Is Homomorphic Encryption Feasible for Smart Mobility?

Smart mobility is a promising approach to meet urban transport needs in an environmentally and and user-friendly way. Smart mobility computes itineraries with multiple means of transportation, e.g., trams, rental bikes or electric scooters, according to customer preferences. A mobility platform cares for reservations, connecting transports, invoicing and billing. This requires sharing sensible personal data with multiple parties, and puts data privacy at risk. In this paper, we investigate if fully homomorphic encryption (FHE) can be applied in practice to mitigate such privacy issues. FHE allows to calculate on encrypted data, without having to decrypt it first. We implemented three typical distributed computations in a smart mobility scenario with SEAL, a recent programming library for FHE. With this implementation, we have measured memory consumption and execution times for three variants of distributed transactions, that are representative for a wide range of smart mobility tasks. Our evaluation shows, that FHE is indeed applicable to smart mobility: With today's processing capabilities, state-of-the-art FHE increases a smart mobility transaction by about 100 milliseconds and less than 3 microcents.Comment: submitted to FedCSI

Proceedings of the 2nd International Workshop on Security in Mobile Multiagent Systems

This report contains the Proceedings of the Second Workshop on Security on Security of Mobile Multiagent Systems (SEMAS2002). The Workshop was held in Montreal, Canada as a satellite event to the 5th International Conference on Autonomous Agents in 2001. The far reaching influence of the Internet has resulted in an increased interest in agent technologies, which are poised to play a key role in the implementation of successful Internet and WWW-based applications in the future. While there is still considerable hype concerning agent technologies, there is also an increasing awareness of the problems involved. In particular, that these applications will not be successful unless security issues can be adequately handled. Although there is a large body of work on cryptographic techniques that provide basic building-blocks to solve specific security problems, relatively little work has been done in investigating security in the multiagent system context. Related problems are secure communication between agents, implementation of trust models/authentication procedures or even reflections of agents on security mechanisms. The introduction of mobile software agents significantly increases the risks involved in Internet and WWW-based applications. For example, if we allow agents to enter our hosts or private networks, we must offer the agents a platform so that they can execute correctly but at the same time ensure that they will not have deleterious effects on our hosts or any other agents / processes in our network. If we send out mobile agents, we should also be able to provide guarantees about specific aspects of their behaviour, i.e., we are not only interested in whether the agents carry out-out their intended task correctly. They must defend themselves against attacks initiated by other agents, and survive in potentially malicious environments. Agent technologies can also be used to support network security. For example in the context of intrusion detection, intelligent guardian agents may be used to analyse the behaviour of agents on a firewall or intelligent monitoring agents can be used to analyse the behaviour of agents migrating through a network. Part of the inspiration for such multi-agent systems comes from primitive animal behaviour, such as that of guardian ants protecting their hill or from biological immune systems

Analyzing the Effects of Transit Network Change on Agency Performance and Riders in a Decentralized, Small-to-Mid-sized US Metropolitan Area: A Case Study of Tallahassee, Florida, MTI Report 12-04

On July 11, 2011, StarMetro, the local public transit agency in Tallahassee, Florida, restructured its entire bus network from a downtown-focused radial system to a decentralized, grid-like system that local officials and agency leaders believed would better serve the dispersed local pattern of population and employment. The new, decentralized network is based on radial routes serving the major arterial roads and new crosstown routes linking the outer parts of the city, where population and employment is growing. Local officials and agency staff hoped the change would increase transit’s attractiveness and usefulness to the community. One year after the service restructuring, overall performance results are similar to those experienced in other cities that have implemented major service changes. Overall ridership and productivity are lower than before the service restructuring, due to the short time frame for rider adjustments and longer-than-anticipated headways, but new ridership has appeared in previously un-served or under-served corridors and neighborhoods. The service restructuring resulted in longer walks to bus stops, due to the removal of stops from many neighborhoods and their relocation to major roads, but overall transit travel times are shorter due to more direct routing. No particular neighborhoods or community groups disproportionately benefited from or were harmed by the change. The service restructuring was supported by some segments of the community who viewed the older system as ill-suited to the increasingly decentralized community, while it was opposed by other community stakeholders who worried about the loss of service in some neighborhoods and issues of access and safety, particularly affecting elderly and disabled riders, at new stop locations. StarMetro’s extensive public outreach efforts and ongoing service adjustments have reduced the intensity of the opposition to the service restructuring over time, although some segments of the community continue to voice their concerns about the effects of the change on transit-dependent, disabled, and elderly riders

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

High Accuracy Distributed Target Detection and Classification in Sensor Networks Based on Mobile Agent Framework

High-accuracy distributed information exploitation plays an important role in sensor networks. This dissertation describes a mobile-agent-based framework for target detection and classification in sensor networks. Specifically, we tackle the challenging problems of multiple- target detection, high-fidelity target classification, and unknown-target identification. In this dissertation, we present a progressive multiple-target detection approach to estimate the number of targets sequentially and implement it using a mobile-agent framework. To further improve the performance, we present a cluster-based distributed approach where the estimated results from different clusters are fused. Experimental results show that the distributed scheme with the Bayesian fusion method have better performance in the sense that they have the highest detection probability and the most stable performance. In addition, the progressive intra-cluster estimation can reduce data transmission by 83.22% and conserve energy by 81.64% compared to the centralized scheme. For collaborative target classification, we develop a general purpose multi-modality, multi-sensor fusion hierarchy for information integration in sensor networks. The hierarchy is com- posed of four levels of enabling algorithms: local signal processing, temporal fusion, multi-modality fusion, and multi-sensor fusion using a mobile-agent-based framework. The fusion hierarchy ensures fault tolerance and thus generates robust results. In the meanwhile, it also takes into account energy efficiency. Experimental results based on two field demos show constant improvement of classification accuracy over different levels of the hierarchy. Unknown target identification in sensor networks corresponds to the capability of detecting targets without any a priori information, and of modifying the knowledge base dynamically. In this dissertation, we present a collaborative method to solve this problem among multiple sensors. When applied to the military vehicles data set collected in a field demo, about 80% unknown target samples can be recognized correctly, while the known target classification ac- curacy stays above 95%

The Attracting Intelligent Minds Conference: An Assessment of Graduate Diversity Recruitment

Graduate student recruitment is one of the most important factors in growing university enrollment. Unlike undergraduate recruitment, graduate recruitment is a coordinated effort facilitated between graduate faculty and program coordinators and graduate recruiters who often work outside of the department. An essential element in graduate recruitment is the effectiveness with which underrepresented minorities are identified and recruited. Graduate schools are commonly using initiatives known as intervention strategies to help enhance their traditional recruitment strategies and campus visitation programs have become a popular recruitment tool within those strategies. Since the 1990’s, the University of Arkansas (UA) has employed various intervention strategies utilizing the campus visitation approach to attract minority graduate students. A frequently used program is the Attracting Intelligent Minds (AIM) Conference. This study assesses the AIM conference, using Program Evaluation Theory, to determine how impactful it has been as a recruitment vehicle. The Program Theory Evaluation (PTE) framework was used to examine the conference activities, recruitment strategies, involvement with graduate faculty and administrators, and the roles that UA and Minority Serving Institutes (MSI), particularly Historically Black Colleges and Universities (HBCU) play in the success of the conference. Broadly, the study determined that AIM has been moderately effective for recruiting underrepresented minorities, primarily from HBCUs, to various graduate programs at UA, and strengthening the cultural capital among existing graduate students. But its continued success and growth will be largely dependent on collaboration between all stakeholders and the priority that is placed upon minority graduate recruitment

Using mobility and exception handling to achieve mobile agents that survive server crash failures

Mobile agent technology, when designed and used effectively, can minimize bandwidth consumption and autonomously provide a snapshot of the current context of a distributed system. Protecting mobile agents from server crashes is a challenging issue, since developers normally have no control over remote servers. Server crash failures can leave replicas, instable storage, unavailable for an unknown time period. Furthermore, few systems have considered the need for using a fault tolerant protocol among a group of collaborating mobile agents. This thesis uses exception handling to protect mobile agents from server crash failures. An exception model is proposed for mobile agents and two exception handler designs are investigated. The first exists at the server that created the mobile agent and uses a timeout mechanism. The second, the mobile shadow scheme, migrates with the mobile agent and operates at the previous server visited by the mobile agent. A case study application has been developed to compare the performance of the two exception handler designs. Performance results demonstrate that although the second design is slower it offers the smaller trip time when handling a server crash. Furthermore, no modification of the server environment is necessary. This thesis shows that the mobile shadow exception handling scheme reduces complexity for a group of mobile agents to survive server crashes. The scheme deploys a replica that monitors the server occupied by the master, at each stage of the itinerary. The replica exists at the previous server visited in the itinerary. Consequently, each group member is a single fault tolerant entity with respect to server crash failures. Other schemes introduce greater complexity and performance overheads since, for each stage of the itinerary, a group of replicas is sent to servers that offer an equivalent service. In addition, future research is established for fault tolerance in groups of collaborating mobile agents

Strategy-based dynamic assignment in transit networks with passenger queues

This thesis develops a mathematical framework to solve the problem of dynamic assignment in densely connected public transport (or transit – the two words are interchangeably used) networks where users do not time their arrival at a stop with the lines’ timetable (if any is published). In the literature there is a fairly broad agreement that, in such transport systems, passengers would not select the single best itinerary available, but would choose a travel strategy, namely a bundle of partially overlapping itineraries diverging at stops along different lines. Then, they would follow a specific path depending on what line arrives first at the stop. From a graph-theory point of view, this route-choice behaviour is modelled as the search for the shortest hyperpath (namely an acyclic sub-graph which includes partially overlapping single paths) to the destination in the hypergraph that describes the transit network. In this thesis, the hyperpath paradigm is extended to model route choice in a dynamic context, where users might be prevented from boarding the lines of their choice because of capacity constraints. More specifically, if the supplied capacity is insufficient to accommodate the travel demand, it is assumed that passenger congestion leads to the formation of passenger First In, First Out (FIFO) queues at stops and that, in the context of commuting trips, passengers have a good estimate of the expected number of vehicle passages of the same line that they must let go before being able to board. By embedding the proposed demand model in a fully dynamic assignment model for transit networks, this thesis also fills in the gap currently existing in the realm of strategy-based transit assignment, where – so far – models that employ the FIFO queuing mechanism have proved to be very complex, and a theoretical framework for reproducing the dynamic build-up and dissipation of queues is still missing.Open Acces

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

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Cargo Logistics Airlift Systems Study (CLASS). Volume 5: Summary

Findings and conclusions derived during the study of freighter aircraft requirements to the year 2008 are summarized. These results represent the stepping off point for the much needed coordinated planning efforts by government agencies, the airlines, the users, and the aircraft manufacturers. The methodology utilized in the investigations is shown. The analysis of the current system encompassed evaluations of the past and current cargo markets and on sight surveys of airport and cargo terminals. The findings that resulted provided the basis for formulating the case study procedures, developing the future scenario, and developing the future cargo market demand