Volume 14, Issue 2, April 2023

IoT Devices Operating Systems Unveiled: An Analysis and Comparison of Operating System for Internet of Things

Maleeha Kanwal, Maryam Wajeeha, Nageen Khan

Department of Computer Science, University of Engineering and Technology, Lahore, Pakistan

Abstract- The Internet of Things (IoT) is described by heterogeneous devices. For research objectives, the Internet of Things (IoT) presents many difficulties. IoT devices operating system are beneficial for this purpose. The low-end IoT devices are not reliable for outdated operating systems. A lot of effort is required to design operating systems for concerned devices. This paper compares operating systems for low-end IoT devices and examines essential characteristics in the majority of current IoT operating systems based on different resource management attributes. The comparison will focus on operating systems that are best for low-end devices on behalf of Architecture, Programming model, Scalability, Network performance, Energy Consumption and Scheduling. Operating systems that we will discuss in this paper are Contiki, TinyOS, LiteOS and freeRTOS, Zephyr, Tizen, UbuntuCore, OpenWSN etc. This paper can be beneficial for researchers interested in this field. It can provide an overview of the available IoT operating systems, their features, advantages, and limitations, as well as this paper can also help researchers identify gaps in the existing literature.

Keywords- Low Ended Devices, Operating System, Tizen IoT, Zephyr and Comparison

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On Farm Evaluation of Locally Available Animal Feed Choppers

Abdo Hussien, Gizachew Tefera, Birtukan Mokonen

Oromia Agricultural Research Institute, Bako Agricultural Engineering Research Center, P.O.Box 07, West Shoa, Bako

Abstract- The research was conducted at Bako Agricultural Engineering Research Center to evaluate the machine performance in terms of cutting efficiency, chopping efficiency throughput capacity and fuel consumption at different speeds on two Animal feed choppers. The primary goal of this study was aimed for on farm evaluation of locally available animal feed choppers of Asella AERC model and selam model chopper for crop locally adopted forage varieties in Bako with treatments of the engine seed, feed rate and crops using split plot design with three replications. Asela model animal chopper have mean cutting efficiency (94.88%), chopping efficiency (94%), throughout capacity (389.3 kg/hr)and mean fuel consumption 121ml on elephant grass and have cutting efficiency (96.25%), chopping efficiency (96.9%), throughout put capacity (1063.3 kg/hr) and mean fuel consumption 120ml/kg on Maize Stalk. Selam model animal chopper have mean cutting efficiency (97.47%), chopping efficiency (97.39%), throughout capacity (700.8kg/hr) and mean fuel consumption 31.67ml/kg on elephant grass and have mean cutting efficiency (94.39%), chopping efficiency (97.21%), throughout put capacity (645.45 kg/hr) and mean fuel consumption 40.9ml/kg on Maize Stalk was recorded. From the result obtained both animal feed chopper have best cutting efficiency, chopping efficiency and throughout put capacity, though according to their capacity of the engine they have the customers or farmers can these animal feed choppers at speed of 800rpm and 5kg/min feeding rate,but using greater than the above speed may affect the machine specially Asela model chopper. So, It recommend, these machine must be go to extension and reach to farmers.

Keywords- On Farm Evaluation, Animal Feed Chopper, Elephant Grass and Maize Stalk

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The Positive Impact of Intelligent Agent in IoT data Security and Privacy

Hafsa Tariq, Junaid Arshad

Computer Science Department, University of Engineering and Technology, Lahore, Pakistan

Abstract- The paper provides an overview of an article discussing the importance of data security in IoT and how it is critical for protecting all other aspects of IoT, including privacy. The paper highlights the need for data security and privacy preserving methods in IoT due to the increasing number of IoT devices and potential cyber threats. It describes various techniques, including machine learning algorithms, blockchain, encryption, and access control, to secure IoT data and reduce vulnerabilities and data breaches. The paper also discusses the challenges related to data security in IoT concerning intelligent agents, such as authentication and authorization, encryption, data privacy, device security, and interoperability. The paper proposes a combination of technological solutions, best practices, and compliance with privacy regulations to address these challenges. It also discusses advanced technologies and approaches, such as blockchain technology and machine learning-based anomaly detection, to ensure the integrity and security of IoT data. Finally, the paper emphasizes the positive impacts of data security and privacy in IoT, including protection of sensitive data, building trust, compliance with regulations, prevention of cyberattacks, and improved operational efficiency.

Keywords- Intelligent Agent, Data Security, Impact, Encryption, Block chain, Privacy Protection, Unauthorized User and Authentication

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BOTNET Threat Intelligence in IoT-Edge Devices

Ahsan Ali, Nabeel Aslam, M. J. Arshad

Information Technology Centre

Abstract- Recently, deep learning has gotten progressively popular in the domain of security. However, Traditional machine learning models are not capable to discover zero-day botnet attacks with extraordinary privacy. For this purpose, researchers have utilized deep learning based computational framework for Botnet which can detect zero-day attacks, achieve data privacy and improve training time using machine learning techniques for the IoT-edge devices. However, it combines and integrates various models and contexts. As a result, the objective of this research was to incorporate the deep learning model which controls different operation of IoT devices and reduce the training time. In deep learning, there are numerous components that aspect the false positive rate of every detected attack type. These elements are F1 score, false-positive rate, and training time; reduce the time of detection, and Accuracy. Bashlite and Mirai are two examples of zero-day botnet attacks that pose a threat to IoT edge devices. The majority of cyber-attacks are executed by malware infected devices that are remotely controlled by attackers. This malware is often referred to as a bot or botnet, and it enables attackers to control the device and perform malicious actions, such as spamming, stealing sensitive information, and launching DDoS attacks. The model was formulated in Python libraries and subsequently tested on real life data to assess whether the integrated model performs better than its counterparts. The outcomes show that the proposed model performs in a way that is better than existing models, along the 99% accuracy and 0.1% false positive rate percent improving and reliability of the deep learning based federated learning.

Keywords- Botnet Detection, Cyber Security, Deep Learning (DL), Deep Neural Network (DNN), Botnet Attacks Intelligence (BAI), Internet of Things (IoT).

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A Review on the Performance Evaluation of Mobile RPL-Based IoT Networks under Version Number Attack

Saqib Yaseen, Muhammad Jawad, Ahmad Raza, Junaid Arshad

Department of Computer Science, University of Engineering and Technology, Lahore, Pakistan

Abstract- The article “Performance evaluation of mobile RPL-based IOT networks under version number attack” evaluates the effectiveness of version number assault on mobile RPL-based IOT networks. RPL is a popular routing protocol used in IOT networks for its adaptability to different network topologies and low power consumption. However, it is susceptible to security threats like the attack on the version number. In this attack, malicious nodes can inject false routing information into the network by manipulating the version number field in RPL messages, causing routing loops and network congestion. The study evaluates the impact of the version number attack on the performance of mobile RPL-based IOT networks by simulating different scenarios using the Cooja simulator. According to the findings, the version number attack dramatically reduces packet delivery rate, end-to-end delay, and network longevity. Moreover, the impact of the attack is more severe in mobile networks due to the frequent topology changes and node mobility. The article suggests several countermeasures to mitigate the version number attack, including secure version number assignment, neighbor verification, and message authentication. These countermeasures can enhance the security of RPL-based IOT networks and improve their performance under security attacks.

Keywords- Mobile RPL, IoT, IoT Networks, Version Number Attack, Performance Evaluation, Denial-of-Service (DOS) Attack

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Evaluation of RPL-based IoT Protocol Performance under Various Mobility Scenarios

Rimsha Fayyaz, Nimra Khan, Muhammad Haris

Department of Computer Science, University of Engineering and Technology Lahore, Pakistan

Abstract- The growth of IoT applications and connected smart devices has made routing a challenging concept. To address this, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) was standardized for IoT networks. However, RPL was designed for stationary IoT applications and has difficulty adapting to the dynamic fluctuations of mobile applications. While several studies have attempted to adjust RPL for mobile IoT applications, a standardized version of this protocol is still in high demand. This research presents a comprehensive study on the impact of various mobility models on the performance of a mobility aware RPL to facilitate this process. A performance evaluation is conducted using IoT simulation tools to compare the performance of the network and its IoT devices under different mobility models from several perspectives. The results of this research will aid researchers in both academia and industry in designing and implementing application-specific and standard versions of RPL suitable for mobile IoT applications.

Keywords- Internet of Things, Mobility Models, Simulation, RPL, Routing Protocols, Performance Evaluation and Energy Consumption.

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