Physical Sciences and Mathematics Commons^™

Blockchain Based Access Control For Enterprise Blockchain Applications, Lei Xu, Isaac Markus, Subhod I, Nikhil Nayab

Computer Science Faculty Publications and Presentations

Access control is one of the fundamental security mechanisms of IT systems. Most existing access control schemes rely on a centralized party to manage and enforce access control policies. As blockchain technologies, especially permissioned networks, find more applicability beyond cryptocurrencies in enterprise solutions, it is expected that the security requirements will increase. Therefore, it is necessary to develop an access control system that works in a decentralized environment without compromising the unique features of a blockchain. A straightforward method to support access control is to deploy a firewall in front of the enterprise blockchain application. However, this approach does not …

Kcrs: A Blockchain-Based Key Compromise Resilient Signature System, Lei Xu, Lin Chen, Zhimin Gao, Xinxin Fan, Kimberly Doan, Shouhuai Xu, Weidong Shi

Computer Science Faculty Publications and Presentations

Digital signatures are widely used to assure authenticity and integrity of messages (including blockchain transactions). This assurance is based on assumption that the private signing key is kept secret, which may be exposed or compromised without being detected in the real world. Many schemes have been proposed to mitigate this problem, but most schemes are not compatible with widely used digital signature standards and do not help detect private key exposures. In this paper, we propose a Key Compromise Resilient Signature (KCRS) system, which leverages blockchain to detect key compromises and mitigate the consequences. Our solution keeps a log of …

Learning To Detect Pedestrians By Watching Videos, Andrew Y. Chen

Theses and Dissertations

The field of deep learning has experienced a resurgence in the recent years, particularly resulting with the advent of AlexNet. Supervised learning is currently the most common and practical machine learning method. The struggle with employing supervised learning to approach problems is that it requires training data. Sufficient training data is correlated with performance for deep learning models. The issue is that preparing the training data can be a tedious and labor intensive task, especially on a large scale. The purpose of this paper is to determine how efficient a machine can learn when trained on automatically annotated data. The …

Comparison Of Rl Algorithms For Learning To Learn Problems, Adolfo Gonzalez Iii

Theses and Dissertations

Machine learning has been applied to many different problems successfully due to the expressiveness of neural networks and simplicity of first order optimization algorithms. The latter being a vital piece needed for training large neural networks efficiently. Many of these algorithms were produced with behavior produced by experiments and intuition. An interesting question that comes to mind is that rather than observing and then designing algorithms with beneficial behaviors, can these algorithms be learned through a reinforcement learning by modeling optimization as a game. This paper explores several reinforcement learning algorithms which are applied to learn policies suited for optimization.

Detecting Phone-Related Pedestrian Behavior Using A Two-Branch Convolutional Neural Network, Humberto Saenz

Theses and Dissertations

With the wide use of smart phones, distraction has become a major safety concern to roadway users. The distracted phone-use behaviors among pedestrians, like Texting, Game Playing and Phone Calls, have caused increasing fatalities and serious injuries. With the increasing usage of driver monitor systems on intelligent vehicles, distracted driver behaviors can be efficiently detected and warned. However, the research of phone-related distracted behavior by pedestrians has not been systemically studied. It is desired to improve both the driving and pedestrian safety by automatically discovering the phone-related pedestrian distracted behaviors. In this thesis, we propose a new computer vision-based method …

An Accelerated Hierarchical Approach For Object Shape Extraction And Recognition, Mahmoud K. Quweider, Bassam Arshad, Hansheng Lei, Liyu Zhang, Fitratullah Khan

Computer Science Faculty Publications and Presentations

We present a novel automatic supervised object recognition algorithm based on a scale and rotation invariant Fourier descriptors algorithm. The algorithm is hierarchical in nature to capture the inherent intra-contour spatial relationships between the parent and child contours of an object. A set of distance metrics are introduced to go along with the hierarchical model. To test the algorithm, a diverse database of shapes is created and used to train standard classification algorithms, for shape-labeling. The implemented algorithm takes advantage of the multi-threaded architecture and GPU efficient image-processing functions present in OpenCV wherever possible, speeding up the running time and …

Safedb: Spark Acceleration On Fpga Clouds With Enclaved Data Processing And Bitstream Protection, Han-Yee Kim, Rohyoung Myung, Boeui Hong, Heonchang Yu, Taeweon Suh, Lei Xu, Weidong Shi

Computer Science Faculty Publications and Presentations

This paper proposes SafeDB: Spark Acceleration on FPGA Clouds with Enclaved Data Processing and Bitstream Protection. SafeDB provides a comprehensive and systematic hardware-based security framework from the bitstream protection to data confidentiality, especially for the cloud environment. The AES key shared between FPGA and client for the bitstream encryption is generated in hard-wired logic using PKI and ECC. The data security is assured by the enclaved processing with encrypted data, meaning that the encrypted data is processed inside the FPGA fabric. Thus, no one in the system is able to look into clients' data because plaintext data are not exposed …

A Novel Method For Intelligent Single Fault Detection Of Bearings Using Sae And Improved D–S Evidence Theory, Jianguang Lu, Huan Zhang, Xianghong Tang

Computer Science Faculty Publications and Presentations

In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this paper proposes a method based on features self-extraction of a Sparse Auto-Encoder (SAE) and results fusion of improved Dempster–Shafer evidence theory (D–S). Multi-fault signal compression features of bearings were extracted by SAE on multiple vibration sensors’ data. Data sets were constructed by the extracted compression features to train the Support Vector Machine (SVM) according to the rule of single fault detection (R-SFD) this paper proposed. Fault detection results were obtained by the improved D–S evidence theory, …

A Holistic Approach For Enhancing Distributed Education With Multi-Campus Course Delivery Methods, Mahmoud K. Quweider, Ala Qubbaj, Liyu Zhang, Fitratullah Khan, Hansheng Lei

Computer Science Faculty Publications and Presentations

To create an emerging research institution, a regional university was created that spans multiple campuses within a radius of more than one hundred miles by merging at least three current institutions. The merge allowed the university to pool its human and technical resources. Students can now pursue new degrees that were not available before at one campus or another, take a newly available technical or specialty courses, and even select their own preferred professor when a course is offered by many faculty. In order to serve students at multiple campuses that are geographically far a part, the university instituted policies …

Optimal Staged Self-Assembly Of Linear Assemblies, Cameron Chalk, Eric Martinez, Robert Schweller, Luis Vega, Andrew Winslow, Tim Wylie

Computer Science Faculty Publications and Presentations

We analyze the complexity of building linear assemblies, sets of linear assemblies, and O(1)-scale general shapes in the staged tile assembly model. For systems with at most b bins and t tile types, we prove that the minimum number of stages to uniquely assemble a 1 n line is (logt n + logb n t + 1). Generalizing to O(1) n lines, we prove the minimum number of stages is O( log n tb t log t b2 + log log b log t ) and

( log n tb t log t b2 ). Next, we consider assembling sets …

Mobile Solar Energy Environmental Control System With Remote Accessibility, Luis S. Garay

Theses and Dissertations

The proposed system, Mobile Solar Energy Environmental Control System with Remote Accessibility (mSEECS w/ RA), is based on the utilization of an already available Energy Storage Unit (ESU) in a Transport Unit System (TUS) to harness solar energy to provide a system to enhance the environment, safety and security of a TUS in a stationary or a mobile state by monitoring and controlling the operation of its onboard systems, and provide remote accessibility to know the state of affairs at any time. To relate to a real world application, the battery (ESU) of a vehicle (TUS) is underutilized …

Cophosk: A Method For Comprehensive Kinase Substrate Annotation Using Co-Phosphorylation Analysis, Marzieh Ayati, Danica Wiredja, Daniela Schlatzer, Sean Maxwell, Ming Li, Mehmet Koyutürk, Mark R. Chance

Computer Science Faculty Publications and Presentations

We present CoPhosK to predict kinase-substrate associations for phosphopeptide substrates detected by mass spectrometry (MS). The tool utilizes a Naïve Bayes framework with priors of known kinase-substrate associations (KSAs) to generate its predictions. Through the mining of MS data for the collective dynamic signatures of the kinases’ substrates revealed by correlation analysis of phosphopeptide intensity data, the tool infers KSAs in the data for the considerable body of substrates lacking such annotations. We benchmarked the tool against existing approaches for predicting KSAs that rely on static information (e.g. sequences, structures and interactions) using publically available MS data, including breast, colon, …

Randomized Parameterized Algorithms For The Kidney Exchange Problem, Mugang Lin, Jianxin Wang, Qilong Feng, Bin Fu

Computer Science Faculty Publications and Presentations

In order to increase the potential kidney transplants between patients and their incompatible donors, kidney exchange programs have been created in many countries. In the programs, designing algorithms for the kidney exchange problem plays a critical role. The graph theory model of the kidney exchange problem is to find a maximum weight packing of vertex-disjoint cycles and chains for a given weighted digraph. In general, the length of cycles is not more than a given constant L (typically 2 L 5), and the objective function corresponds to maximizing the number of possible kidney transplants. In this paper, we study the …

Digital Transformation Through Internet Of Things Services, Tayfun Keskin, Frederick J. Riggins

Information Systems Faculty Publications and Presentations

Internet of Things (IoT) have been disrupting industries through shifting novel services, and business models. Organizations should also redesign their business service models to navigate this disruption. A holistic understanding of digital transformation through IoT requires the cooperation of multiple disciplines ranging from engineering to economics. This paper utilizes a conceptual model to develop an analytical framework to investigate a number of pricing strategies enabled by different business models. Our findings demonstrate that the Internet of Things phenomenon has the potential to disrupt the way we do business by connecting markets and enabling new business models.

Full Tilt: Universal Constructors For General Shapes With Uniform External Forces, Jose Balanza-Martinez, Austin Luchsinger, David Caballero, Rene Reyes, Angel A. Cantu, Robert Schweller, Luis Angel Garcia, Tim Wylie

Computer Science Faculty Publications and Presentations

We investigate the problem of assembling general shapes and patterns in a model in which particles move based on uniform external forces until they encounter an obstacle. In this model, corresponding particles may bond when adjacent with one another. Succinctly, this model considers a 2D grid of “open” and “blocked” spaces, along with a set of slidable polyominoes placed at open locations on the board. The board may be tilted in any of the 4 cardinal directions, causing all slidable polyominoes to move maximally in the specified direction until blocked. By successively applying a sequence of such tilts, along with …

Elf3 Is An Antagonist Of Oncogenic-Signalling-Induced Expression Of Emt-Tf Zeb1, D Liu, Y Skomorovska, J Song, E Bowler, R Harris, R Ravasz, S Bai, Marzieh Ayati, K Tamai, Mehmet Koyuturk

Computer Science Faculty Publications and Presentations

Background: Epithelial-to-mesenchymal transition (EMT) is a key step in the transformation of epithelial cells into migratory and invasive tumour cells. Intricate positive and negative regulatory processes regulate EMT. Many oncogenic signalling pathways can induce EMT, but the specific mechanisms of how this occurs, and how this process is controlled are not fully understood.

Methods: RNA-Seq analysis, computational analysis of protein networks and large-scale cancer genomics datasets were used to identify ELF3 as a negative regulator of the expression of EMT markers. Western blotting coupled to siRNA as well as analysis of tumour/normal colorectal cancer panels was used to …