Towards Secure, Power-Efficient and Location-Aware Mobile Computing

In the post-PC era, mobile devices will replace desktops and become the main personal computer for many people. People rely on mobile devices such as smartphones and tablets for everything in their daily lives. A common requirement for mobile computing is wireless communication. It allows mobile devices to fetch remote resources easily. Unfortunately, the increasing demand of the mobility brings many new wireless management challenges such as security, energy-saving and location-awareness. These challenges have already impeded the advancement of mobile systems. In this dissertation we attempt to discover the guidelines of how to mitigate these problems through three general communication patterns in 802.11 wireless networks. We propose a cross-section of a few interesting and important enhancements to manage wireless connectivity. These enhancements provide useful primitives for the design of next-generation mobile systems in the future.;Specifically, we improve the association mechanism for wireless clients to defend against rogue wireless Access Points (APs) in Wireless LANs (WLANs) and vehicular networks. Real-world prototype systems confirm that our scheme can achieve high accuracy to detect even sophisticated rogue APs under various network conditions. We also develop a power-efficient system to reduce the energy consumption for mobile devices working as software-defined APs. Experimental results show that our system allows the Wi-Fi interface to sleep for up to 88% of the total time in several different applications and reduce the system energy by up to 33%. We achieve this while retaining comparable user experiences. Finally, we design a fine-grained scalable group localization algorithm to enable location-aware wireless communication. Our prototype implemented on commercial smartphones proves that our algorithm can quickly locate a group of mobile devices with centimeter-level accuracy

Mitigating the Effects of Cyber Attacks and Human Control in an Autonomous Intersection

Widespread use of fully autonomous vehicles is near. However, the desire for a human to maintain control, even if limited, of a vehicle will likely never fully subside. Protocols to safely and efficiently manage reservation-based intersections with a mixture of fully autonomous, semi-autonomous, and non-autonomous vehicles exist such as AIM, SemiAIM, and H-AIM. Missing from these protocols is persistent human control of semi-autonomous vehicles in approaching and navigating autonomous intersections without the use of traditional signals. This thesis offers a proof-of-concept of a reservation-based protocol with necessary extensions required for human control in semi-autonomous vehicles. Desired is a protocol that maintains the benefits in efficiency of a fully autonomous environment, such as AIM, while allowing persistent human control of a vehicle. Proposed are possible feedback mechanisms for human response such as displays detailing intersection arrival time, goal velocity, lane keeping assistance, and other warnings. Also developed is a synthetic environment able to demonstrate cyber attacks, their mitigations, and aid in designing a protocol introducing persistent human control. The AFTR Burner three-dimensional virtual world offers the ability to model this physics based environment in a highly predictable and realistic manner. The reservation-based protocol used in the synthetic environment is first verified and validated against both an established reservation-based protocol, such as AIM, and also use case scenarios to determine if the expected behavior is exhibited. Preliminary observations suggest that persistent human control is a possibility among reservation-based autonomous intersections, but further research must be done to determine its viability

Synthetic Generation of Realistic Signal Strength Data to Enable 5G Rogue Base Station Investigation in Vehicular Platooning

Rogue Base Stations (RBS), also known as 5G Subscription Concealed Identifier (SUCI) catchers, were initially developed to maliciously intercept subscribers’ identities. Since then, further advances have been made, not only in RBSs, but also in communication network security. The identification and prevention of RBSs in Fifth Generation (5G) networks are among the main security challenges for users and network infrastructure. The security architecture group in 3GPP clarified that the radio configuration information received from user equipment could contain fingerprints of the RBS. This information is periodically included in the measurement report generated by the user equipment to report location information and Received Signal Strength (RSS) measurements for the strongest base stations. The motivation in this work, then is to generate 5G measurement reports to provide a large and realistic dataset of radio information and RSS measurements for an autonomous vehicle driving along various sections of a road. These simulated measurement reports can then be used to develop and test new methods for identifying an RBS and taking mitigating actions. The proposed approach can generate 20 min of synthetic drive test data in 15 s, which is 80 times faster than real time

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version

Comparing Gausian and exact models of malicious interference in VLC systems

Visible Light Communication (VLC) is a technique for high-speed, low-cost wireless data transmission based on LED luminaries. Wireless LAN environments are a major application of VLC. In these environments, VLC is used in place of traditional systems such as Wi-Fi. Because of the physical characteristics of visible light, VLC is considered to be superior to traditional radio-based communication in terms of security. However, as in all wireless systems, the security of VLC with respect to eavesdropping, signal jamming and modification must be analyzed. This paper focuses on the aspect of jamming in VLC networks. In environments where multiple VLC transmitters are used, there is the possibility that one or more transmitters will be hostile (or "rogue"). This leads to communication disruption, and in some cases, the hijacking of the legitimate data stream. In this paper we present the theoretical system model that is used in simulations to evaluate various rogue transmission scenarios in a typical indoor environment. The typical approach used so far in jamming analysis assumes that all disruptive transmissions may be modeled as Gaussian noise, but this assumption may be too simplistic. We analyze and compare two models of VLC jamming: the simplified Gaussian and the exact model, where the full characteristics of the interfering signal are taken into account. Our aim is to determine which methodology is adequate for studying signal jamming in VLC systems