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关键词： Computer engineering   Robotics   Computer science  

摘要： Nonverbal interactions are a key component of human communication. Since robots have become significant by trying to get close to human beings, it is important that they follow social rules governing the use of space. Prior research has conceptualized personal space as physical zones which are based on static distances. This work examined how preferred interaction distance can change given different interaction scenarios. We conducted a user study using three different robot heights. We also examined the difference in preferred interaction distance when a robot approaches a human and, conversely, when a human approaches a robot. Factors included in quantitative analysis are the participants' gender, robot's height, and method of approach. Subjective measures included human comfort and perceived safety. The results obtained through this study shows that robot height, participant gender and method of approach were significant factors influencing measured proxemic zones and accordingly participant comfort. Subjective data showed that experiment respondents regarded robots in a more favorable light following their participation in this study. Furthermore, the NAO was perceived most positively by respondents according to various metrics and the PR2 Tall, most negatively. A follow up study involved finding out if there is any correlation between the robot's height and the method of approach focus across each proxemic zone based on the results obtained from our prior work. In addition, we conducted an user study to understand how interaction distance between a human and a robot changes with the change in the robot's physical configuration such as arm position (extended versus tucked in) and gaze (robot directly looking at the participant versus robot being distracted reading a newspaper). Data collected from this experiment was used to study the relationship between the physical configuration of the robot and preferred interaction distance. Subjective measures included hum

关键词： Information technology   Computer science  

摘要： Distributed Denial of Service (DDoS) attacks attempt to make online services inaccessible to legitimate users. Such attacks require immediate and automatic responses in real-time to prevent or minimize the system downtime. Administrators deploy security appliances such as Intrusion Detection Systems (IDSs) for detection and firewalls for mitigation. Despite the use of these security methods, DDoS attacks continue to occur, interrupting services to their clients. This dissertation presents a generic defense model against DDoS attacks. The proposed solution is software-based instead of hardware-based. Our solution takes advantage of the automation of the Network Functions Virtualization (NFV) paradigm to provide an automatic response to mitigate DDoS attacks without human intervention. The proposed model screens and detects the attack using two types of detectors: alert protocol and a novel Virtualized Security Function (VSF) screening component. Our defense model can be deployed at the organization’s premises to reduce latency and achieve better privacy and security. As numerous types of DDoS attacks exist, this dissertation focuses on SYN flooding as a common and powerful type of DDoS attack. We propose an internal collaborative screening framework in which the screening component comprises of multiple detection agents and a screening controller to ensure that the detection system has adequate capacity to resist the attacks. Our defense system analyzes and aggregates multiple reported SYN patterns to generate customized blocking rulesets. The dissertation also proposes a novel firewall type, XFirewall, to block DDoS attacks. XFirewall is a supplementary, temporary firewall that uses dynamic security rules generated based on the detected pattern. XFirewall is automatically created and removed as needed. Previous detection approaches have fallen short to defeat SYN flooding attacks, as these approaches have weaknesses in detecting attacks with spoofed IP addresses, re

关键词： Computer engineering   Information technology   Computer science  

摘要： Binary instrumentation facilitates the insertion of additional code into an executable in order to observe or modify the executable’s behavior. The uses of binary instrumentation generally fall in to two categories — program observation tooling such as performance profilers and program augmentation tooling such as software updaters and security hardening tools. Both above types of uses are, however, hindered by the instrumentation overhead. For example, fine-grained performance profiling is often done offline due to high overheads. Also, many security hardening schemes such as shadow stacks and control-flow-integrity have not found mass adoption due to their overheads. I present two approaches which can reduce the binary instrumentation overheads and thus, can help bring some of these tooling online and more widely adopted. The first approach is on-demand instrumentation, which is the ability to enable and disable, aka toggle, instrumentation at run-time. Current instrumentation frameworks lack the primitives for cheap run-time instrumentation toggling. I present several novel instruction patching primitives, Wordpatch, Callpatch and Instruction Punning, which in combination, can be used to implement cheap, rapidly togglable instrumentation. I demonstrate the application of these primitives by developing a lightweight latency profiler. The second approach is instrumentation elision, which skips inserting instrumentation at certain program locations using a particular instrumentation policy. Using shadow stacks as a case study, I demonstrate how we can elide shadow stack instrumentation on certain safe code regions as determined by binary static analysis. Finally, I present how this application of instrumentation elision leads to significant overhead reductions in shadow stacks.

关键词： Mathematics   Computer science  

摘要： The main goal of this research is to design and develop a genetic algorithm (GA) for path planning of an Unmanned Aerial Vehicle (UAV) outfitted with a camera to efficiently search for a lost person in an area of interest. The research focuses on scenarios where the lost person is from a vulnerable population, such as someone suffering from Alzheimer or a small child who has wondered off. To solve this problem, a GA for path planning was designed and implemented in Matlab. The area of interest is considered to be a circle that encompasses the distance the person could have walked in the time they have been missing. The area might also have some subareas that could not be excluded from the search for various reasons, such as a river they could not cross, or a fenced area. A grid is imposed on the area of interest, based on the field of view of the camera that the UAV is carrying and the height the UAV is flying. A chromosome is the encoding of the path the UAV will fly and the fitness function of the GA is designed to ensure that the UAV is covering all areas of the grid with the least amount of backtracking. The results show that the GA can find a path that efficiently covers the area. These results can be generalized to use more than one UAV.

关键词： Artificial intelligence   Computer science  

摘要： Team Formation Problem (TFP) in Social Networks (SN) is to collect the group of individuals who match the requirements of given tasks under some constraints. It has several applications, including academic collaborations, healthcare, and human resource management. These types of problems are highly challenging because each individual has his or her own demands and objectives that might conflict with team objectives. The major contribution of this dissertation is to model a computational framework to discover teams of experts in various applications and predict the potential for collaboration in the future from a given SN. Inspired by an evolutionary search technique using a higher-order cultural evolution, a framework is proposed using Knowledge-Based Cultural Algorithms to identify teams from co-authorship and industrial settings. This model reduces the search domain while guiding the search direction by extracting situational knowledge and updating it in each evolution. Motivated from the above results, this research examines the palliative care multidisciplinary networks to identify and measure the performance of the optimal team of care providers in a highly dynamic and unbalanced SN of volunteer, community, and professional caregivers. Thereafter, a visualization framework is designed to explore and monitor the evolution in the structure of the care networks. It helps to identify isolated patients, imbalanced resource allocation, and uneven service distribution in the network. This contribution is recognized by Hospice and the Windsor Essex Compassion Care Community in partnership with the Faculty of Nursing. In each setting, several cost functions are attempted to measure the performance of the teams. To support this study, the temporal nature of two important evaluation metrics is analyzed in Dynamic Social Networks (DSN): dynamic communication cost and dynamic expertise level. Afterward, a novel generic framework for TFP is designed by incorporating essentia

关键词： Computer science  

摘要： Utilities infrastructure like the electric grid have been the target of more sophisticated cyberattacks designed to disrupt their operation and create social unrest and economical losses. Just in 2016, a cyberattack targeted the Ukrainian power grid and successfully caused a blackout that affected 225,000 customers. Industrial Control Systems (ICS) are a critical part of this infrastructure. Honeypots are one of the tools that help us capture attack data to better understand new and existing attack methods and strategies. Honeypots are computer systems purposefully left exposed to be broken into. They do not have any inherent value, instead, their value comes when attackers interact with them. However, state-of-the-art honeypots lack sophisticated service simulations required to obtain valuable data. Worst, they cannot adapt while ICS malware keeps evolving and attacks patterns are increasingly more sophisticated. This work presents HoneyPLC: A Next-Generation Honeypot for ICS. HoneyPLC is, the very first medium-interaction ICS honeypot, and includes advanced service simulation modeled after S7-300 and S7-1200 Siemens PLCs, which are widely used in real-life ICS infrastructures. Additionally, HoneyPLC provides much needed extensibility features to prepare for new attack tactics, e.g., exploiting a new vulnerability found in a new PLC model. HoneyPLC was deployed both in local and public environments, and tested against well-known reconnaissance tools used by attackers such as Nmap and Shodan's Honeyscore. Results show that HoneyPLC is in fact able to fool both tools with a high level of confidence. Also, HoneyPLC recorded high amounts of interesting ICS interactions from all around the globe, proving not only that attackers are in fact targeting ICS systems, but that HoneyPLC provides a higher level of interaction that effectively deceives them.

关键词： Watermarking   Medical diagnostic imaging   Authentication   Image quality   Computer science   Image reconstruction   Medical images   fragile watermarking   authentication   self-recovery   turtle shell-based data hiding (TSDH)  

摘要： It is increasingly important to achieve security and anti-counterfeiting for medical images. The integrity and verifiability of medical images before they are reviewed for potential medical diagnoses is imperative. This paper presents an effective self-embedding fragile watermarking scheme for medical images. Both self-recovery information and authentication code for each block are generated in advance and then embedded into other blocks separately with the help of the turtle shell and embedding table. In the tampering detection and localization phase, a three-level detection and localization strategy is employed to achieve higher accuracy for tampering localization. In the self-recovery phase, a two-hierarchical restoration method is exploited to achieve higher image quality in the recovered images. Several malicious attacks were tested to demonstrate the performance of the proposed scheme in terms of tampering detection and image recovery. Simulation results confirmed that the tampering detection rate can be up to 99.83% and the average PSNR of a recovered image can be up to 42.11 dB, both of which are higher than those of the Shehab et al.'s method.

关键词： Computer science  

摘要： In the last two decades, a new class of rendering methods called image-based rendering has emerged as an alternative to traditional geometry-based rendering methods. Image-based representations require an intensive amount of image data, making compression a critical issue. In particular, we need efficient compression schemes that map well to the current graphics hardware and provide random access capability for interactive applications. In this dissertation, we present new, efficient random-access compression schemes for three different image-based representations. Our first compression scheme, MPTC, introduces the idea of transcoding compressed video data directly to compressed textures such that the decoded output can be rendered using commodity texture mapping hardware. Our method improves rendering speeds up to an order of magnitude on mobile devices. Next, we propose two novel compression schemes, RLFC and HMLFC, for encoding light field images. In the RLFC algorithm, we describe a new hierarchical approach that provides progressive streaming and decoding capabilities that enable interactive rendering of light fields. HMLFC combines two different approaches for encoding light fields, motion compensation and hierarchical approaches to capture redundancies in a hybrid fashion; the compression rates with the hybrid approach improve by a factor of 2-5 times over the underlying motion and hierarchical schemes. Our third compression method, RANDM, deals with compressing depth maps using a range-partitioning and a global dictionary. RANDM is the first compression scheme that enables random access decoding for depth maps and achieves compression rates similar to the existing schemes. Each of these three methods allow compressed representation of image data in memory while rendering and selectively decoding required data quickly during run-time. We also present a novel, deep learning-based approach (neural networks), TexNN, for predicting the right set of encoding param

关键词： Computer science  

摘要： Data Mining (DM) is a process for extracting interesting patterns from large volumes of data. It is one of the crucial steps in Knowledge Discovery in Databases (KDD). It involves various data mining methods that mainly fall into predictive and descriptive models. Descriptive models look for patterns, rules, relationships and associations within data. One of the descriptive methods is association rule analysis, which represents co-occurrence of items or events. Association rules are commonly used in market basket analysis. An association rule is in the form of X → Y and it shows that X and Y co-occur with a given level of support and confidence. Association rule mining is a common technique used in discovering interesting frequent patterns in large datasets acquired in various application domains. Having petabytes of data finding its way into data storages in perhaps every day, made many researchers look for efficient methods for analyzing these large datasets. Many algorithms have been proposed for searching for frequent patterns. The search space combinatorically explodes as the size of the source data increases. Simply using more powerful computers, or even super-computers to handle ever-increasing size of large data sets is not sufficient. Hence, incremental algorithms have been developed and used to improve the efficiency of frequent pattern mining. One of the challenges of frequent itemset mining is long running times of the algorithms. Two major costs of long running times of frequent itemset mining are due to the number of database scans and the number of candidates generated (the latter one requires memory, and the more the number of candidates there are the more memory space is needed. When the candidates do not fit in memory then page swapping will occur which will increase the running time of the algorithms). In this dissertation we propose a new implementation of Apriori algorithm, NCLAT (Near Candidate-less Apriori with Tidlists), which scans the datab

关键词： Computer science  

摘要： Interactive narrative is becoming increasingly popular for entertainment, such as video games and interactive TV, as well as high impact domains such as education, training and health. Designing complex storytelling experiences is a considerable challenge, even for experts. Iterative design is a common design method used across academia and industry that relies on repeatedly building and testing scenarios, using various formative evaluation methods. These testing methods, however, require human playtesters, making the process both time-consuming and resource demanding. Further, our community has yet to develop a way to communicate, evaluate, and compare interactive narratives. In this dissertation, I present a new model for describing and communicating interactive narrative design called Progression Model, which captures the narratives structure from a users’ experience perspective. Further, I present a novel model capturing progression and moment-to-moment interaction in a graph-based representation called Progression Maps. Moreover, I present a new automated system, called Design Assistant, that develops a graph-based visualization of progression in interactive narratives. Results from various studies show the success of the use of Progression Maps and the automatically generated Design Assistant graphs. Specifically, the results show that the models and graphs are suitable for novice designers to communicate about their designs; they are easy to understand and suitable for qualitative and quantitative analysis of interactive narrative design.