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

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

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security

An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)

With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications

A heterogeneous network management approach to wireless sensor networks in personal healthcare environments

University of Technology, Sydney. Faculty of Science.Many countries are facing problems caused by a rapid surge in numbers of people over sixty-five. This aging population cohort will place a strain on the existing health systems because the elderly are prone to falls, chronic illnesses, dementia and general frailty. At the same time governments are struggling to attract more people into the health systems and there are already shortages of qualified nurses and care givers. This thesis represents a multi disciplinary approach to trying to solve some of the above issues. In the first instance the researcher has established the validity of the health crisis and then examined ways in which Information Technology could help to alleviate some of the issues. The nascent technology called Wireless Sensor Networks was examined as a way of providing remote health monitoring for the elderly, the infirm and the ill. The researcher postulated that Network Management models and tools that are used to monitor huge networks of computers could be adapted to monitor the health of persons in their own homes, in aged care facilities and hospitals. Wireless Sensor Network (WNS) Personal Healthcare can monitor such vital signs as a patient’s temperature, heart rate and blood oxygen level. WSNs (often referred to as Motes) use wireless transceivers that can do remote sensing. The researcher aimed to assist all stakeholders in the personal healthcare arena to use WSNs to improve monitoring. The researcher provided a solution architecture and framework for healthcare sensor monitoring systems, based on network management techniques. This architecture generalises to heterogeneous and autonomous data acquisition systems. Future directions from this research point towards new areas of knowledge from the development or creation of new technologies to support the exponential growth of ubiquitous, just-in-time WSN health informational services and applications such as the preventive and proactive personal care health management and services around it. The affordable and ubiquitous distributed access to remote personal health care technologies in the future could have an important impact in the society, by allowing the individuals to take immediate preventive actions over their overall health condition. These systems could potentially prevent death as well as improve national health budgets by limiting costly medical interventions that could have been avoided by individual, easy-action early prevention

Strategically Addressing the Latest Challenges of Workplace Mobility to Meet the Increasing Mobile Usage Demands

During this post-PC era, many organizations are embracing the concept of IT consumerization/ Bring-Your-Own Device (BYOD) in their workplace. BYOD is a strategy that enables employees to utilize their personally-owned mobile devices, such as smart phones, tablets, laptops, and netbooks, to connect to the corporate network and access enterprise data. It is estimated that employees will bring two to four Internet-capable devices to work for personal and professional activities. From increased employee satisfaction and productivity to lower IT equipment and operational expenditures, companies have recognized that mobile devices are reasonably essential to their own success. However, many organizations are facing significant challenges with the explosion of mobile devices being used today along with provisioning the appropriate supporting infrastructure due to the unprecedented demands on the wireless and network infrastructures. For example, there is not only a growth in the number of wirelessly connected devices but the amount of bandwidth being consumed on the enterprise networks as well which is furthermore driven by increased usage of video and enterprise applications. Managing mobility and storage along with securing corporate assets have become difficult tasks for IT professionals as many organizations underestimate the potential security and privacy risks of using wireless devices to access organizational resources and data. Therefore, to address the needs and requirements of a new mobile workforce, organizations must involve key members from the Information Technology (IT), Human Resources (HR) and various business units to evaluate the existing and emerging issues and risks posed by BYOD. Then a mobile strategy should be developed by taking into consideration the enterprise objectives to ensure it aligns with the overall organizational strategy. There are various solutions available to address the needs and demands of an organization, such as Distributed Intelligence Architecture, network optimization, monitoring tools, unified management and security platforms, and other security measures. By implementing a suitable mobile strategy, organizations can ensure their particular enterprise network and wireless architecture is designed for highly scalability, performance and reliability. They must also evaluate their existing policies and procedures to ensure appropriate security and privacy measures are in place to address the increasing mobile usage demands and potential liability risks. By taking these factors into consideration, our team has analyzed the current BYOD issues for Educational Testing Service (ETS), which is a non-profit organization based in Princeton, New Jersey. Our findings have revealed a few major technical concerns relating to inadequate network and wireless infrastructure and the lack of a unified management and security platform. Thus, the team has recommended for ETS to implement Distributed Intelligence Architecture, network optimization and Enterprise Mobility Management (EMM) to address and resolve their current issues and risks. In conclusion, companies are beginning to seize this transition in order to become competitive and productive in the workplace; however the unprecedented demands on the corporate network and risk to data security are critical aspects that need to be evaluated on an on-going basis. With this analysis, organizations can review, evaluate and implement the proposed solutions and best practices to address the most common BYOD-related issues that companies are facing these days. However, organizations should continually research the latest technologies that may be available and implement solutions that specifically meet their issues

Analyzing Usage Conflict Situations in Localized Spectrum Sharing Scenarios: An Agent-Based Modeling and Machine Learning Approach

As spectrum sharing matures, different approaches have been proposed for a more efficient allocation, assignment, and usage of spectrum resources. These approaches include cognitive radios, multi-level user definitions, radio environment maps, among others. However, spectrum usage conflicts (e.g., "harmful" interference) remain a common challenge in spectrum sharing schemes. In particular, in conflict situations where it is necessary to take actions to ensure the sound operations of sharing agreements. A typical example of a usage conflict is where incumbents' tolerable levels of interference (i.e., interference thresholds) are surpassed. In this work, we present a new method to examine and study spectrum usage conflicts. A fundamental goal of this project is to capture local resource usage patterns to provide more realistic estimates of interference. For this purpose, we have defined two spectrum and network-specific characteristics that directly impact the local interference assessment: resource access strategy and governance framework. Thus, we are able to test the viability in spectrum sharing situations of distributed or decentralized governance systems, including polycentric and self-governance. In addition, we are able to design, model, and test a multi-tier spectrum sharing scheme that provides stakeholders with more flexible resource access opportunities. To perform this dynamic and localized study of spectrum usage and conflicts, we rely on Agent-Based Modeling (ABM) as our main analysis instrument. A crucial component for capturing local resource usage patterns is to provide agents with local information about their spectrum situation. Thus, the environment of the models presented in this dissertation are given by the REM's Interference Cartography (IC) map. Additionally, the agents' definitions and actions are the results of the interaction of the technical aspects of resource access and management, stakeholder interactions, and the underlying usage patterns as defined in the Common Pool Resource (CPR) literature. Finally, to capture local resource usage patterns and, consequently, provide more realistic estimates of conflict situations, we enhance the classical rule-based ABM approach by using Machine Learning (ML) techniques. Via ML algorithms, we refine the internal models of agents in an ABM. Thus, the agents' internal models allow them to choose more suitable responses to changes in the environment

Modélisation formelle des systèmes de détection d'intrusions

L’écosystème de la cybersécurité évolue en permanence en termes du nombre, de la diversité, et de la complexité des attaques. De ce fait, les outils de détection deviennent inefficaces face à certaines attaques. On distingue généralement trois types de systèmes de détection d’intrusions : détection par anomalies, détection par signatures et détection hybride. La détection par anomalies est fondée sur la caractérisation du comportement habituel du système, typiquement de manière statistique. Elle permet de détecter des attaques connues ou inconnues, mais génère aussi un très grand nombre de faux positifs. La détection par signatures permet de détecter des attaques connues en définissant des règles qui décrivent le comportement connu d’un attaquant. Cela demande une bonne connaissance du comportement de l’attaquant. La détection hybride repose sur plusieurs méthodes de détection incluant celles sus-citées. Elle présente l’avantage d’être plus précise pendant la détection. Des outils tels que Snort et Zeek offrent des langages de bas niveau pour l’expression de règles de reconnaissance d’attaques. Le nombre d’attaques potentielles étant très grand, ces bases de règles deviennent rapidement difficiles à gérer et à maintenir. De plus, l’expression de règles avec état dit stateful est particulièrement ardue pour reconnaître une séquence d’événements. Dans cette thèse, nous proposons une approche stateful basée sur les diagrammes d’état-transition algébriques (ASTDs) afin d’identifier des attaques complexes. Les ASTDs permettent de représenter de façon graphique et modulaire une spécification, ce qui facilite la maintenance et la compréhension des règles. Nous étendons la notation ASTD avec de nouvelles fonctionnalités pour représenter des attaques complexes. Ensuite, nous spécifions plusieurs attaques avec la notation étendue et exécutons les spécifications obtenues sur des flots d’événements à l’aide d’un interpréteur pour identifier des attaques. Nous évaluons aussi les performances de l’interpréteur avec des outils industriels tels que Snort et Zeek. Puis, nous réalisons un compilateur afin de générer du code exécutable à partir d’une spécification ASTD, capable d’identifier de façon efficiente les séquences d’événements.Abstract : The cybersecurity ecosystem continuously evolves with the number, the diversity, and the complexity of cyber attacks. Generally, we have three types of Intrusion Detection System (IDS) : anomaly-based detection, signature-based detection, and hybrid detection. Anomaly detection is based on the usual behavior description of the system, typically in a static manner. It enables detecting known or unknown attacks but also generating a large number of false positives. Signature based detection enables detecting known attacks by defining rules that describe known attacker’s behavior. It needs a good knowledge of attacker behavior. Hybrid detection relies on several detection methods including the previous ones. It has the advantage of being more precise during detection. Tools like Snort and Zeek offer low level languages to represent rules for detecting attacks. The number of potential attacks being large, these rule bases become quickly hard to manage and maintain. Moreover, the representation of stateful rules to recognize a sequence of events is particularly arduous. In this thesis, we propose a stateful approach based on algebraic state-transition diagrams (ASTDs) to identify complex attacks. ASTDs allow a graphical and modular representation of a specification, that facilitates maintenance and understanding of rules. We extend the ASTD notation with new features to represent complex attacks. Next, we specify several attacks with the extended notation and run the resulting specifications on event streams using an interpreter to identify attacks. We also evaluate the performance of the interpreter with industrial tools such as Snort and Zeek. Then, we build a compiler in order to generate executable code from an ASTD specification, able to efficiently identify sequences of events