Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Blockchain (2)
- Renewable energy (2)
- Adaptive network (1)
- Bitcoin (1)
- Bootstrapping (1)
-
- Bug bounty (1)
- Classification (1)
- Cloud computing (1)
- Competitive analysis (1)
- Complemented BLP and Biba Model (1)
- Constant-space algorithm (1)
- Cryptocurrency (1)
- DApps (1)
- DDoS attacks (1)
- Data centers (1)
- Data coloring access control (1)
- Data locality (1)
- Database clustering (1)
- Decentralized apps (1)
- Decision Trees (1)
- Deep data locality (1)
- Deep learning (1)
- Dynamic networks (1)
- Empirical recurrence rates (1)
- Empirical recurrence rates ratios (1)
- Encryption (1)
- Energy efficiency (1)
- Energy-efficiency (1)
- Green computing (1)
- Green energy (1)
Articles 1 - 15 of 15
Full-Text Articles in Physical Sciences and Mathematics
Evaluation Of Continuous Power-Down Schemes, James Andro-Vasko, Wolfgang Bein
Evaluation Of Continuous Power-Down Schemes, James Andro-Vasko, Wolfgang Bein
Computer Science Faculty Research
We consider a power-down system with two states—“on” and “off”—and a continuous set of power states. The system has to respond to requests for service in the “on” state and, after service, the system can power off or switch to any of the intermediate power-saving states. The choice of states determines the cost to power on for subsequent requests. The protocol for requests is “online”, which means that the decision as to which intermediate state (or the off-state) the system will switch has to be made without knowledge of future requests. We model a linear and a non-linear system, and …
A Survey On Securing Iot Ecosystems And Adaptive Network Vision, Tejaswini Goli, Yoohwan Kim
A Survey On Securing Iot Ecosystems And Adaptive Network Vision, Tejaswini Goli, Yoohwan Kim
Computer Science Faculty Research
The rapid growth of Internet-of-Things (IoT) devices and the large network of interconnected devices pose new security challenges and privacy threats that would put those devices at high risk and cause harm to the affiliated users. This paper emphasizes such potential security challenges and proposes possible solutions in the field of IoT Security, mostly focusing on automated or adaptive networks. Considering the fact that IoT became widely adopted, the intricacies in the security field tend to grow expeditiously. Therefore, it is necessary for businesses to adopt new security protocols and to the notion of automated network security practices driven by …
Bountychain: Toward Decentralizing A Bug Bounty Program With Blockchain And Ipfs, Alex Hoffman, Phillipe Austria, Chol Hyun Park, Yoohwan Kim
Bountychain: Toward Decentralizing A Bug Bounty Program With Blockchain And Ipfs, Alex Hoffman, Phillipe Austria, Chol Hyun Park, Yoohwan Kim
Computer Science Faculty Research
Bug Bounty Programs (BBPs) play an important role in providing and maintaining security in software applications. These programs allow testers to discover and resolve bugs before the general public is aware of them, preventing incidents of widespread abuse. However, they have shown problems such as organizations providing accountability of reporting bugs and nonrecognition of testers. In this paper, we discuss Bountychain, a decentralized application using Ethereum-based Smart Contracts (SCs) and the Interplanetary File System (IPFS), a distributed file storage system. Blockchain and SCs provide a safe, secure and transparent platform for a BBP. Testers can submit bug reports and organizations …
Rethinking The Weakness Of Stream Ciphers And Its Application To Encrypted Malware Detection, William Stone, Daeyoung Kim, Victor Youdom Kemmoe, Mingon Kang, Junggab Son
Rethinking The Weakness Of Stream Ciphers And Its Application To Encrypted Malware Detection, William Stone, Daeyoung Kim, Victor Youdom Kemmoe, Mingon Kang, Junggab Son
Computer Science Faculty Research
One critical vulnerability of stream ciphers is the reuse of an encryption key. Since most stream ciphers consist of only a key scheduling algorithm and an Exclusive OR (XOR) operation, an adversary may break the cipher by XORing two captured ciphertexts generated under the same key. Various cryptanalysis techniques based on this property have been introduced in order to recover plaintexts or encryption keys; in contrast, this research reinterprets the vulnerability as a method of detecting stream ciphers from the ciphertexts it generates. Patterns found in the values (characters) expressed across the bytes of a ciphertext make the ciphertext distinguishable …
A Design Of Mac Model Based On The Separation Of Duties And Data Coloring: Dsdc-Mac, Soon-Book Lee, Yoo-Hwan Kim, Jin-Woo Kim, Chee-Yang Song
A Design Of Mac Model Based On The Separation Of Duties And Data Coloring: Dsdc-Mac, Soon-Book Lee, Yoo-Hwan Kim, Jin-Woo Kim, Chee-Yang Song
Computer Science Faculty Research
Among the access control methods for database security, there is Mandatory Access Control (MAC) model in which the security level is set to both the subject and the object to enhance the security control. Legacy MAC models have focused only on one thing, either confidentiality or integrity. Thus, it can cause collisions between security policies in supporting confidentiality and integrity simultaneously. In addition, they do not provide a granular security class policy of subjects and objects in terms of subjects' roles or tasks. In this paper, we present the security policy of Bell_LaPadula Model (BLP) model and Biba model as …
Hadoop Performance Analysis Model With Deep Data Locality, Sungchul Lee, Ju-Yeon Jo, Yoohwan Kim
Hadoop Performance Analysis Model With Deep Data Locality, Sungchul Lee, Ju-Yeon Jo, Yoohwan Kim
Computer Science Faculty Research
Background: Hadoop has become the base framework on the big data system via the simple concept that moving computation is cheaper than moving data. Hadoop increases a data locality in the Hadoop Distributed File System (HDFS) to improve the performance of the system. The network traffic among nodes in the big data system is reduced by increasing a data-local on the machine. Traditional research increased the data-local on one of the MapReduce stages to increase the Hadoop performance. However, there is currently no mathematical performance model for the data locality on the Hadoop. Methods: This study made the Hadoop performance …
Energy Efficiency And Renewable Energy Management With Multi-State Power-Down Systems, James Andro-Vasko, Wolfgang W. Bein, Hiro Ito
Energy Efficiency And Renewable Energy Management With Multi-State Power-Down Systems, James Andro-Vasko, Wolfgang W. Bein, Hiro Ito
Computer Science Faculty Research
A power-down system has an on-state, an off-state, and a finite or infinite number of intermediate states. In the off-state, the system uses no energy and in the on-state energy it is used fully. Intermediate states consume only some fraction of energy but switching back to the on-state comes at a cost. Previous work has mainly focused on asymptotic results for systems with a large number of states. In contrast, the authors study problems with a few states as well as systems with one continuous state. Such systems play a role in energy-efficiency for information technology but are especially important …
Self-Stabilizing Token Distribution With Constant-Space For Trees, Yuichi Sudo, Ajoy K. Datta, Lawrence L. Larmore, Toshimitsu Masuzawa
Self-Stabilizing Token Distribution With Constant-Space For Trees, Yuichi Sudo, Ajoy K. Datta, Lawrence L. Larmore, Toshimitsu Masuzawa
Computer Science Faculty Research
Self-stabilizing and silent distributed algorithms for token distribution in rooted tree networks are given. Initially, each process of a graph holds at most l tokens. Our goal is to distribute the tokens in the whole network so that every process holds exactly k tokens. In the initial configuration, the total number of tokens in the network may not be equal to nk where n is the number of processes in the network. The root process is given the ability to create a new token or remove a token from the network. We aim to minimize the convergence time, the number …
Loosely-Stabilizing Leader Election With Polylogarithmic Convergence Time, Yuichi Sudo, Fukuhito Ooshita, Hirotsugu Kukugawa, Toshimitsu Masuzawa, Ajoy K. Datta, Lawrence L. Larmore
Loosely-Stabilizing Leader Election With Polylogarithmic Convergence Time, Yuichi Sudo, Fukuhito Ooshita, Hirotsugu Kukugawa, Toshimitsu Masuzawa, Ajoy K. Datta, Lawrence L. Larmore
Computer Science Faculty Research
A loosely-stabilizing leader election protocol with polylogarithmic convergence time in the population protocol model is presented in this paper. In the population protocol model, which is a common abstract model of mobile sensor networks, it is known to be impossible to design a self-stabilizing leader election protocol. Thus, in our prior work, we introduced the concept of loose-stabilization, which is weaker than self-stabilization but has similar advantage as self-stabilization in practice. Following this work, several loosely-stabilizing leader election protocols are presented. The loosely-stabilizing leader election guarantees that, starting from an arbitrary configuration, the system reaches a safe configuration with a …
Mining Association Rules For Low-Frequency Itemsets, Jimmy Ming-Tai Wu, Justin Zhan, Sanket Chobe
Mining Association Rules For Low-Frequency Itemsets, Jimmy Ming-Tai Wu, Justin Zhan, Sanket Chobe
Computer Science Faculty Research
High utility itemset mining has become an important and critical operation in the Data Mining field. High utility itemset mining generates more profitable itemsets and the association among these itemsets, to make business decisions and strategies. Although, high utility is important, it is not the sole measure to decide efficient business strategies such as discount offers. It is very important to consider the pattern of itemsets based on the frequency as well as utility to predict more profitable itemsets. For example, in a supermarket or restaurant, beverages like champagne or wine might generate high utility (profit), but also sell less …
Deep Learning For Link Prediction In Dynamic Networks Using Weak Estimators, Carter Chiu, Justin Zhan
Deep Learning For Link Prediction In Dynamic Networks Using Weak Estimators, Carter Chiu, Justin Zhan
Computer Science Faculty Research
Link prediction is the task of evaluating the probability that an edge exists in a network, and it has useful applications in many domains. Traditional approaches rely on measuring the similarity between two nodes in a static context. Recent research has focused on extending link prediction to a dynamic setting, predicting the creation and destruction of links in networks that evolve over time. Though a difficult task, the employment of deep learning techniques have shown to make notable improvements to the accuracy of predictions. To this end, we propose the novel application of weak estimators in addition to the utilization …
Using Empirical Recurrence Rates Ratio For Time Series Data Similarity, Moinak Bhaduri, Justin Zhan
Using Empirical Recurrence Rates Ratio For Time Series Data Similarity, Moinak Bhaduri, Justin Zhan
Computer Science Faculty Research
Several methods exist in classification literature to quantify the similarity between two time series data sets. Applications of these methods range from the traditional Euclidean type metric to the more advanced Dynamic Time Warping metric. Most of these adequately address structural similarity but fail in meeting goals outside it. For example, a tool that could be excellent to identify the seasonal similarity between two time series vectors might prove inadequate in the presence of outliers. In this paper, we have proposed a unifying measure for binary classification that performed well while embracing several aspects of dissimilarity. This statistic is gaining …
Energy Saving In Data Centers, Wolfgang W. Bein
Energy Saving In Data Centers, Wolfgang W. Bein
Computer Science Faculty Research
Globally CO2 emissions attributable to Information Technology are on par with those resulting from aviation. Recent growth in cloud service demand has elevated energy efficiency of data centers to a critical area within green computing. Cloud computing represents a backbone of IT services and recently there has been an increase in high-definition multimedia delivery, which has placed new burdens on energy resources. Hardware innovations together with energy-efficient techniques and algorithms are key to controlling power usage in an ever-expanding IT landscape. This special issue contains a number of contributions that show that data center energy efficiency should be addressed from …
Dynamically Adjusting The Mining Capacity In Cryptocurrency With Binary Blockchain, Yoohwan Kim, Ju-Yeon Jo
Dynamically Adjusting The Mining Capacity In Cryptocurrency With Binary Blockchain, Yoohwan Kim, Ju-Yeon Jo
Computer Science Faculty Research
Many cryptocurrencies rely on Blockchain for its operation. Blockchain serves as a public ledger where all the completed transactions can be looked up. To place transactions in the Blockchain, a mining operation must be performed. However, due to a limited mining capacity, the transaction confirmation time is increasing. To mitigate this problem many ideas have been proposed, but they all come with own challenges. We propose a novel parallel mining method that can adjust the mining capacity dynamically depending on the congestion level. It does not require an increase in the block size or a reduction of the block confirmation …
Sutm System Api At Unlv: Small Uas Traffic Management System Api, Monetta Angelique Shaw, Ju-Yeon Jo, Yoohwan Kim
Sutm System Api At Unlv: Small Uas Traffic Management System Api, Monetta Angelique Shaw, Ju-Yeon Jo, Yoohwan Kim
Computer Science Faculty Research
This file contains the set of APIs for small unmanned aircraft systems (UAS) Traffic Management (sUTM). The sUTM server hosts a web service that allows any software or device that can use the Internet to utilize the server’s sUAS traffic management (sUTM) functions through these application programming interfaces (API). This library was developed as part of the MS thesis by Monetta Shaw in Spring 2016, "A web based solution for small unmanned aircraft systems (sUAS) traffic management". The summary of the library and its usage instructions are described in the thesis.