Online informal communication is developing quickly with a full scope of administration that is accessible for gigantic number of clients to impart insights and interests, express feelings, and stay in contact with companions. The people group is getting to expand associated with one another. Numerous online locales give various approaches to get to the webpage utilizing gadgets, for example, PCs and advanced cells. Consequently, clients can utilize their locales rapidly and effectively, whenever, and any place. In this paper, we zeroed in on the way toward ordering on the web informal organization customer of different security that emphasis on every customer of long reach casual correspondence objections and studies various methods to dismember customer direct in online casual networks. Besides, we autonomously focus on different threats that grow on account of the sharing of sight and sound substance inside an individual-to-individual correspondence site.

In the rapid world of technology, the IT Industry is growing at a rapid speed with Cloud Image Security. In the developing trends, cloud orchestration is becoming impressive and uncertain of dealing a large amount of information. In the last two decades there has been extensive development in image encryption. Chaos based image encryption techniques form framework for a faster algorithm than traditional techniques. Chaos based techniques are highly efficient in case of multimedia data. The proposed algorithm uses the modified logistic map for the generation of chaotic sequence, encrypts the image in single scan, so runs faster and makes the proper use of confusion and diffusion. It dynamically updates the key during execution. This algorithm is secure against the brute force attack and differential attack.

In GPS system enabled hand-held communication devices which works as a beacon that transmits our location. Also, the location-based services that emerged in recent years make use of location data. The location data provided to these location-based service providers have enough sensitive information to bother about. The location privacy became an area of concern in recent years. Developed and developing countries are now in process to make laws against the use of location information without the consent of the user or without legal warrant. Most of the research strategies proposed in recent years have one thing in common that we provide a region instead of exact coordinates of the location of the user. These attacks are called location dependent attacks or velocity linkage attacks in literature. We have in our effort proposed a solution to the problem of location privacy protection taking care of the location dependent attacks. We also keep in mind the fact that user is more concerned about his locations at certain places. We tested the proposed solution against requests issued by 5000 and 15000 users moving in a field of 10000x10000 units' area.

The amalgamation of wearable sensor technologies and artificial intelligence (AI) presents a transformative paradigm for optimising athletic performance in real time. This paper explores the integration of cutting-edge sensors - including bioimpedance sensors, accelerometers, and gyroscopes - with advanced AI algorithms such as machine learning and decision support systems. By capturing diverse physiological, biomechanical, and environmental data, the proposed framework aims to offer personalized, actionable insights for athletes. This research synthesizes the current landscape of wearable sensor technology in sports and highlights the evolving role of AI in interpreting data for enhancing athletic performance. It delineates an innovative framework designed for real-time analysis, personalized feedback, and training optimization. The seamless interaction between sensors and AI models empowers athletes and coaches to make informed decisions, optimizing training regimens and minimizing injury risks. The paper discusses the practical implications, challenges, and ethical considerations associated with this integration, emphasizing its potential benefits in diverse sports disciplines. Results from real-world trials underscore the efficacy of the proposed framework in providing dynamic guidance to athletes, thereby augmenting their performance through tailored interventions.

In this paper we propagate the Sybil attack in WSN (Wireless sensor network), by the researchers many attacks have been recognized in WSN till now and there are many attacks which can attack over through internet, Internet of thing means all devices is interconnected to each other M2M over internet and can be attacked by any of the attacker on any devices. Sybil attack is the detrimental attack against sensor network where several counterfeit identities and legitimate identities are used to get prohibited pass in a network. This is major attack which results an information loss and misinterpretation in the network, and it also minimizes the routing disturbance, trustworthiness and dropping sensitivity packets into a network. In this instance node can trust the imaginary node and sharing of information starts, owed to this security of node is get affected and information is lost. In this paper, a survey of CONTIKI OS-2.7, stimulation tool COOJA and the Sybil attack and proposed the defense mechanisms and CAM (Compare and Match) approach to verify the Sybil attack position and prevent it. This Sybil attack can be stimulated on the stimulation tool COOJA which helps to identify the attacker position node, whereas these attacks outcome in uni-casting as well as multicasting and in this paper specifically given the secure security for Wireless sensor network.

Varieties of serious mental and physical disorders are the cause of variations in gait. Gait analysis is extensively used in a variety of clinical applications to diagnose and monitor specific disorders. Sports, physical rehabilitation, clinical evaluation, surveillance, identification, modeling, and other industries all benefit from gait analysis. The study provides extensive information on characteristics, types, methodologies, limitations, applications, datasets, and tools used in gait analysis employing different sensor-based and vision-based approaches. A thorough study on gait analysis indicates a significant research gap in various elements of vision-based gait analysis. The field is either undiscovered or has received minimal attention in various scenarios, thus requiring emphasis on comprehensive analysis and exploration. This study will help analyze human walking patterns concerning clinical applications, rehabilitation, injury assessment, and fall risk assessment. It can provide important insights into various aspects of a person’s gait.