Computer Sciences Commons^™

An Empirical Assessment Of Audio/Visual/Haptic Alerts And Warnings To Mitigate Risk Of Phishing Susceptibility In Emails On Mobile Devices, Molly Marie Cooper

CCAC Theses and Dissertations

Phishing emails present a threat to both personal and organizational data. Phishing is a cyber-attack using social engineering. About 94% of cybersecurity incidents are due to phishing and/or social engineering. A significant volume of prior literature documented that users are continuing to click on phishing links in emails, even after phishing awareness training. It appears there is a strong need for creative ways to alert and warn users to signs of phishing in emails.

The main goal of the experiments in this study was to measure participants’ time for recognizing signs of phishing in emails, thus, reducing susceptibility to phishing …

Sns As An Educational Tool: Effect On Academic Performance And Learners’ Perceptions, Nawwaf Mohssen Altalhi

CCAC Theses and Dissertations

With Social Networking Sites (SNSs) being extensively used by students, there has been extensive research in relation to their ability to enhance students’ academic performance in various learning environments, although the advent of research on online learning is a recent development.

Studies regarding the use of SNSs indicated that there was a negative relationship between students’ use of SNSs and students’ academic performance. However, it is unknown whether the implementation of an instructional training course utilizing SNSs as an educational tool might lead to improvements in students’ academic performance. Many students have admitted to not knowing how to properly use …

A Hierarchical Temporal Memory Sequence Classifier For Streaming Data, Jeffrey Barnett

CCAC Theses and Dissertations

Real-world data streams often contain concept drift and noise. Additionally, it is often the case that due to their very nature, these real-world data streams also include temporal dependencies between data. Classifying data streams with one or more of these characteristics is exceptionally challenging. Classification of data within data streams is currently the primary focus of research efforts in many fields (i.e., intrusion detection, data mining, machine learning). Hierarchical Temporal Memory (HTM) is a type of sequence memory that exhibits some of the predictive and anomaly detection properties of the neocortex. HTM algorithms conduct training through exposure to a stream …

An Approach To Twitter Event Detection Using The Newsworthiness Metric, Jonathan Adkins

CCAC Theses and Dissertations

No abstract provided.

Detecting Rogue Manipulation Of Smart Home Device Settings, David Zeichick

CCAC Theses and Dissertations

Smart home devices control a home’s environmental and security settings. This includes devices that control home thermostats, sprinkler systems, light bulbs, and home appliances. Malicious manipulation of the settings of these devices by an outside adversary has caused emotional distress and could even cause physical harm. For example, researchers have reported that there is a rise in domestic abuse perpetrated via smart home devices; victims have reported their thermostat settings being unwittingly manipulated and being locked out of their house due to their smart lock code being changed. Rapid adoption of smart home devices by consumers has led to an …

Unix Administrator Information Security Policy Compliance: The Influence Of A Focused Seta Workshop And Interactive Security Challenges On Heuristics And Biases, John Palmer Mcconnell

CCAC Theses and Dissertations

Information Security Policy (ISP) compliance is crucial to the success of healthcare organizations due to security threats and the potential for security breaches. UNIX Administrators (UXAs) in healthcare Information Technology (IT) maintain critical servers that house Protected Health Information (PHI). Their compliance with ISP is crucial to the confidentiality, integrity, and availability of PHI data housed or accessed by their servers. The use of cognitive heuristics and biases may negatively influence threat appraisal, coping appraisal, and ultimately ISP compliance behavior. These failures may result in insufficiently protected servers and put organizations at greater risk of data breaches and financial loss. …

The Social Media Machines: An Investigation Of The Effect Of Trust Moderated By Disinformation On Users’ Decision-Making Process, Zulma Valedon Westney

CCAC Theses and Dissertations

Social media networking sites (SMNS) have become a popular communications medium where users share information, knowledge, and persuasion. In less than two decades, social media's (SM) dominance as a communication medium can't be disputed, for good or evil. Combined with the newly found immediacy and pervasiveness, these SM applications' persuasive power are useful weapons for organizations, angry customers, employees, actors, and activists bent on attacking or hacking other individuals, institutions, or systems. Consequently, SM has become the preferred default mechanism of news sources; however, users are unsure if the information gathered is true or false. According to the literature, SMNS …

Protecting The Protector: Mapping The Key Terrain That Supports The Continuous Monitoring Mission Of A Cloud Cybersecurity Service Provider, Chris Bush

CCAC Theses and Dissertations

Key terrain is a concept that is relevant to warfare, military strategy, and tactics. A good general maps out terrain to identify key areas to protect in support of a mission (i.e., a bridge allowing for mobility of supplies and reinforcements). Effective ways to map terrain in Cyberspace (KT-C) has been an area of interest for researchers in Cybersecurity ever since the Department of Defense designated Cyberspace as a warfighting domain. The mapping of KT-C for a mission is accomplished by putting forth efforts to understand and document a mission's dependence on Cyberspace and cyber assets. A cloud Cybersecurity Service …

A Novel S-Box-Based Postprocessing Method For True Random Number Generation, Erdi̇nç Avaroğlu, Taner Tuncer

Turkish Journal of Electrical Engineering and Computer Sciences

The quality of randomness in numbers generated by true random number generators (TRNGs) depends on the source of entropy. However, in TRNGs, sources of entropy are affected by environmental changes and this creates a correlation between the generated bit sequences. Postprocessing is required to remove the problem created by this correlation in TRNGs. In this study, an S-box-based postprocessing structure is proposed as an alternative to the postprocessing structures seen in the published literature. A ring oscillator (RO)-based TRNG is used to demonstrate the use of an S-box for postprocessing and the removal of correlations between number sequences. The statistical …

Harmonic Effects Optimization At A System Level Using A Harmonic Power Flowcontroller, Reza Mehri, Hossein Mokhtari

Turkish Journal of Electrical Engineering and Computer Sciences

Increase of nonlinear loads in industries has resulted in high levels of harmonic currents and consequently harmonic voltages in power networks. Harmonics have several negative effects such as higher energy losses and equipment life reduction. To reduce the levels of harmonics in power networks, different methods of harmonic suppression have been employed. The basic idea in all of these methods is to prevent harmonics from flowing into a power network at customer sides and the point of common coupling (PCC). Due to the costs, none of the existing mitigating methods result in a harmonic-free power system. The remaining harmonic currents, …

Adaptive Batch Size Selection In Active Learning For Regression, Anthony L. Faulds

CCAC Theses and Dissertations

Training supervised machine learning models requires labeled examples. A judicious choice of examples is helpful when there is a significant cost associated with assigning labels. This dissertation aims to improve upon a promising extant method - Batch-mode Expected Model Change Maximization (B-EMCM) method - for selecting examples to be labeled for regression problems. Specifically, it aims to develop and evaluate alternate strategies for adaptively selecting batch size in B-EMCM, named adaptive B-EMCM (AB-EMCM).

By determining the cumulative error that occurs from the estimation of the stochastic gradient descent, a stop criteria for each iteration of the batch can be specified …

You Might Be A Robot, Bryan Casey, Mark A. Lemley

Cornell Law Review

As robots and artificial intelligence (Al) increase their influence over society, policymakers are increasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots arid AI-not even experts. What's more, technological advances make it harder and harder each day to tell people from robots and robots from "dumb" machines. We have already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you are reading this you are (probably) not …

A Pcnn Framework For Blood Cell Image Segmentation, Carol D. Lenihan

CCAC Theses and Dissertations

This research presents novel methods for segmenting digital blood cell images under a Pulse Coupled Neural Network (PCNN) framework. A blood cell image contains different types of blood cells found in the peripheral blood stream such as red blood cells (RBCs), white blood cells (WBCs), and platelets. WBCs can be classified into five normal types – neutrophil, monocyte, lymphocyte, eosinophil, and basophil – as well as abnormal types such as lymphoblasts and others. The focus of this research is on identifying and counting RBCs, normal types of WBCs, and lymphoblasts. The total number of RBCs and WBCs, along with classification …

Towards Practical Modulation Recognition For Future Spectrum-Sharing Applications, Wei Xiong

Legacy Theses & Dissertations (2009 - 2024)

With recent advances in emerging Dynamic Spectrum Access (DSA) and Cognitive Radio technologies, modulation recognition (ModRec) has emerged as a critical problem with importance to spectrum-sharing applications. Existing approaches, target modulation recognition as if a packet will be decoded in full and thus, pose stringent requirements on spectrum sensing and transmitter behavior: (i) a transmitter's bandwidth should be scanned alone and in full, (ii) for MIMO ModRec, the sensor should have at least same as many antennas as the transmitter, (iii) modulation symbol representation should be uniform and (iv) prior knowledge of the transmitter's technology should be available. These stringent …

Sequentially-Closed And Forward-Closed String Rewriting Systems, Yu Zhang

Legacy Theses & Dissertations (2009 - 2024)

In this dissertation we introduce the new concept of sequentially-closed string rewriting systems which generalizes forward-closed string rewriting systems and monadic string rewriting systems. We also investigate subclasses and properties of finite and regular sequentially-closed systems and forward-closed systems.

Detecting And Protecting Against Ai-Synthesized Faces, Yuezun Li

Legacy Theses & Dissertations (2009 - 2024)

The recent advances in deep learning and the availability of vast volume of online personal images and videos have drastically improved the reality of synthesized faces in images and videos. While there are interesting and creative applications of the AI face synthesis systems, they can also be weaponized, as it can create the illusions of a person's presence and activities that do not occur in reality, which results in serious political, social, financial, and legal consequences. Therefore, it is of great importance to develop effective method to expose the AI-synthesized faces. In this thesis, a set of our recent efforts …

Invariant-Based Online Software Anomaly Detection And Selective Regression Testing, Yizhen Chen

Legacy Theses & Dissertations (2009 - 2024)

Software has been extensively used in various domains to provide online services. With the growing popularity of these types of applications, the quality of the software has a great impact on many of our daily activities [1]. Reliable software executions that deliver expected outcomes are essential for quality services. Software is considered abnormal when its behavior deviates from what is expected at any point during its execution. When anomalous behavior propagates to an exit point of the software and produces an incorrect output or an unexpected termination of the execution, it is considered a software failure. An anomaly may or …

Uncertainty Learning In Subjective Logic And Pattern Discovery In Network Data, Adilijiang Alimu

Legacy Theses & Dissertations (2009 - 2024)

Uncertainty caused by unreliable or insufficient data and vulnerable machine learning models

Discriminative Factorization Models For Student Behavioral Pattern Detection And Classification, Mehrdad Mirzaei

Legacy Theses & Dissertations (2009 - 2024)

The goal of this dissertation is to examine factors such as how a student chooses to engage with the online platform and time spent on individual tasks and draw conclusions to improve the efficiency of the students and efficacy of online learning tools. Student activities and decision-making while functioning in a computer-based learning environment are utilized to guide students with effective patterns in studying. In addition to the sequence of actions, we have considered the time spent on each activity in modeling to have a more accurate representation of students' behavior in studying. Using sequential pattern mining methods, we find …

Field-Of-View Optimization Of Magnetically Actuated 2d Gimballed Scanners, Gökçe Aköz, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents the field of view (FOV) maximization of a magnetically actuated two-dimensional (2D) gimballed scanner. The process of maximization is completed in two steps. (1) Optimization of the electrocoil providing the magnetic force that moves the scanner and (2) precise choice of optimum respective locations of both the scanner and the electrocoil. We first derived a formula relating the generated magnetic flux density, coil design parameters and driving voltage. Subsequently, we discussed the design trade-offs of an actuating electrocoil. We also conducted several experiments on a stainless steel 430 scanner having a footprint of 15 mm × 15 …

Exploring The Power Of Supervised Learning Methods For Company Name Disambiguation In Microblog Posts, Nafi̇ye Polat, Ali̇ Çakmak, Rabi̇a Turan

Turkish Journal of Electrical Engineering and Computer Sciences

Twitter is an online social networking website where people can post short messages on any subject, and these messages become visible to other users. Users intentionally express their opinions about companies or products via microblogging texts. Analyzing such messages might help explore what customers think about company products, or what the broad feelings of customers are. Identifying tweets referring to products and companies is becoming an important tool recently. However, company names are often vague. Hence, the first step is to locate the messages that are relevant to a company. In this paper, we present a number of supervised learning …

Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose

Turkish Journal of Electrical Engineering and Computer Sciences

Cognitive Radio Sensor Network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here, the concept of Dynamic Spectrum Access (DSA) denes the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the Primary User (PU) has the license to access the spectrum band. On the other hand, the Secondary User (SU) tries to access the unused spectrum eciently, by not disturbing the PU. Considering that issue, this study introduces a …

Reconfiguration-Based Hierarchical Energy Management In Multimicrogrid Systems Considering Power Losses, Reliability Index, And Voltage Enhancement, Farid Hamzeh Aghdam, Navid Taghizadegan Kalantari, Sajad Najafi Ravadanegh

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a reconfiguration-based hierarchical energy management for interconnected microgrids known as multimicrogrid system. The goal is to minimize the operational costs of different entities alongside with finding the best topology to minimize the active power loss, enhance reliability index, and improve the voltage level. The distribution network (DN) includes several dispatchable and undispatchable distributed energy resources, energy storage devices, and multiple microgrids (MGs). The first layer of the optimization process is executed by each MG operator and each MG performs local energy management. Each MG operator informs the DN operator about its optimal schedules. Finally, global energy management …

An Encrypted Speech Authentication Method Based On Uniform Subband Spectrumvariance And Perceptual Hashing, Qiuyu Zhang, Denghai Zhang, Liang Zhou

Turkish Journal of Electrical Engineering and Computer Sciences

In a real-world cloud server, a speech signal is prone to suffer various attacks, such as malicious muting and tampering. In such a context, the privacy security of the speech owner will not be guaranteed. In order to achieve content authentication of encrypted speech in the cloud server, an efficient encrypted speech authentication method based on uniform subband spectrum variance and perceptual hashing is proposed. Firstly, the original speech is scrambled by Henon mapping to construct an encrypted speech library in the cloud, through extracting uniform subband spectrum variance of the encrypted speech and constructing a hashing sequence to generate …

Low Power And Low Phase Noise Vco With Dual Current Shaping For Iotapplications, Sajad Nejadhasan, Narges Moazenian, Ebrahim Abiri, Mohammah Reza Salehi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, two low phase noise and power consumption VCO circuits, which are suitable for Internet of things (IoT) applications, are proposed. In the first structure, in order to have more control of the current consumption, the current shaping technique is used in the PMOS and NMOS biasing circuit. In the second structure, for increasing the oscillation amplitude and reducing the phase noise, independent biasing for the NMOS section is used. In both structures, to increase the frequency tuning range (FTR), without using a capacitor bank, the varactor is used in the biasing structure. In the first structure the …

Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar

Turkish Journal of Electrical Engineering and Computer Sciences

The performance of cross-correlation functions can decrease computational complexity under optimal fingerprint feature selection. In this paper, a technique is proposed to perform alignment of fingerprints followed by their matching in fewer computations. Minutiae points are extracted and alignment is performed on the basis of their spatial locations and orientation fields. Unlike traditional cross-correlation based matching algorithms, ridges are not included in the matching process to avoid redundant computations. However, optimal cross-correlation is chosen by correlating feature vectors accompanying x-y locations of minutiae points and their aligned orientation fields. As a result, matching time is significantly reduced with much improved …

Efficient Bandwidth Management Algorithm For Ng-Epon, Ammar Rafiq, Muhammad Faisal Hayat

Turkish Journal of Electrical Engineering and Computer Sciences

Next generation ethernet passive optical network (NG-EPON) is a promising technology to cater huge bandwidth and efficient distribution demands of the future Internet services. IEEE working group has been doing efforts for the standardization of NG-EPON. Four wavelength channels of 25Gbps each are supported by NG-EPON for the transmission of optical network unit (ONU) traffic towards optical line terminal (OLT). Dynamic wavelength and bandwidth allocation (DWBA) algorithms are needed for the efficient arbitration of bandwidth resources between subscribers. In this paper, we have proposed a DWBA algorithm named as efficient bandwidth management algorithm (EBMA) for NG-EPON. EBMA has been designed …

Construction And Performance Analysis Of A New Sac-Ocdma Code Based Onlatin Square Matrix, Amel Aissaoui, Latifa Hacini

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a family of novel spreading code called Latin square code (LSC) is proposed for spectral amplitude coding-optical code division multiple access (SAC-OCDMA) system. The main feature of the proposed code is the zero cross-correlation which eliminates both multiple access interference (MAI) and phase induced intensity noise (PIIN). The code construction can be easily accomplished using Latin square matrix (LSM) for any weight and number of users. The simplicity in the construction code has made it a compelling candidate for future OCDMA applications. SAC-OCDMA system employing direct decoding is mathematically analyzed and then numerically simulated using Matlab and …

An Efficient Storage-Optimizing Tick Data Clustering Model, Haleh Amintoosi, Masood Niazi Torshiz, Yahya Forghani, Sara Alinejad

Turkish Journal of Electrical Engineering and Computer Sciences

Tick data is a large volume of data, related to a phenomenon such as stock market or weather change, with data values changing rapidly over time. An important issue is to store tick data table in a way that it occupies minimum storage space while at the same time it can provide fast execution of queries. In this paper, a mathematical model is proposed to partition tick data tables into clusters with the aim of minimizing the required storage space. The genetic algorithm is then used to solve the mathematical model which is indeed a clustering model. The proposed method …

Modelling Sensor Ontology With The Sosa/Ssn Frameworks:A Case Study For Laboratory Parameters, Özlem Aktaş, Mehmet Mi̇lli̇, Sanaz Lakestani̇, Musa Mi̇lli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, the use of sensor-based systems in many areas has led to an exponential increase in the raw sensor data. However, the lack of neither syntactic nor semantic integrity between these sensor data limited their sharing, reusability, and interpretation. These inabilities can cause some problems. For example, different wireless sensor networks may not work together due to the subtle variations in their sensing methods, operating systems, syntax, and data structure. In recent years, to cope with these inabilities, the semantic sensor web approach, which enables us to enrich the meaning of sensor data, has been seen as the critical technology …