Urmil Shah, Brandon Hoang, Ryan Villanueva, K. George
{"title":"Focus Detection Using Spatial Release From Masking","authors":"Urmil Shah, Brandon Hoang, Ryan Villanueva, K. George","doi":"10.1109/CCWC47524.2020.9031273","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031273","url":null,"abstract":"Individuals are often subjected to environments where multiple conversations occur simultaneously. In these situations, most hearing-abled individuals are able to focus on the auditory stimulus of their choice by filtering out other present auditory stimuli. This ability is also referred to as ‘The Cocktail Party Effect’. Unfortunately, this ability is not yet applicable for people who use assistive listening devices or digital communications devices to communicate with more than one individual [1]. In this study, Spatial Release from Masking techniques are used within the context of its influence on Speech Intelligibility. A Brain-Computer Interface (BCI) system was used to take electroencephalogram (EEG) signals, through noninvasive methods, for machine learning classification training. The goal of using EEG signals to train a machine learning classifier is to find a model that can accurately predict if a subject is listening to a particular auditory stimulus in the presence of multiple auditory stimuli. A similar study has been conducted before but without the use of machine learning for data processing [2].","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"54 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114040279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"HID-SMART: Hybrid Intrusion Detection Model for Smart Home","authors":"Faisal Alghayadh, D. Debnath","doi":"10.1109/CCWC47524.2020.9031177","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031177","url":null,"abstract":"Smart homes become part of people's daily life. Many people happily attempt to monitor and control their smart homes by using a smartphone, tablet, or computer because smart home systems make residential living areas more comfortable and convenient. Many devices in home are now being connected to the Internet; these devices can easily become a target of attack and can cause serious problems that could affect a user's life. Some of these attacks are difficult to detect because attackers can be intelligent or they use the same protocols that are employed by users to do legitimate requests. An intrusion detection system (IDS) is designed to detect, and mitigate attacks on the network. However, various constraints on the smart home sensors and device manufacturers are not able to ensure the security and privacy of the wireless sensor networks by using one tier standard intrusion detection. Therefore, we propose a Hybrid Intrusion Detection (HID) system using a random forest algorithm and misuse detection.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115063206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shota Sakakura, K. Sanada, Hiroyuki Hatano, K. Mori
{"title":"Optimal Contention Window Based on Performance Analysis for Full Duplex WLANs","authors":"Shota Sakakura, K. Sanada, Hiroyuki Hatano, K. Mori","doi":"10.1109/CCWC47524.2020.9031252","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031252","url":null,"abstract":"Wireless full-duplex (FD) communication enables one to double the throughput of any link in theory. To achieve such benefits for FD wireless networks, it is very beneficial to develop medium access control (MAC) protocols for wireless FD networks. A backoff mechanism for FD MAC is designed based on distributed coordination function (DCF). In a fundamental backoff operation for FD MAC, nodes transmit data frames as a secondary transmitter even when they have not counted up their backoff timer to zero, which is the difference between the conventional DCF and FD MAC. By considering such operation, several theoretical models to analyze the FD networks have been developed. Whereas, there are few works for deriving the throughput maximization for FD MAC because the FD MAC operation makes the analysis complex and difficult. This paper presents an optimal CW for FD MAC based on theoretical performance analysis regarding FD wireless local area networks (FD WLANs), As an essential contribution in this paper, a theoretical expression for the optimal value of the initial contention window ($CW_{min}$) is derived, which gives the maximum throughput in networks, from the analytical model for FD MAC. By applying the derived optimal $CW_{min}$ in FD WLANs, the network throughput is improved significantly for any number of contention nodes.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115610727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Data Driven PID Control System","authors":"E. Yfantis, W. Culbreth","doi":"10.1109/CCWC47524.2020.9031230","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031230","url":null,"abstract":"Proportional, Integral, Derivative control systems are used in aviation, automotive industry, robotics, mechatronics and many other application areas. The proportional, integral, and derivative coefficients are defined deterministically in a generic way regardless of the process they control. In this research paper we compute these coefficients using mean square error analysis. The data used in the analysis, are produced by setting up proper experiments, using stratification, pre-sampling, experimental, design, sampling and finally computation of the coefficients. The method outlined in this research paper can be used in any control application where PID controllers are to be considered. The application emphasized in this paper is UAVs (Unmanned Air Vehicles), and cruise control in automobiles. Our Data driven PID system is modeled like a finite state machine. The PID coefficients are optimized separately for each state. A PID control system uses sensors to obtain the needed input from its environment, processors to process the input and decide which action is needed, and actuators to control the components of the system that is designed to control. The processors we use are FPGAs. The reason for that is because they make it easy to upgrade, debug, and improve the software driving the hardware.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123194685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Node Replacement Method for Disaster Resilient Wireless Sensor Networks","authors":"Alberto Gallegos Ramonet, Taku Noguchi","doi":"10.1109/CCWC47524.2020.9031271","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031271","url":null,"abstract":"In recent years, wireless sensor networks (WSN) have evolved from single-hop networks to complex multi-hop (mesh) networks. WSN nodes are finite resources that must be replaced periodically, either due to damage or because they have depleted their energy. When multiple nodes fail simultaneously, a replacement priority must be used to replace the most significant nodes first. In this paper, we propose a method to calculate a node replacement priority in multiple situations. Our method is designed to be used in WSN. Unlike traditional networks, WSN values their nodes not only on the amount of data they collect but also the size of the area their sensors can cover. Traditional node replacement approaches rarely consider these factors. Our method uses the sensor's coverage area to assign a priority to each node and determine its relevance in the network. This priority assignation considers not only the sensor coverage area of a single node, but also the aggregated sensors' coverage areas of multiple nodes. The proposed method is particularly useful when a multinode failure occurs (e.g. natural disasters) or when diagnostic and maintenance tasks are necessary.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123400979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laik Ruetten, Paulo Alexandre Regis, David Feil-Seifer, S. Sengupta
{"title":"Area-Optimized UAV Swarm Network for Search and Rescue Operations","authors":"Laik Ruetten, Paulo Alexandre Regis, David Feil-Seifer, S. Sengupta","doi":"10.1109/CCWC47524.2020.9031197","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031197","url":null,"abstract":"Intelligent robot swarms are increasingly being explored as tools for search and rescue missions. Efficient path planning and robust communication networks are critical elements of completing missions. The focus of this research is to give unmanned aerial vehicles (UAVs) the ability to self-organize a mesh network that is optimized for area coverage. The UAVs will be able to read the communication strength between themselves and all the UAVs it is connected to using RSSI. The UAVs should be able to adjust their positioning closer to other UAVs if RSSI is below a threshold, and they should also maintain communication as a group if they move together along a search path. Our approach was to use Genetic Algorithms in a simulated environment to achieve multi-node exploration with emphasis on connectivity and swarm spread.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123420264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shirin Nasr Esfahani, V. Muthukumar, E. Regentova, K. Taghva, M. Trabia
{"title":"Complex Food Recognition using Hyper-Spectral Imagery","authors":"Shirin Nasr Esfahani, V. Muthukumar, E. Regentova, K. Taghva, M. Trabia","doi":"10.1109/CCWC47524.2020.9031258","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031258","url":null,"abstract":"Developing a rapid and low-cost approach for automated food recognition is a necessity for applications such as dietary assessment to determine the caloric and nutritional food intake for short-term rehab and elderly care centers are very critical for the health care system. The main step in dietary assessment is not only to identify (classify) different components of the food but also to identify food cooked by different processes. Many researchers have focused their efforts on developing image-based learning techniques of food classification. Hyperspectral Imagery (HSI) allows for examining the spectral response of foods over a larger frequency spectrum. This paper presents the use of hyperspectral images for the detection of different foods in a meal. The hyperspectral data of food have been collected under a controlled illumination environment and food classified using SVM (Support Vector Machine) and Logistic Regression classifiers. We compare RGB and hyperspectral data classification on a set of common foods and present results.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122918497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Inductive and Deductive Reasoning to Assist in Cyber-Attack Prediction","authors":"E. Marin, Mohammed Almukaynizi, P. Shakarian","doi":"10.1109/CCWC47524.2020.9031154","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031154","url":null,"abstract":"Information about cyber-attack planning has been increasingly shared by malicious hackers online, making what was once a hard-to-penetrate market becomes accessible to a wider population. Although this trend helps to produce a huge amount of malware, it also provides intelligence for defenders since the shared information can be leveraged as precursors of cyber-attacks. In this work, we apply Annotated Probabilistic Temporal (APT) logic into the cybersecurity domain to accomplish two tasks: 1) induct APT rules that correlate malicious hacking activity with enterprise attacks to predict imminent cyber incidents; 2) leverage a deductive approach that combines attack predictions for more accurate security warnings. Results demonstrate considerable prediction gains in F1 score (up to 150.24%) compared to the baseline when the pre-conditions of APT rules include socio-personal indicators of the hackers behind cyber incidents, and when the predictions made for a given day are combined using deduction (up to 182.38%). Those findings highlight how AI tools can empower proactive cyber defense","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126149246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fausto Vega, Eric Hwang, L. Park, Brandon Chan, Paul Y. Oh
{"title":"Service Robot Navigation and Computer Vision Application in a Banquet Hall Setting","authors":"Fausto Vega, Eric Hwang, L. Park, Brandon Chan, Paul Y. Oh","doi":"10.1109/CCWC47524.2020.9031123","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031123","url":null,"abstract":"This paper describes a low computation system for a surveying service robot in a banquet hall setting. Automating this process will allow staff to focus on other tasks which will improve the overall efficiency of the event setup. The robot platform used was FURO, a two-wheeled service robot with an on board computer as well as a camera. Image processing algorithms were developed using the open source Open CV library to detect a total item count and ellipse tracker program. Potential fields was the navigation algorithm implemented to generate a collision free path towards the edge of the table. The results were successful as the computer vision algorithms worked 90% of the time in a controlled environment with a normal setup. It experienced failure when items were overlapping or too close to each other. Differences in lighting also came into effect when detecting the contents on the table. Nonetheless, this experiment presents a service robot application for table monitoring in a ballroom.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128656759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Pei, Xuefeng Li, Xiaochuan Wu, Liang Sun, Yixin Cao
{"title":"UDPP: Blockchain based Open Platform as a Privacy Enabler","authors":"Xin Pei, Xuefeng Li, Xiaochuan Wu, Liang Sun, Yixin Cao","doi":"10.1109/CCWC47524.2020.9031142","DOIUrl":"https://doi.org/10.1109/CCWC47524.2020.9031142","url":null,"abstract":"Data privacy has drawn a lot of attention from people in sectors of commerce, data processing and credit reporting, especially with the adoption of GDPR, CCPA, PIPA, GB/T35273 and ISO27701 etc. These regulations aim to give people the ownership of data they produce by law, however, due to the lack of standards, tools, and best practices, many enterprises struggle to adapt their workflow and database to ensure that the data processing is in compliance with the data owner's consent and suffer from heavy fines. In light of this challenge, we develop a blockchain based platform to enable both privacy preserving and privacy compliance. UDPP (User Data Privacy Protection) platform is constructed on an immutable blockchain system, including the compliance module and the privacy tool set. UDDP provides utilities and tools to make desensitization, encryption and self-check process easier. The compliance module can assist companies to self-check on the privacy policy as well as the data processing both in their apps and backend services, while the tool set provides multiple combinations of privacy protection schemes to solve different privacy preserving and user authorization cases. Moreover, UDPP will provide the user with a “token”, which represents the permissions of the data ownership. The token can be viewed as a privacy badge, and it records hash of all the data processing and storage infos as well as the update of user consents.","PeriodicalId":161209,"journal":{"name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130580548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}