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Towards Smart Farming: Simulation Framework to Exploit Network Connectivity for End-to-End data Transmission

Towards Smart Farming: Simulation Framework to Exploit Netwo...

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international conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA)

作者： Dongyang Huo Sri Devi Ravana Asad Waqar Malik Anis Ur Rahman Ismail Ahmedy Department of Information Systems Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur Malaysia Department of Computing National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Computer Systems & Technology Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781665493352

Traditional agriculture is highly dependent on human participation and experience. Therefore, it is not possible to guarantee crop yield and quality while expanding the production scale. In recent years, based on the continuous development and innovation of IoT and ICT technologies, the concept of smart farming has started to receive the attention of researchers and farmers. However, many existing smart agriculture applications and research are conducted under controlled environments such as greenhouse farming, vertical farming, and hydroponic farming, etc. Few studies have shifted attention to large-scale arable agriculture, thus neglecting the scalability of the system. This work presents a simulation stack (digital mapping) in which the results of running the simulation model in a large-scale class of real-world scenarios are used to enhance the further performance of the proposed farming system in large-scale scenarios.

关键词： Smart agriculture Technological innovation System performance Scalability Production data models Software

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Improved Image Encryption Technique for Reversible data Hiding using Binary Block Embedding

Improved Image Encryption Technique for Reversible Data Hidi...

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advances in computing and Future Communication technologies (ICACFCT), international conference on

作者： Subodh Kumar Rajendra Kumar Department of Computer Science Jamia Millia Islamia University Delhi India

ISBN: (数字)9781665420761

ISBN: (纸本)9781665420778

This paper proposed an improved binary block embedding approach for embedding the “secret data” into any “binary image”. In this approach we propose an algorithm which embeds the secret information into an image after finding the capacity. The proposed method divides the pixel values into good and bad type depending on the pixel values. Embedding rate, block capacity, correlation analysis is deduced for security analysis.

关键词： Correlation Communications technology Encryption Security

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A Survey on Blockchain Technology Supported Approaches for Healthcare System, Open Issues and Challenges

A Survey on Blockchain Technology Supported Approaches for H...

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international conference on Mathematics, Actuarial science, Computer science and Statistics (MACS)

作者： Sumit Kumar Rana Sanjeev Kumar Rana Arun Kumar Rana Kashif Nisar Tariq Rahim Soomro Sana Nisar Computer Science and Engineering Maharishi Markandeshwar (deemed to be University) Ambala Haryana India Electronics and Communication Engineering Panipat Institute of Engineering and Technology Panipat Haryana India Victorian Institute of Technology (VIT) Adelaide South Australia College of Computer Science and Information Systems Institute of Business Management Karachi Sindh Pakistan Faculty of Computing and Informatics University Malaysia Sabah Kota Kinabalu Sabah Malaysia

ISBN: (纸本)9781665460729

In the last few years, technological development has multiplied. New technologies are affecting almost every industry. One of these which noticed the abrupt change in their ecosystem is the healthcare industry. As this industry has a direct impact on the human lives so adoption of new technology is not so easy. Proper testing and trials are performed before amalgamating any new technology with the healthcare system. Emerging technologies are being employed to deliver better health-related services to patients. Different communication and information collection technologies are used to maintain and access patients' health data to authorized users. But with the employment of technology, health data security and privacy-related issues are increasing. Maintaining trust among multiple entities of the healthcare system is a challenging task. One emerging technology, distributed ledger technology (DLT), is creating some hope for resolving the fears mentioned above of the healthcare ecosystem. Attributes like Security, privacy and authentication can be enhanced by integrating this technology with the healthcare ecosystem. This study examines the role of distributed ledger technology in the healthcare system while highlighting how some aspects of this disruptive technology can completely alter current business practices. To achieve this, the theoretical foundations of numerous research papers published in prestigious scientific journals and several reports from industries are included in this survey. This helps to streamline our analysis and fully capture the constantly expanding blockchain domain. This survey also identifies several research holes and prospective areas for further study using these findings as a starting point. Both academics and practitioners should find great value in these discoveries. This survey presents a comprehensive evaluation of current DLT- supported approaches in the healthcare system. and provides benefits and limitations of the recent work. Th

关键词： Industries Access control Privacy Distributed ledger Ecosystems Smart contracts Medical services

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Secure ciphertext policy using blowfish hybridized weighted attribute-based encryption 1st

Secure ciphertext policy using blowfish hybridized weighted ...

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1st international conference on Frontiers in Smart Systems technologies, ICFSST 2019

作者： Porkodi, S. Kesavaraja, D. Department of Computer Science and Engineering Dr. Sivanthi Aditanar College of Engineering TiruchendurTamil Nadu India

ISBN: (纸本)9789811550287

There are lots of application which are been used by the people where a user’s data has to be protected from the attackers who steal the data by using fake identities which makes difficult to find the real culprit. The main issue is to give strong security to the data and to minimize computational cost with an efficient key management system. We propose a new encryption method in this paper, based on user attributes and access control policy using blowfish which is hybridized and weighted encryption which is a combination of features from two different algorithms to provide a high security to user data and to generate key efficiently. The two algorithms ciphertext policy attribute encryption with access control policy and the hierarchical identity-based encryption with weighted attributes are included. Here, based on the priority, the weights are assigned to the attributes and then the message is combined with access control policy given by the user and encrypted. This algorithm is used to find the culprit who is misusing the application. Also we can add that person to the blacklist, and all the accounts associated with that identity can also be blacklisted. The proposed system provides multi-authority security, efficiency, collusion resistant, secure against chosen plain text attack and reliable. © Springer Nature Singapore Pte Ltd 2021.

关键词： data transfer

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Detection of Abnormal Crowd Behavior Based on Graph Convolutional Neural Network

Detection of Abnormal Crowd Behavior Based on Graph Convolut...

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IEEE international Symposium on Information (IT) in Medicine and Education, ITME

作者： Xiang Zhou Ruliang Xiao Department of Computing and Information Science Fuzhou Institute of Technology Fuzhou Fujian China College of Computer and Cyber Security Fujian Normal University Fuzhou Fujian China

With the increasing demand for public safety precautions, the accuracy and timeliness of abnormal crowd behavior detection is gradually improving. Therefore, with the development of the technology for the abnormal crowd behavior, it’s even more demanding on how to effectively prevent the occurrence of accidents and eliminate the impact of disasters on the society. This article first introduces the current applications of abnormal behavior detection and the research and development of related technologies. Second, it proposes a method for detecting abnormal crowd behavior based on Graph Convolutional Neural Network (GCN). This method first proposes to effectively and accurately locate the abnormal behavior characteristics through the extraction of abnormal behavior characteristics from the auto-encoder of the surveillance video. With the construction of the graph classification model based on SAGPool, the classification of normal and abnormal behavior is carried out. Finally, experimental data show that data displayed with this method meet the expected requirements.

关键词： Uncertainty Surveillance Sociology Feature extraction Behavioral sciences Safety Convolutional neural networks

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Security Analysis for Virtual Machine Allocation in Cloud computing

Security Analysis for Virtual Machine Allocation in Cloud Co...

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Cyber Resilience (ICCR), international conference on

作者： Tahir Alyas Karamath Ateeq Mohammed Alqahtani Saigeeta Kukunuru Nadia Tabassum Rukshanda Kamran Department of Computer Science Lahore Garrison University Lahore Pakistan School of Information Technology Skyline University College University City Sharjah Sharjah UAE Department of Computer Information Systems College of Computer Science and Information Technology Abdulrahman Bin Faisal University Dammam Saudi Arabia Assistant professor in management Faculty Swiss Business school. RAK. UAE Department of Computer Science Virtual University of Pakistan Pakistan Faculty of Compter science and Information Technology Universiti Kota Samarahan Sarawak East Malaysia

ISBN: (数字)9781665461221

ISBN: (纸本)9781665461238

A huge number of cloud users and cloud providers are threatened of security issues by cloud computing adoption. Cloud computing is a hub of virtualization that provides virtualization-based infrastructure over physically connected systems. With the rapid advancement of cloud computing technology, data protection is becoming increasingly necessary. It's important to weigh the advantages and disadvantages of moving to cloud computing when deciding whether to do so. As a result of security and other problems in the cloud, cloud clients need more time to consider transitioning to cloud environments. Cloud computing, like any other technology, faces numerous challenges, especially in terms of cloud security. Many future customers are wary of cloud adoption because of this. Virtualization technologies facilitates the sharing of recourses among multiple users. Cloud services are protected using various models such as type-I and type-II hypervisors, OS-level, and unikernel virtualization but also offer a variety of security issues. Unfortunately, several attacks have been built in recent years to compromise the hypervisor and take control of all virtual machines running above it. It is extremely difficult to reduce the size of a hypervisor due to the functions it offers. It is not acceptable for a safe device design to include a large hypervisor in the Trusted computing Base (TCB). Virtualization is used by cloud computing service providers to provide services. However, using these methods entails handing over complete ownership of data to a third party. This paper covers a variety of topics related to virtualization protection, including a summary of various solutions and risk mitigation in VMM (virtual machine monitor). In this paper, we will discuss issues possible with a malicious virtual machine. We will also discuss security precautions that are required to handle malicious behaviors. We notice the issues of investigating malicious behaviors in cloud computing, give t

关键词： Cloud computing Trusted computing Virtual machine monitors Memory Virtual machining Behavioral sciences Security

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CANBERT: A Language-based Intrusion Detection Model for In-vehicle Networks

CANBERT: A Language-based Intrusion Detection Model for In-v...

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international conference on Machine Learning and Applications (ICMLA)

作者： Ebelechukwu Nwafor Habeeb Olufowobi Department of Computing Sciences Villanova University Villanova PA USA Department Computer Science and Engineering University of Texas at Arlington Arlington TX USA

Controller Area networks (CAN) provide a standard means of communicating across vehicular electronic units without a centralized computing unit or complex dedicated wiring. Despite the benefits offered by in-vehicle networks, CAN networks have been susceptible to network attacks such as replay, fuzzing, and denial of service attacks. In addition, the proliferation of internet-connected vehicles motivates the need to build a robust and secure vehicular network system. Deep learning-based language models such as Bidirectional Encoder Representations from Transformers (BERT) models have proven to produce remarkable results for natural language tasks. BERT models provide a deep understanding of the underlying semantics in textual data. In this paper, we propose CANBERT, a language-based intrusion detection model for CAN bus. We leverage the power of transformer models to provide the detection of malicious attacks on the CAN network. We provide a thorough analysis of our approach using a CAN dataset produced in a realistic driving scenario which consists of a combination of normal data and malicious data from various types of attack scenarios such as Denial of Service (DoS), fuzzy, and impersonation attacks. Our approach is able to detect all of the attacks with high precision and accuracy. In addition, we compare our method with other baseline models and state-of-the-art deep learning intrusion detection approach for in-vehicle networks.

关键词： Wiring Vehicular and wireless technologies Bit error rate Semantics Natural languages Intrusion detection Transformers

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Cryptanalysis of Lightweight Block Ciphers using Metaheuristic Algorithms in Cloud of Things (CoT)

Cryptanalysis of Lightweight Block Ciphers using Metaheurist...

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data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), international conference on

作者： Md Saquib Jawed Mohammad Sajid Department of Computer Science Aligarh Muslim University Aligarh India

ISBN: (纸本)9781665490597

The Cloud of Things (CoT) has transformed communication and network technologies by expanding the Iimitation of IoT devices. The Cloud of Things is a fusion of Cloud computing with IoT that provides endless storage, networking, and compute capabilities to IoT devices. Cloud of Things (CoT) has substantially boosted IoT applications in healthcare, automotive, agriculture, education, welfare, and businesses. Even though Cloud of Things (CoT) is scalable, faster, cost-effective, and remotely accessible,it also faces many challenges like interoperability, compatibility, performance, longevity, and security. Security is the biggest hurdle in adopting Cloud of Things (CoT) because it directly involves users’ private data. Researchers and academicians are equally concerned and proposed various lightweight block ciphers (LWBC) to secure the user’s data. In this paper, the relative cryptographic strength of three lightweight block ciphers (LWBC) is measured by performing Cryptanalysis with three metaheuristic algorithms using the proposed framework. The chosen three lightweight block ciphers (LWBC) are SIMON, SPECK, and PRESENT ciphers, which belong to different categories of Lightweight Block Ciphers (LWBC), and three metaheuristic algorithms are Cuckoo Search (CS), Whale optimization Algorithm (WOA), and Salp Swarm Algorithm (SSA). The result of the experiments shows that SIMON and SPECK are equally strong while PRESENT is a relatively weak cipher. Also, the Cuckoo Search (CS) is found to be better than both WOA and SSA. However, for the weak keys, WOA is able to break all three ciphers completely.X

关键词： Performance evaluation Ciphers Cloud computing Metaheuristics Medical services Immunity testing Whale optimization algorithms

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A brief review on wearable ECG devices and processing techniques for fall risk assessment, prevention and detection

A brief review on wearable ECG devices and processing techni...

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Mediterranean conference on Embedded computing (MECO)

作者： Amar Silajdž ić Anja Trkulja Asja Muharemović Lejla Gurbeta-Pokvić Edin Begić Almir Badnjević Faculty of Engineering and Natural Sciences International Burch University Sarajevo Bosnia and Herzegovina Sarajevo Medical School Sarajevo School of Science and Technology &#x0026 General Hospital Prim. Dr. Abdulah Naka&#x0161 &#x201D Sarajevo Bosnia and Herzegovina Faculty of Pharmacy University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9781665468282

ISBN: (纸本)9781665468299

As a consequence of the progress of the modern mobile medicine, wearable technologies, especially ECG wearables tend to become indispensable part of peoples' lives. As applications and devices for tracking cardiac electrical activity are rapidly entering the market, it is important to compare individual ECG wearable devices. This review takes a systematic approach on the analysis of wearable ECG devices. It provides a detailed introduction on the updated methods, to create a comparison between individual features of devices, and to evaluate techniques for fall risk assessment, diagnosis, and prevention. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) instructions were used as a report standard. In an effort to collect the appropriate data, various databases were queried together with specific subject-oriented keywords. This was combined with different inclusion and exclusion criteria to find the relevant data. To further improve the data gathering and reduce bias, a Zotero tool was used. The results of this paper show the comparison of the different devices and their features. All findings can be observed in the table and in words. As information for the QardioCore are scarce, all six authors consolidated on the VitalCore being the most accurate ECG wearable device, as its sensitivity and specificity are the highest. Recent advances in wearable ECG devices allow for more trouble free out of clinic fall risk assessment, detection and prevention. As people tend to prefer the comfort of their home over doctors, such progress will assure the everyday emerging of new wearables.

关键词： Systematics Sensitivity Wearable computers Medical services Electrocardiography Signal processing Sensitivity and specificity

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Edge-Based Infrared-Ultrasonic Anti-Collision Radar System for Robotic Navigation: *Applications of Cost-effective Bisensory System for Obstacle Detection, Tracking, and Avoidance

Edge-Based Infrared-Ultrasonic Anti-Collision Radar System f...

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IEEE conference on technologies for Homeland Security

作者： Kosisochukwu Pal Nnoli Mbadiwe Samuel Benyeogor Jones Ifeanyi Bolu Oladayo Olufemi Olakanmi Dept. of Computer Science and Electrical Engineering Jacobs University Bremen Germany Dept. of Physics Westfälische Wilhelms-Universität Münster Münster Germany Junior Information Technology Analyst Program NPower Canada Toronto Canada Dept. of Electrical and Electronics Engineering University of Ibadan Ibadan Nigeria

ISBN: (纸本)9781665494052

Significant progress has been made in the development of an edge computing system for the fusion, representation, and visualization of dual-sensor data for obstacle avoidance control of mobile robots. This involves the use of an error-filtering covariance and averaging algorithm to logically fuse distance measurements from a pair of infrared and ultrasonic sensors, which was instrumented into a robot and used to generate radar visuals to track the proximity of ambient obstacles within 180 degrees spanning ahead of the robot. Hands-on experiments were performed to evaluate the performance and applicability of the system in real-time. The results show that the developed system is viable and robust. In line with the emerging field of edge computing, this work is an efficient, portable, and cost-effective approach to developing mobile robotic systems.

关键词： Visualization Navigation Fuses Sensor fusion Robot sensing systems Radar tracking Acoustics

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