Comparative Analysis of Privacy Preserving Location Based Services Mechanisms

Recent trends in computing have enabled the provision of location-based services, offering practicality and convenience to users. Moreover, this has also given rise to new challenges and vulnerabilities that can potentially compromise user privacy. As these services are predominantly used on handheld devices, the risk of security breaches is higher. This research collates existing studies that have conducted quantitative and qualitative comparisons and analyses on how to address related challenges, with a particular focus on protecting user privacy in location-based services

An Efficient approach for Firearms Detection using Machine Learning

Each year, there is a significant number of people impacted by gun-related violence globally. To address this issue, we have created a computer-based system that can automatically identify firearms, specifically pistol. Recent advancements in machine learning has shown success in the fields of recognition and object detection. Our system utilizes the You Only Look Once (YOLO V3) object detection model, which was trained on a personalized dataset. Our training results indicate that YOLO V3 outperforms both traditional convolutional neural network (CNN) models and YOLO V2. Notably, our approach did not require high computation resources or intensive GPUs to train our model. By incorporating this YOLO V3 model into our security system, we hope to rescue lives and decrease the occurrence of manslaughter or mass killings. Moreover, detecting weapons or other dangerous materials and preventing harm or risk to human life could be accomplished by integrating this system into sophisticated surveillance and security robots

Questgator: A Platform for Content Aggregation and Text Classification

The Web has witnessed a surge in content over recent years. Content is revolutionizing the way people conduct business, communicate, and make informed decisions. However, the vast amount of data used for communication today is oftenunstructured and challenging to comprehend. Content aggregators provide a solution to this problem by collecting data from various sources and organizing it into a structured format in one place. This research proposed the content aggregator "Questgator" that extracts content for example news, scholarships, jobs, books, video content, and research papers. In this paper Naive Bayes theorem is used for text classification. Moreover, paper also provides comparison with other platforms to show the efficiency of proposed content aggregator

A Study Towards Exploring Access Control Mechanisms and its Limitations in Cloud Computing

Cloud computing technologies are growing fast day by day. Cloud technologies are attracting enterprises to themselves by providing great and enhanced services. There is no doubt that cloud technologies reduced the burden of the digital world by giving manageable computing services, huge room for unlimited data storage, on-demand software services, great platforms, and access control management systems. To use cloud-based manageable services users and organizations must have access to the cloud. Before using any access control mechanism, the organizations should know about the limitations of the access control mechanism. At present, many access control mechanisms are available in cloud computing. In this paper, our main goal is to identify the access control mechanisms in cloud computing and their limitations in cloud computing