97,349 research outputs found
Secure and Decentralized Swarm Behavior with Autonomous Agents for Smart Cities
Unmanned Aerial Vehicles (UAVs), referenced as drones, have advanced to
consumer adoption for hobby and business use. Drone applications, such as
infrastructure technology, security mechanisms, and resource delivery, are just
the starting point. More complex tasks are possible through the use of UAV
swarms. These tasks increase the potential impacts that drones will have on
smart cities, modern cities which have fully adopted technology in order to
enhance daily operations as well as the welfare of it's citizens. Smart cities
not only consist of static mesh networks of sensors, but can contain dynamic
aspects as well including both ground and air based autonomous vehicles.
Networked computational devices require paramount security to ensure the safety
of a city. To accomplish such high levels of security, services rely on
secure-by-design protocols, impervious to security threats. Given the large
number of sensors, autonomous vehicles, and other advancements, smart cities
necessitates this level of security. The SHARK protocol (Secure, Heterogeneous,
Autonomous, and Rotational Knowledge for Swarms) ensures this kind of security
by allowing for new applications for UAV swarm technology. Enabling drones to
circle a target without a centralized control or selecting lead agents, the
SHARKS protocol performs organized movement among agents without creating a
central point for attackers to target. Through comparisons on the stability of
the protocol in different settings, experiments demonstrate the efficiency and
capacity of the SHARKS protocol.Comment: 8 pages, 1 figure, 1 chart, 8 table
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Security models for trusting network appliances
A significant characteristic of pervasive computing is the need for secure interactions between highly mobile entities and the services in their environment. Moreover,these decentralised systems are also characterised by partial views over the state of the global environment, implying that we cannot guarantee verification of the properties of the mobile entity entering an unfamiliar domain. Secure in this context encompasses both the need for cryptographic security and the need for trust, on the part of both parties, that the interaction is functioning as expected. In this paper we make a broad assumption that trust and cryptographic security can be considered as orthogonal concerns (i.e. cryptographic measures do not ensure transmission of correct information). We assume the existence of reliable encryption techniques and focus on the characteristics of a model that supports the management of the trust relationships between two devices during ad-hoc interactions
Adding X-security to Carrel: security for agent-based healthcare applications
The high growth of Multi-Agent Systems (MAS) in Open Networks with initiatives such as Agentcities1 requires development in many different areas such as scalable and secure agent platforms, location services, directory services, and systems management. In our case we have focused our effort on security for agent systems. The driving force of this paper is provide a practical vision of how security mechanisms could be introduced for multi-agent applications. Our case study for this experiment is Carrel [9]: an Agent-based application in the Organ and Tissue transplant domain. The selection of this application is due to its characteristics as a real scenario and use of high-risk data for example, a study of the 21 most visited health-related web sites on the Internet discovered that personal information provided at many of the sites was being inadvertently leaked for unauthorized persons. These factors indicate to us that Carrel would be a suitable environment in order to test existing security safeguards. Furthermore, we believe that the experience gathered will be useful for other MAS. In order to achieve our purpose we describe the design, architecture and implementation of security elements on MAS for the Carrel System.Postprint (published version
Data Confidentiality in Mobile Ad hoc Networks
Mobile ad hoc networks (MANETs) are self-configuring infrastructure-less
networks comprised of mobile nodes that communicate over wireless links without
any central control on a peer-to-peer basis. These individual nodes act as
routers to forward both their own data and also their neighbours' data by
sending and receiving packets to and from other nodes in the network. The
relatively easy configuration and the quick deployment make ad hoc networks
suitable the emergency situations (such as human or natural disasters) and for
military units in enemy territory. Securing data dissemination between these
nodes in such networks, however, is a very challenging task. Exposing such
information to anyone else other than the intended nodes could cause a privacy
and confidentiality breach, particularly in military scenarios. In this paper
we present a novel framework to enhance the privacy and data confidentiality in
mobile ad hoc networks by attaching the originator policies to the messages as
they are sent between nodes. We evaluate our framework using the Network
Simulator (NS-2) to check whether the privacy and confidentiality of the
originator are met. For this we implemented the Policy Enforcement Points
(PEPs), as NS-2 agents that manage and enforce the policies attached to packets
at every node in the MANET.Comment: 12 page
Emerging privacy challenges and approaches in CAV systems
The growth of Internet-connected devices, Internet-enabled services and Internet of Things systems continues at a rapid pace, and their application to transport systems is heralded as game-changing. Numerous developing CAV (Connected and Autonomous Vehicle) functions, such as traffic planning, optimisation, management, safety-critical and cooperative autonomous driving applications, rely on data from various sources. The efficacy of these functions is highly dependent on the dimensionality, amount and accuracy of the data being shared. It holds, in general, that the greater the amount of data available, the greater the efficacy of the function. However, much of this data is privacy-sensitive, including personal, commercial and research data. Location data and its correlation with identity and temporal data can help infer other personal information, such as home/work locations, age, job, behavioural features, habits, social relationships. This work categorises the emerging privacy challenges and solutions for CAV systems and identifies the knowledge gap for future research, which will minimise and mitigate privacy concerns without hampering the efficacy of the functions
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