The Role of Satellites and Smart Devices: Data Surprises and Security, Privacy, and Regulatory Challenges

Strava, a popular social media platform and mobile app like Facebook but specifically designed for athletes, posts a “heatmap” with consensually-obtained details about users’ workouts and geolocation. Strava’s heatmap depicts aggregated data of user location and movement by synthesizing GPS satellite data points and movement data from users’ smart devices together with satellite imagery. In January of 2018, a 20-year-old student tweeted that Strava’s heatmap revealed U.S. forward operating bases. The tweet revealed a significant national security issue and flagged substantial privacy and civil liberty concerns. Smart devices, software applications, and social media platforms aggregate consumer data from multiple data collection sources, including device-embedded sensors, cameras, software, and GPS chips, as well as from consumer activities like social media posts, pictures, texts, email, and contacts. These devices and apps utilize satellite data, including GPS, as a fundamental component of their data collection arsenal. We call this little understood, across-device, across-platform, and multi-sourced data aggregation the satellite-smart device information nexus. Given the nature of the technology and data aggregation, no one escapes the satellite and smart device information nexus. We explain the technology behind both satellites and smart devices, and we examine how the satellite-smart device information nexus works. We also address how private industry’s aggregation of data through this nexus poses a threat to individual privacy, civil liberties, and national security. In so doing, we work to fill a marked gap in the privacy and cyber-related legal literature when it comes to analyzing the technology, surveillance capabilities, law, and regulation behind government and commercial satellites together with private industry’s aggregation, use, and dissemination of geolocation and other data from the satellite-smart device information nexus. This lack of awareness about the satellite-smart device information nexus has adverse consequences on individual privacy, civil liberties, and the security of nation states; it impedes informed legislation; and it leaves courts in the dark. A contributing factor to the lack of awareness is that commercial remote sensing and government satellites are regulated by a byzantine scheme of international laws, treaties, organizations, and domestic nation states’ laws that combine to control access to satellite data, sharing of satellite data, licensing, ownership, positioning in space, technical requirements, technical restrictions, and liability for harm caused by satellites. Although the satellite-smart device information nexus involves staggering quantities of personal information, we examine how the nexus falls outside the U.S. electronic surveillance and data legislative scheme and why it is unimpeded by privacy decisions due to a disconnect in U.S. Supreme Court decisions treating aerial surveillance differently than location tracking. We breakdown the complex yet opaque regulatory structure governing commercial remote sensing and government satellites. We examine why the Strava event and others like it are—and will continue to be—the new norm, absent significant legislative and regulatory change. We conclude by providing a suggested roadmap for that legislative and regulatory change

Geographic Information Systems: A Survey

At its core GIS or Geographical Information System, is a mapping tool that allows various types of information to be linked to geolocation. With advances in Big Data technologies, the availability of a large and ever-increasing stream of geolocated data, the new services based on geolocation that are used by massive numbers of people especially on mobile devices, GIS systems are becoming fundamental and increasingly important to large numbers of individuals as well as businesses and industry. The purpose of this paper is to review the current state of the art of GIS technology and provide a summary view of its functionality and the major issues around its use. It is aimed to be readable by a wide readership familiar with computing technologies but not necessarily versed in GIS

Providing Context to the Clues: Recovery and Reliability of Location Data from Android Devices

Mobile device data continues to increase in significance in both civil and criminal investigations. Location data is often of particular interest. To date, research has established that the devices are location aware, incorporate a variety of resources to obtain location information, and cache the information in various ways. However, a review of the existing research suggests varying degrees of reliability of any such recovered location data. In an effort to clarify the issue, this project offers case studies of multiple Android mobile devices utilized in controlled conditions with known settings and applications in documented locations. The study uses data recovered from test devices to corroborate previously identified accuracy trends noted in research involving live-tracked devices, and it further offers detailed analysis strategies for the recovery of location data from devices themselves. A methodology for reviewing device data for possible artifacts that may allow an examiner to evaluate location data reliability is also presented. This paper also addresses emerging trends in device security and cloud storage, which may have significant implications for future mobile device location data recovery and analysis. Discussion of recovered cloud data introduces a distinct and potentially significant resource for investigators, and the paper addresses the cloud resources\u27 advantages and limitations

Cooperatively Extending the Range of Indoor Localisation

̶Whilst access to location based information has been mostly possible in the\ud outdoor arena through the use of GPS, the provision of accurate positioning estimations and\ud broad coverage in the indoor environment has proven somewhat problematic to deliver.\ud Considering more time is spent in the indoor environment, the requirement for a solution is\ud obvious. The topography of an indoor location with its many walls, doors, pillars, ceilings\ud and floors etc. muffling the signals to \from mobile devices and their tracking devices, is one\ud of the many barriers to implementation. Moreover the cha racteristically noisy behaviour of\ud wireless devices such as Bluetooth headsets, cordless phones and microwaves can cause\ud interference as they all operate in the same band as Wi -Fi devices. The limited range of\ud tracking devices such as Wireless Access Point s (AP), and the restrictions surrounding their\ud positioning within a buildings’ infrastructure further exacerbate this issue, these difficulties\ud provide a fertile research area at present.\ud The genesis for this research is the inability of an indoor location based system (LBS) to\ud locate devices beyond the range of the fixed tracking devices. The hypothesis advocates a\ud solution that extends the range of Indoor LBS using Mobile Devices at the extremities of\ud Cells that have a priori knowledge of their location, and utilizing these devices to ascertain\ud the location of devices beyond the range of the fixed tracking device. This results in a\ud cooperative localisation technique where participating devices come together to aid in the\ud determination of location of device s which otherwise would be out of scope

Military Contingencies in Megacities and Sub-Megacities

Urbanization is one of the most important mega-trends of the 21st century. Consequently, the possibility of U.S. military involvement in a megacity or sub-megacity is an eventuality that cannot be ignored. After elucidating the nature of urbanization and developing a typology in terms of smart, fragile, and feral cities, we give consideration to the kinds of contingencies that the U.S. military, especially the Army, needs to think about and prepare for. Understanding the city as a complex system or organism is critical and provides the basis for changes in intelligence, recruitment, training, equipment, operations, and tactics. One of the key takeaways is the need to understand the urban environment and the need to work with (instead of against) the flows and rhythms of a city. Without such an approach, the results of military involvement in such a formidable environment would likely be disastrous; with it, the prospects for success would at least be enhanced.https://press.armywarcollege.edu/monographs/1416/thumbnail.jp

Cooperatively extending the range of indoor localisation

Whilst access to location based information has been mostly possible in the outdoor arena through the use of GPS, the provision of accurate positioning estimations and broad coverage in the indoor environment has proven somewhat problematic to deliver. Considering more time is spent in the indoor environment, the requirement for a solution is obvious. The topography of an indoor location with its many walls, doors, pillars, ceilings and floors etc. muffling the signals to from mobile devices and their tracking devices, is one of the many barriers to implementation. Moreover the characteristically noisy behaviour of wireless devices such as Bluetooth headsets, cordless phones and microwaves can cause interference as they all operate in the same band as Wi-Fi devices. The limited range of tracking devices such as Wireless Access Points (AP), and the restrictions surrounding their positioning within a buildings' infrastructure further exacerbate this issue, these difficulties provide a fertile research area at present. The genesis for this research is the inability of an indoor location based system (LBS) to locate devices beyond the range of the fixed tracking devices. The hypothesis advocates a solution that extends the range of Indoor LBS using Mobile Devices at the extremities of Cells that have a priori knowledge of their location, and utilizing these devices to ascertain the location of devices beyond the range of the fixed tracking device. This results in a cooperative localisation technique where participating devices come together to aid in the determination of location of devices which otherwise would be out of scope

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Citizen science characterization of meanings of toponyms of Kenya: a shared heritage

This paper examines the toponymic heritage used in Kenya’s Authoritative Geographic Information (AGI) toponyms database of 26,600 gazetteer records through documentation and characterization of meanings of place names in topographic mapping. A comparison was carried out between AGI and GeoNames and between AGI and OpenStreetMap (OSM) volunteered records. A total of 15,000 toponymic matchings were found. Out of these, 1567 toponyms were then extracted for further scrutiny using AGI data in the historical records and from respondents on toponyms’ meanings. Experts in toponymy assisted in verifying these data. From the questionnaire responses, 235 names occurred in more than one place while AGI data had 284. The elements used to characterize the toponyms included historical perceptions of heritage evident in toponyms in their localities, ethnographic, toponymical and morphology studies on Kenya's dialects. There was no significant relationship established between the same place name usages among dialects as indicated by a positive weak correlation r (438), = 0.166, p < 0.001 based on the effect of using the related places and the distance between related places. The weak correlation implies that the one name one place principle does not apply due to diverse language boundaries, strong bonds associated with historical toponyms in the form of heritage and significant variations on how names resist changes to preserve their heritage

Using Physical and Social Sensors in Real-Time Data Streaming for Natural Hazard Monitoring and Response

Technological breakthroughs in computing over the last few decades have resulted in important advances in natural hazards analysis. In particular, integration of a wide variety of information sources, including observations from spatially-referenced physical sensors and new social media sources, enables better estimates of real-time hazard. The main goal of this work is to utilize innovative streaming algorithms for improved real-time seismic hazard analysis by integrating different data sources and processing tools into cloud applications. In streaming algorithms, a sequence of items from physical and social sensors can be processed in as little as one pass with no need to store the data locally. Massive data volumes can be analyzed in near-real time with reasonable limits on storage space, an important advantage for natural hazard analysis. Seismic hazard maps are used by policymakers to set earthquake resistant construction standards, by insurance companies to set insurance rates and by civil engineers to estimate stability and damage potential. This research first focuses on improving probabilistic seismic hazard map production. The result is a series of maps for different frequency bands at significantly increased resolution with much lower latency time that includes a range of high-resolution sensitivity tests. Second, a method is developed for real-time earthquake intensity estimation using joint streaming analysis from physical and social sensors. Automatically calculated intensity estimates from physical sensors such as seismometers use empirical relationships between ground motion and intensity, while those from social sensors employ questionaries that evaluate ground shaking levels based on personal observations. Neither is always sufficiently precise and/or timely. Results demonstrate that joint processing can significantly reduce the response time to a damaging earthquake and estimate preliminary intensity levels during the first ten minutes after an event. The combination of social media and network sensor data, in conjunction with innovative computing algorithms, provides a new paradigm for real-time earthquake detection, facilitating rapid and inexpensive risk reduction. In particular, streaming algorithms are an efficient method that addresses three major problems in hazard estimation by improving resolution, decreasing processing latency to near real-time standards and providing more accurate results through the integration of multiple data sets