Brent Lagesse

DTT: A Distributed Trust Toolkit for pervasive systems

Effective security mechanisms are essential to the widespread deployment of pervasive systems. Much of the research focus on security in pervasive computing has revolved around distributed trust management. While such mechanisms are effective in specific environments, there is no generic framework for deploying and extending these mechanisms over a variety of pervasive systems. We present the design and implementation of a novel framework called Distributed Trust Toolkit (DTT), for implementing and evaluating trust mechanisms in pervasive systems. The DTT facilitates the extension and adaptation of trust mechanisms by abstracting trust mechanisms into interchangeable components. Furthermore, the DTT provides a set of tools and interfaces to ease implementation of trust mechanisms and facilitate their execution on a variety of platforms and networks. In addition to the adaptability and extensibility provided by this design, we demonstrate through simulation that use of DTT improves utilization of resources and enhances performance of existing trust mechanisms in pervasive systems. We are currently developing an implementation of the DTT that can be easily deployed in pervasive environments.

A Game-Theoretical Model for Task Assignment in Project Management

The assignment of tasks to employees is one of the most essential aspects of a project managers job. A situation with employees working on tasks that they are not well-suited for can lead to a significant loss of time and resources in addition to a sub-par product or service. The simple difference between a good and bad task assignment for employees can easily result in major differences in a companys bottom line. We utilize techniques from game theory to produce an algorithm for matching employees and tasks based on manager and employee preference, employee time, and employee skills. As a result, we have created a deterministic algorithm for task assignment with built-in feedback mechanisms for measuring the health of the project group with respect to the work given

ReSCo: A middleware component for Reliable Service Composition in pervasive systems

Service composition schemes create high-level application services by combining several basic services. Service composition schemes for dynamic, open systems, such as those found in pervasive environments, must be cognizant of the possibility of failures and attacks. In open systems, it is seldom feasible to guarantee the reliability of each node prior to access; however, there may be several possible ways to compose the same high-level service, each having a different (though possibly overlapping) set of nodes that can satisfy the composition. We approach this problem with a Reliable Service Composition middleware component, ReSCo, to determine trustworthy compositions and nodes for service composition in dynamic, open systems. ReSCo is a modular, adaptive middleware component that selects from possible composition paths and nodes to enhance reliability of service compositions. ReSCo can work with a broad range of both service composition algorithms and trust establishment mechanisms.

Special issue on “Internet of Things: Research challenges and Solutions”

The past decade has witnessed a significant proliferation of nternet-capable devices. While its greatest commercial impact has een in the area of consumer electronics, with the smartphone evolution and the uptake of wearables, connecting humans is only art of a greater trend toward the interconnection of the physical orld with the digital world. While the Internet is a communication network connecting eople to information, the Internet of Things (IoT) is an interconected ecosystem of uniquely addressable physical objects with arying degrees of sensing, processing, and actuation capabilities, haring the ability to communicate and interoperate through the nternet as their common denominator [1] . With the IoT paradigm, sensor-equipped devices can provide ne-grained information about the physical world, allowing cloudased resources to extract value from such information and posibly make decisions to be implemented by actuator-equipped deices, blurring the line between the IoT and the broader concept of yber-Physical Systems [2–4] , which does not necessarily presupose Internet connectivity per se. The vagueness of the term “Things”makes it hard to define the ver expanding boundaries of the IoT, but at the same time offers clear idea of its heterogeneity and its virtually limitless applicaion potential. This has spawned very encouraging projections from arket analysts and corporate players who envision a multi-trillion ollar market for the IoT. As commercial success materializes, the IoT continues to offer a eemingly boundless supply of opportunities for both business and esearch. This special issue of Computer Communications is dediated to the latter, offering a varied collection of research contriutions to cutting-edge themes within the IoT space. This special ssue complements [5] , which focused on architectures, protocols, nd services.

A Novel Utility and Game-Theoretic Based Security Mechanism for Mobile P2P Systems

Research on security in peer-to-peer (P2P) systems is dominated by reputation-based solutions. These solutions propagate opinions about other peers in order to help identify the best set of peers to utilize. In this paper, we model peers with utility functions and use those functions to examine the case in which an individual peer participates in an unfamiliar and untrusted system, similar to one in which a mobile peer can enter when moving into a new location. We additionally introduce a novel security mechanism for P2P systems called resource exploration in order to mitigate the problems inherent in reputation-based systems and analyze its effect on a 2-player game (between an attacker and the benign peer).

UBCA: Utility-Based Clustering Architecture for Peer-to-Peer Systems

Peer-to-peer (P2P) systems are currently used in a variety of applications. File sharing applications and ad hoc networking have fueled the usage of these systems. P2P systems generate new challenges in scalability, fairness, and quality of service. Current systems often approach these challenges through incentive-based solutions and structured system design. Incentive-based solutions appeal to the self-interested nature of peers by utilizing payment or penalty to encourage peers to contribute to the system. System design principles, which attempt to improve performance through protocols and system-algorithms, include distributed hash tables and graph-theoretic designs. These approaches have seen some success, but also result in new problems such as overhead costs of authenticity/security for incentives, increased centralization, and decreased ability to handle dynamic peers. We introduce Utility-Based Clustering Architecture, (UBCA) designed to improve quality of service through the use of implicit incentives. UBCA runs on peers and groups them into logical clusters in real time, based on mutual utility gained as a result of the grouping. Simulation studies show with a high confidence that UBCA exhibits improved bandwidth and latency per access.

Embracing the cloud for better cyber security

The future of cyber security is inextricably tied to the future of computing. Organizational needs and economic factors will drive computing outcomes. Cyber security researchers and practitioners must recognize the path of computing evolution and position themselves to influence the process to incorporate security as an inherent property.

Analysis of Causative Attacks against SVMs Learning from Data Streams

Machine learning algorithms have been proven to be vulnerable to a special type of attack in which an active adversary manipulates the training data of the algorithm in order to reach some desired goal. Although this type of attack has been proven in previous work, it has not been examined in the context of a data stream, and no work has been done to study a targeted version of the attack. Furthermore, current literature does not provide any metrics that allow a system to detect these attack while they are happening. In this work, we examine the targeted version of this attack on a Support Vector Machine(SVM) that is learning from a data stream, and examine the impact that this attack has on current metrics that are used to evaluate a models performance. We then propose a new metric for detecting these attacks, and compare its performance against current metrics.

Toward consumer-friendly security in smart environments

The use of Internet of Things (IoT) devices has grown significantly in the past decade. While IoT is expected to improve life for many by enabling smart living spaces, the number of security risks that consumers and businesses will face is also increasing. A high number of vulnerable IoT devices are prone to attacks and easy exploit. Existing research has focused on security that must be implemented by administrators and manufacturers to be effective. Our work focuses on a system that does not rely on best practices by IoT device companies, but rather allows inexperienced users to be confident about the security of the devices that they add to their network. We present an implementation of an IoT architectural framework based on Software Defined Networking (SDN). In this architecture, IoT devices attempting to join an IoT network are scanned for vulnerabilities using custom vulnerability scanners and penetration testing tools before being allowed to communicate with any other device. In the case that a vulnerability is detected, the system will try to fix the vulnerability. If the fix fails, then the user will be alerted to the vulnerability and provided with suggestions for fixing it before it will be allowed to join the network. Our implementation demonstrates that the approach works and causes minimal overhead to the network once the device is deemed trustworthy.

Living Lab Bamberg: an infrastructure to explore smart city research challenges in the wild

The growing number of smart technologies for ubiquitous sensing and interaction of computer systems and the physical environment offer many opportunities for more efficient usage of energy and other resources and to improve the quality of life among communities. There are numerous problems that must be solved first. Research areas such as security, privacy, data quality, and data modeling must be addressed. In order to move forward to a better world, we have established the living lab Bamberg where we will address these research problems and provide open data and interfaces to other researchers to enable collaboration and extensive testing of smart city research and applications. As we continue to use the living lab Bamberg to improve state of the art research in smart cities, we believe we will see smart city technology adopted more commonly and drastically improve the lives of people living in those cities.