Analysis Of The Prisense Protocol

As technology is advancing in this digital age so is the need to protected people’s privacy and to keep their personal information confidential. As Michael McFarland, of the Markkula Center for Applied Ethics noted “Reverence for the human person as an end in itself and as an autonomous being requires respect for personal privacy. To lose control of one 's personal information is in some measure to lose control of one 's life and one 's dignity. Therefore, even if privacy is not in itself a fundamental right, it is necessary to protect other fundamental rights” (Michael McFarland, 2012). It is in the light of this that the ethical dilemma of whether smartphone manufacturer has the right to track their customer location is the focus of this paper. People’s personal and sensitive information such as medical records, court records, financial records and geolocation information should be protected and held confidential. Today manufacturer of smartphone embedded beacon in their device which transmits their customer location. The location data collected are notably used as part of providing services or for contextual advertising (Electronic Frontier Foundation, 2016).

Although technology has provided tools to enhance our capabilities in things such as finding a missing person, solving murder cases based on technological assets etc.., this technology also leaves us vulnerable in many ways to slowly losing our privacy (Burten, C., 2012).

maximization of network lifetime [8]. This protocol is also divided into two phase: 1. Clustering and 2. Routing of aggregated data. In clustering phase, a fixed topological arrangement is done by sensor nodes. In the data aggregation phase, heuristic is proposed. The advantage is that it provides energy efficiency and network lifetime also be increased.

In this section, we present the details of proposed protocol. Our protocol implements the idea of probabilities for cluster heads selection based on initial energy and residual energy of sensor nodes as well as the average energy of the sensor network.

Anonymous authentication at some point was good but it declined in the recent years. The last known published research on anonymous authentication for biometrics is dated back in 2008. Anonymous authentication can be considered as a good approach on the cloud. With a new mind set and tools available, new innovative framework can be created.

In a modern life, from the minute a person is born, a digital record is created. From that point on, the individual’s behavior is regularly tracked and information are collected about the typical parts of the person life such as when government collect data about our health, education and income, we hope that the data are used in good way. However, we always have concerned about our privacy. Liina Kamm did her research on the Information Security Research Institute of Cybernetica AS. Kamm worked with development team of the secure data analysis system Sharemind to develop she developed a convenient privacy-preserving data analysis tool Rmind to help on the future privacy

With the rapid growth of mobile computing, mobile device become a necessary tool in our daily life. Without mobile device our life quality, efficiency will totally decrease. Users just need to connect to network and gather information they want in a few second. Although mobile devices bring us convenient, mobile devices contain large amount of personal data, including emails, photos, contact data, financial, and medical information, privacy issue [1] occur due to users unknowingly expose their privacy through mobile application, camera, network etc. and their use poses a serious threat to both personal and corporate security. It greatly extending the reach of technology and raising concerns that prevailing traditions of privacy may be challenged.

Although we do not describe about the privacy mechanisms, there are various privacy mechanisms proposed for Location Based Services [9].

Abstract: Wireless sensor network (WSN) is built of hosts called sensors which can sense a phenomenon such as motion, temperature, and humidity. Sensors represent what they sense in data format. Providing an efficient end-to-end privacy solution would be a challenging task due to the open nature of the WSN. The key schemes needed for end-to-end location privacy are anonymity, observability, capture likelihood and safety period. On top of that, having temporal privacy is crucial to attain. We extend this work to provide a solution against global adversaries. We present a network model that is protected against passive/active and local/multi-local/global attacks. This work provides a solution for temporal privacy to attain end-to-end anonymity and location privacy.

The Payment Card industry Data Security Standard applies to companies that use, store and transmit protected financial information. Companies bear responsibility for compliance, but many of the company 's payment processors offer compliance tools for businesses they serve. It 's essential that companies implement PCI standards. Developing a plan for physical and digital security protocols is essential if companies want to avoid fines, penalties, customer lawsuits and even cancellations of their payment processing privileges due to security breaches caused by noncompliance.

The apps used today often collect data more than needed for its functionality (Li et al. 2016, p.1340). Often these apps track the user location, access the photos, address books, access calendar and track IMEI/UDID without users’ notice (Li et al. 2016, 1340). A report by appthority shows that 24 percent of the top iOS paid apps track users’ location. Whereas, 82 percent of the top Android free apps and 49 percent of the top Android paid apps track users’ location (Li et al. 2016, 1340). Enck et al. (2011, p.28) studied 1,100 Android apps, and found that half of these apps exposed location data to third-party advertisement servers without requiring implicit or explicit user consent.

Large amounts of data streams are generated in resource-constrained environments. Sensor networks represent a typical example. These devices

Global Positioning Systems GPS have undergone rapid developments in recent years. The GPS technology allows the locations of users to be determined accurately and there are many advantages to allow GPS tracking systems on cell phones such as finding friends, family members, maps and places to visit. Furthermore, cell phone GPS have proven useful in saving lives during emergencies. In this matter, it is important to mention that the United States of America Federal Communications Commission have made a E-911 application and E112 in Europe which requires cell phone companies to provide an accurate location of a cell phone user who calls for emergency help. However, the location of the cell phone user must be released with consent of the cell phone owner. As well through using location technologies, a service provider can track whereabouts of a user and discover their personal habits. What we are typically aware off is that these pieces of sensitive information can be sold to third parties without their consent or knowledge. It is often feared that government agencies can monitor the behaviour of individuals, or trace the places they have visited. Therefore, protecting location privacy from being invaded is thus of utmost importance.

“Today, many areas of our lives are digitized. The amount of data we generate has increased enormously and our every step can be tracked by the Internet, our smartphone or other mobile devices. The growing number of ways in which data can be stored and analyzed is threatening our privacy. However, with the current social and political climates we can expect little support on holding manufacturers and developers to their defined privacy regulations. As a society we must demand from these that our right to privacy is upheld and that consent for sharing our information is being sought.”

This system presents the first complete design to apply compressive sampling theory to sensor data gathering for large scale wireless sensor networks. The successful scheme developed in this research is expected to offer fresh frame of mind for research in both compressive sampling applications and large-scale wireless sensor networks. We consider the scenario in which a large number of sensor nodes are densely deployed and sensor readings are spatially correlated. The proposed compressive data gathering is able to reduce global scale communication cost without introducing intensive computation or complicated transmission control. The load balancing characteristic is capable of extending the lifetime of the entire sensor network as well as individual sensors. Furthermore, the proposed scheme can cope with abnormal sensor readings gracefully. We also carry out the analysis of the network capacity of the proposed compressive data gathering and validate the analysis through ns-2 simulations. More importantly, this novel compressive data gathering has been tested on