Eagle eye: an accountable logging framework for distributed systems

Security in computer systems has been a major concern since the very beginning. Although security has been addressed in various aspects, accountability is a main stream of security which is lacking in today's computer systems. The ability to not just detect errors but also to find the reason for the failure and also the system in charge is crucial. In this thesis, studies on the various accountability tactics available and how each one of them contributes towards providing strong accountability are performed. The various merits and tradeoffs are also studied. Accountability in distributed systems is a main issue which has to be dealt with more effectively and efficiently. This thesis introduces Eagle Eye, which is a novel approach to overlay accountability over distributed systems. It is a standalone application which does not merge with the application which is being monitored. Eagle Eye works by maintaining secure log files of all the packets being sent and received. Faults are detected using these recorded log files on-demand and periodically. Eagle Eye can be used with a wide variety of applications as it only requires that the results are deterministic and not arbitrary. Eagle Eye was applied to three different protocols over peer-to-peer system and over the network file system and was analyzed. (Published By University of Alabama Libraries

Identifying programmer ability using peer evaluation: an empirical investigation

The ability of students to accurately rate the programming ability of their peers was investigated. Two studies were performed in the context of undergraduate Computer Science courses to measure how closely student peer ratings matched class grades given by course instructors. The results showed that peer ratings did correlate with instructor grades. Additional data was collected regarding how the students related to each other through previous projects and social network connections. These relations were treated as measures of familiarity. Networks of familiarity were created and clusters within these networks were identified to show which students were more familiar with each other. Analyzing these clusters showed that familiarity plays a role in the accuracy of the peer ratings. Students who were more familiar with each other generally provided more accurate ratings of their peers. Further testing is warranted to validate these results, since the data gathered was more sparse than anticipated at the beginning of the study. Also, further analysis of the effect of familiarity may yield more compelling results if different network clustering methods are applied. (Published By University of Alabama Libraries

Communication in disruption tolerant networks: models, analyses and routing

Many scenarios for mobile and wireless networks demonstrate disruptions in communications where connections may not be available from time to time, examples include wireless sensor networks, tactical mobile ad hoc networks, planetary networks and vehicular networks. The intermittent connection could be a result of the mobility of wireless nodes, the limited transmission range, communication jamming or the low nodal density. To deal with the problems, Disruption Tolerant Networking (DTN) has been proposed to handle the disconnection based on a store-carry-forward paradigm. Among the approaches for reducing the communication latency in DTN, introducing the relay nodes called throw-box has been proved to be an effective one. However few studies have provided sufficient analysis and routing solutions for throw-box based network paradigm. This dissertation addresses several challenging issues relating to wireless networks, and specifically, DTN. Firstly, we study the issue of connectivity by focusing on the transition phase of wireless network from a state of partition to a state of connection according to the growth of node density. A percolation theory based model is proposed to derive the lower bound and the upper bound of critical density and further find the critical time points that mark the network transformation from partition to connected state. The second work is to analyze the latency of message dissemination in the throw-box assisted DTNs. In this network architecture, static wireless devices called throw-boxes are deployed to increase message delivery probability and to reduce transmission latency. The research works include modeling the message delivering process among throw-boxes and modeling the latency distribution for message collection. Finally, we propose efficient routing strategies for the throw-box assisted DTNs. In such a network, the mobile nodes traveling between the throw-boxes form time-dependent network links which carry the temporally stored messages from one box to another. Our protocol is designed to consider jointly the capacity of mobile nodes and the time-dependent delay. A Markov model is proposed to describe the evolution of the real-time link, and to help derive the forwarding decision and routing policy. Our trace based simulation validates the advantages of the proposed routing strategy. (Published By University of Alabama Libraries

Programming by voice: a hands-free approach for motorically challenged children

Computer Science (CS) educators frequently develop new methodologies, languages, and programming environments to teach novice programmers the fundamental concepts of CS. A recent trend has focused on new environments that reduce the initial challenges associated with the heavy syntax focus of textual programming languages. There are numerous Initial Programming Environments (IPEs) available that have been created for student use that in some cases have fostered self-discovery and inquiry-based exploration. In this dissertation, three IPEs are discussed: Scratch (2015), Lego Mindstorms (2015), and Blockly (2015). Although the block-based nature of IPEs can be helpful for learning concepts in CS, a small group of students (approximately 5%) is being left out from learning experiences and engagement in CS due to block-based environments’ dependence on the Windows Icon Mouse Pointer (WIMP) metaphor. Block-based environments often require the use of both a mouse and keyboard, which motorically challenged users often are unable to operate. Based on research performed and presented in this dissertation, a Vocal User Interface (VUI) is a viable solution that offers a “Programming by Voice” (PBV) capability (i.e., a capability to describe a program without using a keyboard or mouse). However, adapting legacy applications can be time consuming, particularly, if multiple applications (such as the three IPEs previously mentioned) require specialized VUIs. Each environment has its own visual layout and its own commands; therefore, each application requires a different VUI. In order to create a more generic solution, a Domain-Specific Language (DSL) can be applied to create a semi-automated process allowing a level of abstraction that captures the specific needs of each IPE. From the specification of each IPE, a customized VUI can be generated that integrates with the legacy application in a non-invasive manner. The nine chapters included in this dissertation were motivated by the following four research questions: 1. How can we improve initial programming instruction? 2. Can all children participate in programming instruction? 3. How do we implement PBV to allow children to take advantage of creative, block-based programming environments? 4. What are some potential ideas that can assist in generalizing the process of voice enabling IPEs? (Published By University of Alabama Libraries

UbiMice: a fluid interaction model for multicomputer workspace

Nowadays it is not uncommon for people to have multiple computers in a workspace. A multicomputer workspace favors a user to perform multiple various tasks. At the same time, there is a short of fluid interaction model for this workspace while excessive mice and keyboards that are adjacent to multiple computers bring chaos to the workspace causing a cluttered desktop. A user has to switch back and forth to interact with different workstations. Furthermore, information is often needed to be exchanged among computers every now and then. For information to cross the boundary between two computers, several technologies such as file sharing have already been developed. However, these technologies incommode hands to move between different keyboards and/or mice, which are interruptive. This dissertation proposes a fluid interaction model called UbiMice for the multicomputer workspace to address these issues. In the UbiMice model, co-located computers form a multicomputer workspace. A user needs only one set of input devices to interact with any computer in the workspace. This eradicates gaps of operating multiple input devices and eliminates desktop clutter brought by nimiety keyboards and mice. An interacting focus is represented by a cursor. The cursor can move from computer to computer, interact with any computer, and carry information among the computers. This proposed model also allows multiple cursors used by multiple users simultaneously for collaborative working. A security mechanism is also provided with the model to protect information from unauthorized access in the multi-user case. The UbiMice model enables to build a seamless workspace from multiple computers. Traditional input devices are augmented with the capability of serving multiple computers. Users can interact with the workspace intuitively as if they were interacting with a single computer. This dissertation will study the architecture of UbiMice model together with a proof-of-concept implementation. The model finds many novel applications in different settings and benefits a wide range of user groups. (Published By University of Alabama Libraries

Algorithms with applications in robotics

Many real world applications which involve computational steps are closely tied to theoretical computer science. In order for these systems to be efficiently deployed and used, a thorough analysis is required in advance. This dissertation deals with several real world problems related to the field of Robotics, which can be mathematically modeled and analyzed. One of these problems is known as the pursuit evasion problem and involves the use of independent automated robots to capture a fugitive hiding in a building or a cave system. This is an extensively studied game theory and combinatorics problem which has multiple variations. It can be modeled as a graph and the goal is to minimize the cost of capturing the evader. We deal with two completely different variations of this problem: a vision based variant, in which the robots have limited vision and thus can react when the fugitive is in line of sight; and a no-vision variant, in which the robots do not have any knowledge about the fugitive. Another problem we deal with is the problem of neighbor discovery in wireless networks using directional antennas. This is another problem which received a growing interest in the last years. Our approach to solving this problem, as well as the model, is different from the other results that have been previously published in the literature. Besides modeling and formally analyzing these problems, our focus in this dissertation is to design efficient algorithms that solve them either completely or partially. (Published By University of Alabama Libraries

Accountable logging and its applications to intrusion detection

Today's computer and network systems were not originally designed for accountability which plays a crucial role in information assurance systems. To assure accountability, each entity in the system should be held responsible for its own behaviors so that the entity is a part of larger chains of the system's accountability. To achieve accountability, a flow-net methodology that records events as well as relations between events was proposed. The multi-layer feature of computer and network systems brings us the chance to achieve multiple degrees of accountability, which means we are able to acknowledge the system's behaviors at different levels of accountability. In this dissertation, a multi-resolution flow-net is proposed for achieving multi-layer accountability. Moreover, Intrusion Detection Systems that monitor malicious behaviors in computer and network systems play an important role in assuring system security. Flow-net that builds comprehensive logs and helps track events is able to order to record system and user behaviors. In this dissertation, an Intrusion Detection Scheme by Flow-Net Based Fingerprint (IDS-FF) scheme is proposed for detecting fingerprints of malicious behaviors. As an application of the IDS-FF scheme, we use it to detect intrusions in TCP/IP networks. Furthermore, in order to detect the intrusions that disguise themselves as regular behaviors in networks, we apply the IDS-FF scheme with cryptography techniques in TCP/IP networks. (Published By University of Alabama Libraries

RDIS: a domain model for generalizing the mappings between robotic software frameworks and robotic devices

Researchers, hobbyists, and industrial professionals alike have moved toward a framework-based approach to robotics application development. This allows robotic applications to be written for the domain of the framework and benefits the application developer as it offers domain-specific abstractions and reusability of applications. However, a framework must still know how to translate its domain-specific concepts to the device-specific concepts. One can do this in a general-purpose programming language, but this strategy is not sustainable because drivers must be hand-crafted for each possible permutation of framework and device. Therefore, exploring the appropriate level of abstraction for device drivers is interesting and may enable a description of a robot for it to be used with any robotics framework. A domain model for defining these mappings has been developed. The domain model allows descriptions of robots to be reused between frameworks. The specific mechanism for this is to describe the domain model using a textual syntax and interpret the description at run-time. One may then define the transformation of framework domain concepts to concepts native to the domain model as an adapter. Thus, any appropriately enabled robotic framework and device can communicate with one another. As further evidence for the viability of the domain model, it was implemented formally using the model-driven tool \atommm. One may then design the model at a high-level directly in the terms introduced by the model without the mental load posed by the textual syntax. As well, the tool presents a preliminary approach for generating adapters for frameworks. Future directions for the domain model include kinematic state modeling. A literature review and a preliminary approach for this has also been prepared. (Published By University of Alabama Libraries

Design and analysis of accountable networked and distributed systems

This dissertation focuses on the design and analysis of accountable computing for a wide range of networked systems with affordable expense. The central idea is to incorporate accountability, a long-neglected security objective, into the design and implementation of modern computing systems. Broadly speaking, accountability in the cyber-security domain means that every entity ought to be held responsible for its behavior, and that there always exists undeniable and verifiable evidence linking each event to the liable entities. This dissertation studies accountable computing in three different contexts, including traditional distributed systems, cloud computing, and the Smart Grid. We first propose a quantitative model called P-Accountability to assess the degree of system accountability. P-Accountability consists of a flat model and a hierarchical model. Our results show that P-Accountability is an effective metric to evaluate general distributed systems such as PeerReview [1] in terms of accountability. Next, we develop Accountable MapReduce for cloud computing to prevent malicious working machines from manipulating the processing results. To achieve this goal, we set up a group of auditors to perform an Accountability-Test (A-test) that checks all working machines and detects malicious nodes in real time. Finally, we investigate the accountability issues in the neighborhood area smart grid. A mutual inspection scheme is presented to enable non-repudiation for metering. In addition, we propose and analyze a suite of algorithms to identify malicious meters for the detection of energy theft. (Published By University of Alabama Libraries

A data mining approach to identify perpetrators: an integration framework and case studies

Data mining and social network analysis have been widely used in law enforcement to solve crimes. Research questions such as strength of ties in social networks, crime pattern discovery and prioritizing offenders have been studied in this area. However, most of those studies failed to consider the noisy nature of the data. The techniques they proposed only have been applied to small scale data sets. Therefore, it is an important task to design a framework that can work on large scale data sets and tolerance noisy data. In this dissertation, we built an integrated crime detection framework that combined two data mining techniques: decision tree and genetic algorithm and graph theories to solve the problems we pointed out. Our crime pattern analysis is based on all offenders of the state of Alabama in the past 50 years. Our constructed social network contains all Alabama residents. It allows us to fully evaluate the proposed models. Two case studies have been conducted to evaluate the framework. One is based on 625 inmates released from Madison county jail in 2004. Our experimental results show that our recommended risk level has strong correlation in predicting future offense. Another case study is based on the 100 real police reports. The experimental results show that the median ranking of arrestees remains at the top 3% of the return list. (Published By University of Alabama Libraries