundamental problem will still be able to be found, one of them being difficulty in accessing a node as data traffic is piling up. One of the solutions is load balancing, which is implementing a system that will redirect packets to different service providers to ease up the load and reduce the number of packets that are dropped due to timeouts. This paper analyses the impact of load balancing in an extreme case emulated environment using Mini-NDN and random load balancing strategy. From the results gathered, implementing random load balancing to the consumer nodes decreases-and in some cases eliminates-dropped packets. In addition, implementing load balancing stabilizes packets' RTT (Round Trip Time) but increases the average RTT compared to using best route forwarding in an unloaded environment. © 2023 IEEE.

关键词： Topology

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Development of Digital Signature Features Using MVVM Architecture (Case Study of the Moshelp Application by PT Emos Global Digital) 6

Development of Digital Signature Features Using MVVM Archite...

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6th International Conference on informatics, Multimedia, Cyber and Information System, ICIMCIS 2024

作者： Pahlawan, Muchamad Reza Cholil, Widya Adrezo, Muhammad Widiyanto, Didit Gusti, Kharisma Wiati Chen, Hsing-Chung Universitas Pembangunan Nasional Veteran Jakarta Informatics Faculty of Computer Science Jakarta Indonesia Computer Science and Information Engineering Asia University Taiwan

ISBN: (纸本)9798331533243

EMOS Global Digital is currently enhancing security across various sectors to meet security certification requirements, including securing digital project submission processes. However, the existing system faces threats to document integrity. A solution to this issue is to update the problematic feature with a more secure one. Specifically, the feature in question is project approval, which can be updated to use digital signatures. Currently, Moshelp utilizes the Model-View-ViewModel (MVVM) architecture, which separates the visual elements from the information flow, allowing for parallel and efficient development. Previous research also shows that this architecture improves application performance and facilitates code modification and maintenance. With this update, the approval, previously represented only by a date, will be changed to a quick response code that verifies the content of a document, thus enhancing document integrity in the project approval process. © 2024 IEEE.

关键词： Digital Signature Integrity Model-View-ViewModel Software Architecture

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Optimizing Art Studio Connectivity: A Haversine and Greedy Algorithm Approach for Navigation in Cirebon Indonesia 17

Optimizing Art Studio Connectivity: A Haversine and Greedy A...

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17th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2023

作者： Permana, Indra Surya Arlovin, Teguh Hidayat, Taufik Sarief, Ivany Solihin, Hanhan Hanafiah Mulyadi, Cecep Deni Institut Teknologi Dan Kesehatan Mahardika Department of Informatics Engineering Cirebon Indonesia Universitas AMIKOM Department of Computer Engineering Yogyakarta Indonesia Universitas Indonesia Department of Electrical Engineering Jakarta Indonesia Universitas Sangga Buana Faculty of Engineering Department of Electrical Engineering Bandung Indonesia Universitas Sangga Buana Department of Information System Bandung Indonesia Universitas Sangga Buana Faculty of Engineering Bandung Indonesia

ISBN: (纸本)9798350309164

The proposed geographic information system (GIS) provides a systematic approach to locating and connecting art studios, enabling cultural institutions, artists, and students to collaborate and share resources more efficiently. The implementation of a structured GIS and Haversine Formula and Greedy Algorithm can improve the management and connectivity of art studios in Cirebon, fostering connections and collaboration between art studios, artists, and cultural institutions. This research used a greedy algorithm to find the shortest route from user's current location to the destination point, i.e., Art Gallery. The Greedy Algorithm is a problem-solving approach that aims to find an optimal solution by iteratively selecting the best local option. The Haversine formula is used to calculate the distance from each connected node using the haversine formula, which converts latitudes and longitudes from degrees to radians and calculates the differences in latitude and longitude. In implementing the nearest art studio search system, the Haversine Formula combined with Greedy Algorithm can be employed as an alternative for search logic since it can directly calculate the distance from the initial point or user's selected point by utilizing easily identifiable reference points. © 2023 IEEE.

关键词： Studios

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Onboard Perception-Assisted High Fidelity Simulation Framework for Autonomous Planetary Soft-Landing

Onboard Perception-Assisted High Fidelity Simulation Framewo...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Alibekov, Ulugbek Banerjee, Avijit Satpute, Sumeet Gajanan Nikolakopoulos, George ERASMUS MUNDUS JOINT MASTER in Intelligent Field Robotic Systems Faculty of Informatics Eötvös Loránd University Budapest Hungary Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents an onboard perception-assisted high-fidelity simulation framework for autonomous planetary soft-landing, enabling visual information processing tightly integrated with advanced onboard guidance system in a realistic simulation environments. Utilizing the open source Unity game engine, a physics-based simulation toolbox integrated with the Robotic Operating System (ROS2), we effectively emulate the motion of spacecraft approaching planetary terrain. The simulation environment features a realistic 3D terrain model and a lander spacecraft equipped with onboard camera to effectively capture detailed local terrain images. The simulation engine accurately captures the spacecraft’s 6-degrees of freedom motion, seamlessly integrating space craft orientation with the associated camera feed while incorporating various illumination conditions using a light source representing the Sun. To demonstrate the efficacy of the framework, we implement a recently developed attitude-constrained minimum jerk guidance algorithm to emulate spacecraft motion. Concurrently, the visual feed from the onboard RGB camera is processed through a gradient extraction-based perception system, providing the visual odometer. This system identifies provably safe landing sites, effectively avoiding potential risks of landing on uneven terrain. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Planetary landers

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Sparseswin: Swin Transformer with Sparse Transformer Block

SSRN

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SSRN 2023年

作者： Pinasthika, Krisna Laksono, Blessius Sheldo Putra Irsal, Riyandi Banovbi Putera Shabiyya, Syifa' Hukma Yudistira, Novanto Faculty of Computer Science Informatics Engineering Department Brawijaya University Malang65145 Indonesia

Advancements in computer vision research have put transformer architecture as the state-of-the-art in computer vision tasks. One of the known drawbacks of the transformer architecture is the high number of parameters, this can lead to a more complex and inefficient algorithm. This paper aims to reduce the number of parameters and in turn, made the transformer more efficient. We present Sparse Transformer (SparTa) Block, a modified transformer block with an addition of a sparse token converter that reduces the number of tokens used. We use the SparTa Block inside the Swin-T ar-chitecture (SparseSwin) to leverage Swin’s capability to downsample its input and reduce the number of initial tokens to be calculated. The proposed SparseSwin model outperforms other state-of-the-art models in image classification with an accuracy of 86.96%, 97.43%, and 85.35% on the ImageNet100, CIFAR10, and CIFAR100 datasets respectively. Despite its fewer parameters, the result highlights the potential of a transformer architecture using a sparse token converter with a limited number of tokens to optimize the use of the transformer and improve its performance. © 2023, The Authors. All rights reserved.

关键词： computer vision

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How we can use text classification in the Back-Office environment of a bank as 'business as usual' solution 17

How we can use text classification in the Back-Office enviro...

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17th IEEE International Symposium on Applied Computational Intelligence and informatics, SACI 2023

作者： Krutilla, Zsolt Kovari, Attila Óbuda University Doctoral School of Applied Informatics and Applied Mathematics Budapest Hungary Informatics Institution University of Dunaújváros Dunaújváros Hungary Institute of Engineering Alba Regia Technical Faculty buda University Budapest Hungary Institute of Digital Technology Faculty of Informatics Eszterházy Károly Catholic University Eger Hungary University of Dunaújváros Institute of Engineering Department of Natural Science Dunaújváros Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350321104

Natural Language Processing nowadays provides scientists with many research areas and opportunities, but as with most applied sciences, our goal in Natural Language Processing is to refine the underlying science and technology until it can be used reliably for business purposes. Transformer models, such as GPT or BERT, are currently showing outstanding results in the field of natural-language processing, but they require huge computational power and data to teach, but these conditions can only be met by larger research centers and large companies, and their inaccuracy makes them unsuitable for use as a 'business as usual' (BAU) solution. In this paper, we present a solution that is able to overcome these problems by focusing on accuracy and usability, and that can also bring a new perspective to the process of teaching deep learning models. © 2023 IEEE.

关键词： Information retrieval systems

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Volumetric Hippocampus Segmentation Using 3D U-Net Based On Transfer Learning

Volumetric Hippocampus Segmentation Using 3D U-Net Based On ...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Ramadhan Sanyoto Sugiharso Widodo I Ketut Eddy Purnama Reza Fuad Rachmadi Department of Electrical Engineering Department of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350322996

ISBN: (纸本)9798350323009

The hippocampus, a crucial component of the human brain, is involved in fundamental cognitive processes such as learning, memory, and spatial navigation. However, it is susceptible to several neuropsychiatric disorders, including epilepsy, Alzheimer’s disease, and depression. Utilizing Magnetic Resonance Imaging (MRI) techniques with efficient spatial navigation capabilities is crucial for assessing the physiological condition of the hippocampus. Labeling the hippocampus on MRI images primarily depends on manual methods, which are time-consuming and prone to errors between observers. The issue with MRI image processing lies in its demanding computational requirements and lengthy duration. Furthermore, there is a need for more three-dimensional hippocampal datasets for training deep-learning models, in which 3D labeled medical datasets are often scarce in medical imaging. This paper introduces a 3D U-Net architecture that utilizes a transfer learning model to segment the hippocampus from different pre-trained model scenarios. The results of all test scenarios indicate that the suggested model exhibits an average Dice Score, Intersection over Union (IoU) Score, and Sensitivity exceeding 0.85, 0.75, and 0.80, respectively. The proposed methodology enhances the model’s ability to generalize within a shorter timeframe, even when dealing with limited volumetric datasets. These results are achieved through transfer learning, which decreases computational complexity by utilizing pre-learned characteristics from previous tasks.

关键词： Solid modeling Three-dimensional displays Navigation Magnetic resonance imaging Computational modeling Volume measurement Transfer learning

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