Security of GPS/INS based On-road Location Tracking Systems

Location information is critical to a wide-variety of navigation and tracking applications. Today, GPS is the de-facto outdoor localization system but has been shown to be vulnerable to signal spoofing attacks. Inertial Navigation Systems (INS) are emerging as a popular complementary system, especially in road transportation systems as they enable improved navigation and tracking as well as offer resilience to wireless signals spoofing, and jamming attacks. In this paper, we evaluate the security guarantees of INS-aided GPS tracking and navigation for road transportation systems. We consider an adversary required to travel from a source location to a destination, and monitored by a INS-aided GPS system. The goal of the adversary is to travel to alternate locations without being detected. We developed and evaluated algorithms that achieve such goal, providing the adversary significant latitude. Our algorithms build a graph model for a given road network and enable us to derive potential destinations an attacker can reach without raising alarms even with the INS-aided GPS tracking and navigation system. The algorithms render the gyroscope and accelerometer sensors useless as they generate road trajectories indistinguishable from plausible paths (both in terms of turn angles and roads curvature). We also designed, built, and demonstrated that the magnetometer can be actively spoofed using a combination of carefully controlled coils. We implemented and evaluated the impact of the attack using both real-world and simulated driving traces in more than 10 cities located around the world. Our evaluations show that it is possible for an attacker to reach destinations that are as far as 30 km away from the true destination without being detected. We also show that it is possible for the adversary to reach almost 60-80% of possible points within the target region in some cities

Satellite Navigation for the Age of Autonomy

Global Navigation Satellite Systems (GNSS) brought navigation to the masses. Coupled with smartphones, the blue dot in the palm of our hands has forever changed the way we interact with the world. Looking forward, cyber-physical systems such as self-driving cars and aerial mobility are pushing the limits of what localization technologies including GNSS can provide. This autonomous revolution requires a solution that supports safety-critical operation, centimeter positioning, and cyber-security for millions of users. To meet these demands, we propose a navigation service from Low Earth Orbiting (LEO) satellites which deliver precision in-part through faster motion, higher power signals for added robustness to interference, constellation autonomous integrity monitoring for integrity, and encryption / authentication for resistance to spoofing attacks. This paradigm is enabled by the 'New Space' movement, where highly capable satellites and components are now built on assembly lines and launch costs have decreased by more than tenfold. Such a ubiquitous positioning service enables a consistent and secure standard where trustworthy information can be validated and shared, extending the electronic horizon from sensor line of sight to an entire city. This enables the situational awareness needed for true safe operation to support autonomy at scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS

D-SLATS: Distributed Simultaneous Localization and Time Synchronization

Through the last decade, we have witnessed a surge of Internet of Things (IoT) devices, and with that a greater need to choreograph their actions across both time and space. Although these two problems, namely time synchronization and localization, share many aspects in common, they are traditionally treated separately or combined on centralized approaches that results in an ineffcient use of resources, or in solutions that are not scalable in terms of the number of IoT devices. Therefore, we propose D-SLATS, a framework comprised of three different and independent algorithms to jointly solve time synchronization and localization problems in a distributed fashion. The First two algorithms are based mainly on the distributed Extended Kalman Filter (EKF) whereas the third one uses optimization techniques. No fusion center is required, and the devices only communicate with their neighbors. The proposed methods are evaluated on custom Ultra-Wideband communication Testbed and a quadrotor, representing a network of both static and mobile nodes. Our algorithms achieve up to three microseconds time synchronization accuracy and 30 cm localization error

Level-Headedness in Wireless Sensor Networks

Well-groomed surroundings be a sign of the next evolutionary step in construction, utilities, industrial, residence, shipboard, and haulage system automation. The well-groomed atmosphere needs information about its environment as well as about its internal workings. Sensor networks are the input to assembly the information needed by well-groomed surroundings, whether in buildings, utilities, industrial, home, shipboard, transportation systems, automation, or elsewhere. Localization is one of the basic challenges and it plays vital role. In this paper we are discussing various Application Requirements, probable Approaches, Position unearthing Approaches, Localization Techniques and QOS

Improve Performance Wireless Sensor Network Localization using RSSI and AEMM

Improve wireless sensor network localisation performance using RSSI and an advanced error minimisation method (AEMM). WSNs remain domain-specific and are typically deployed to support a single application. However, as WSN nodes become more powerful, it becomes increasingly important to investigate how multiple applications can share the same WSN infrastructure. Virtualisation is a technology that may allow for this sharing. The issues surrounding wireless sensor node localisation estimation are still being researched. There are a large number of Wireless Sensor Networks (WSNs) with limited computing, sensing, and energy capabilities. Localisation is one of the most important topics in wireless sensor networks (WSNs) because location information is typically useful for many applications. The locations of anchor nodes and the distances between neighbouring nodes are the primary data in a localisation process. The complexity and diversity of current and future wireless detector network operations drive this. Several single schemes have been proposed and studied for position estimation, each with advantages and limitations. Nonetheless, current methods for evaluating the performance of wireless detector networks are heavily focused on a single private or objective evaluation. Accurate position information in a wireless detector network is critical for colourful arising operations (WSN). It is critical to reducing the goods of noisy distance measures to improve localisation accuracy. Existing works (RSSI) are detailed and critically evaluated, with a higher error rate using a set of scenario requirements. Our proposed method (AEMM) is critical for detecting and dealing with outliers in wireless sensor networks to achieve a low localisation error rate. The proposed method (AEMM) for localisation and positioning nodes in wireless sensor networks supported by IOT and discovering the appropriate position of several nodes addresses all of the issues in WSN