Journal of Recent Innovations in Computer Science and Technology
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Cyber Attack Detection in an Internet of Things Employing Random Forest
Get PDFThe Internet of Things is a vast system of interconnected devices. These gadgets are becoming increasingly commonplace in vital applications. As a result, cybercriminals are directing more of their attention toward the IoT. To protect the IoT from intrusion, we employ Random Forest, a popular machine-learning algorithm for classification tasks, in this work. To implement the proposed method, labeled data depicting both normal IoT device operation and malicious attacks must be collected. Our approach is 95% accurate. Because the advantages of using random forests can be used with smaller datasets and normal computational resources, we believe our method is a good one for detecting and avoiding IoT attacks. This paper introduces a method for detecting cyber-attacks in IoT environments. It uses the Random Forest (RF) algorithm, which is well-known for its accuracy and resilience in classification tasks. To better protect the Internet of Things (IoT) from ever-changing cyber threats, this method offers a dependable and scalable solution
Review of Techniques and Algorithms of Load Balancing in Cloud Computing
Get PDF Cloud computing has transformed the IT industry by enabling convenient access to data, programs, and files over the Internet. A variety of load balancing algorithms, including Round Robin, ESCE, Min-Min, Max-Min, and Throttled, are covered in the discussion along with their effects on throughput, fault tolerance, scalability, and overhead. The literature review stresses the dynamic nature of the cloud computing landscape by highlighting important contributions from scholars. Additionally, the study identifies issues in cloud services, such as automated service provisioning, virtual machine migration, energy management, stored data management, and the growth of small data centers. Even though cloud computing has become widely used, these difficulties highlight the continued need for innovation in the industry
Describing the Research Initiative: Unmanned Aircraft Education in Technology
Get PDFThe Structure of the drone, which includes the frame, propeller, engine, power system, electronic control, and communication systemis covered as the first aspect of this article about drones and their applications. One device is called an aircraft. In addition to this other name for a UAV (unmanned aerial vehicle), it is necessary to mention that any drone can be referred to as “unmanned” if it is capable of flying without the presence of a pilot. It can be estimated that shortly, because they are so much loved by the masses and due to their low-cost nature and ease at which one can find them, their use will soar up greatly. The most important danger associated with drone use is when it falls from a great height. This may be caused by depletion in battery bad weather (such as rain or cold) or striking against something (for example trees, houses, or electricity lines)
A Review of Web Usage Mining Methodology and its Practical Implementation
Get PDFData mining techniques are employed in online usage mining to evaluate user behavior on web pages and uncover usage patterns. There has been a dramatic uptick in interest in web usage mining from academics and industry professionals alike. The objective is to better comprehend how people use websites and cater to the requirements of web-based applications. Extensive research has already been conducted in web usage mining, a substantial and quickly developing subfield of web mining. To put internet usage mining into practice, a clearly defined technique is now required. This article presents a methodology derived from suggestions from literature initiatives. This review aims to help readers gain a firmer grasp of the technical state of Web Usage Mining Methodology and future direction. Researchers and practitioners can use this review to guide better decision-making by connecting theoretical knowledge with actual implementation. Also included a current overview of the literature. A quick review of web usage mining is provided
Load Balancing in Wireless Mobile Ad Hoc Networks
No full textAd hoc networks are made up of groups of similar nodes, such as computers or embedded devices. Each node works on its own and talks to the others through a wireless channel. Networks like these are made up of groups of nodes that are either next to each other or connected by another wireless node. Nodes are grouped together along their wireless links to make clusters. Nodes that can talk to other nodes in their transmission range are called cluster heads. This can use cluster heads to send packets to the right nodes in your cluster. In an Ad Hoc network, the idea behind it is that nodes don\u27t always move in the same way. Cluster Heads are picked by different algorithms in different ways. Some of these rules make it clear that some nodes are more important than others. Because of the extra work and faster energy loss that could happen because of more contacts, these nodes may be taken out of the network. Load-balancing across Cluster Heads is necessary to make sure that every node has a fair chance to be a Cluster Head. We Proposed that a number of changes should be made to current algorithms in order to fix the uneven spread of nodes among Cluster Heads and make nodes in a network that uses the fuzzy algorithm last longer.Load balancing in Wireless Mobile Ad Hoc Networks (MANETs) ensures equitable distribution of network traffic among nodes and resources. Due to the ongoing mobility and dynamic nature of nodes in MANETs, this aspect holds significant importance