OS and Networks Commons^™

Dial "N" For Nxdomain: The Scale, Origin, And Security Implications Of Dns Queries To Non-Existent Domains, Gunnan Liu, Lin Jin, Shuai Hao, Yubao Zhang, Daiping Liu, Angelos Stavrou, Haining Wang

Computer Science Faculty Publications

Non-Existent Domain (NXDomain) is one type of the Domain Name System (DNS) error responses, indicating that the queried domain name does not exist and cannot be resolved. Unfortunately, little research has focused on understanding why and how NXDomain responses are generated, utilized, and exploited. In this paper, we conduct the first comprehensive and systematic study on NXDomain by investigating its scale, origin, and security implications. Utilizing a large-scale passive DNS database, we identify 146,363,745,785 NXDomains queried by DNS users between 2014 and 2022. Within these 146 billion NXDomains, 91 million of them hold historic WHOIS records, of which 5.3 million …

Learning Dynamic Multimodal Implicit And Explicit Networks For Multiple Financial Tasks, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Many financial f orecasting d eep l earning w orks focus on the single task of predicting stock returns for trading with unimodal numerical inputs. Investment and risk management however involves multiple financial t asks - f orecasts o f expected returns, risks and correlations of multiple stocks in portfolios, as well as important events affecting different stocks - to support decision making. Moreover, stock returns are influenced by large volumes of non-stationary time-series information from a variety of modalities and the propagation of such information across inter-company relationship networks. Such networks could be explicit - observed co-occurrences in online …

Machine Learning-Based Event Generator For Electron-Proton Scattering, Y. Alanazi, P. Ambrozewicz, M. Battaglieri, A.N. Hiller Blin, M. P. Kuchera, Y. Li, T. Liu, R. E. Mcclellan, W. Melnitchouk, E. Pritchard, M. Robertson, N. Sato, R. Strauss, L. Velasco

Computer Science Faculty Publications

We present a new machine learning-based Monte Carlo event generator using generative adversarial networks (GANs) that can be trained with calibrated detector simulations to construct a vertex-level event generator free of theoretical assumptions about femtometer scale physics. Our framework includes a GAN-based detector folding as a fast-surrogate model that mimics detector simulators. The framework is tested and validated on simulated inclusive deep-inelastic scattering data along with existing parametrizations for detector simulation, with uncertainty quantification based on a statistical bootstrapping technique. Our results provide for the first time a realistic proof of concept to mitigate theory bias in inferring vertex-level event …

Learning Knowledge-Enriched Company Embeddings For Investment Management, Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Relationships between companies serve as key channels through which the effects of past stock price movements and news events propagate and influence future price movements. Such relationships can be implicitly found in knowledge bases or explicitly represented as knowledge graphs. In this paper, we propose KnowledgeEnriched Company Embedding (KECE), a novel multi-stage attentionbased dynamic network embedding model combining multimodal information of companies with knowledge from Wikipedia and knowledge graph relationships from Wikidata to generate company entity embeddings that can be applied to a variety of downstream investment management tasks. Experiments on an extensive set of real-world stock prices and news …

Estimating Homophily In Social Networks Using Dyadic Predictions, George Berry, Antonio Sirianni, Ingmar Weber, Jisun An, Michael Macy

Research Collection School Of Computing and Information Systems

Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors …

Covertnet: Circumventing Web Surveillance Using Covert Channels, Will C. Burghard

Senior Projects Fall 2019

Senior Project submitted to The Division of Science, Mathematics and Computing of Bard College.

Extension Of Cpe 454 Operating System, Joseph Nathaniel Arhar

Computer Science and Software Engineering

This project extended on the operating system I wrote in CPE 454 by adding additional features on top of the existing implementation. In order to implement them, I researched operating system design patterns and hardware details. I used wiki.osdev.org for most research, just like I did in CPE 454. The source code for the project is at https://github.com/josepharhar/jos.

Correcting Pedestrian Dead Reckoning With Monte Carlo Localization Boxed For Indoor Navigation, Akira T. Murphy

Honors Theses

Localization of phones is a ubiquitous part of the modern mobile electronics landscape. However, there are many situations where the current method of networked localization fails. A Pedestrian Dead Reckoning System where the location of the user is calculated by counting the steps and direction of the user was implemented as an iOS app with python for data analysis. A novel algorithm for wireless sensor localization using Ad-Hoc Bluetooth networks was proposed. A small experiment was performed proving that the system is nearly equal to state of the art algorithms.

Bandwidth Aggregation Across Multiple Smartphone Devices, Bradley R. Zeller

Master's Theses

Smartphones now account for the majority of all cell phones in use today [23]. Ubiquitous Internet access is a valuable feature offered by these devices and the vast majority of smartphone applications make use of the Internet in one way or another. However, the bandwidth offered by these cellular networks is often much lower than we typically experience on our standard home networks, leading to a less-than-optimal user experience. This makes it very challenging and frustrating to access certain types of web content such as video streaming, large file downloads, loading large webpages, etc.

Given that most modern smartphones are …

A Neural Network Approach To Border Gateway Protocol Peer Failure Detection And Prediction, Cory B. White

Master's Theses

The size and speed of computer networks continue to expand at a rapid pace, as do the corresponding errors, failures, and faults inherent within such extensive networks. This thesis introduces a novel approach to interface Border Gateway Protocol (BGP) computer networks with neural networks to learn the precursor connectivity patterns that emerge prior to a node failure. Details of the design and construction of a framework that utilizes neural networks to learn and monitor BGP connection states as a means of detecting and predicting BGP peer node failure are presented. Moreover, this framework is used to monitor a BGP network …

Studying The Performance Of A Firewall In Network Courses, José M. Garrido

Faculty and Research Publications

This paper presents a simple simulation model of a firewall to derive several performance metrics and briefly argues on the importance and value of modeling and simulation in courses that study various aspects of perimeter defense in network security.

The simulation model mentioned previously is part of an effort by faculty of our department to develop a multi-disciplinary repository of computational models that includes object-oriented discrete-event simulation models. One of the goals of this repository is to build resources that help educate students of computer science, software engineering, and information technology, in modeling and information security.

This and other network …

Designing A High-Quality Network: An Application-Oriented Approach, Sudheer Dharanikota

Computer Science Theses & Dissertations

As new computer network technologies emerge, the application designers and the application users expect an increasing level of quality of service from them. Hence, it is a common practice in the newer technologies to provide more Quality of Service (QoS) components. Until now, these QoS solutions have been both network-technology specific and network-oriented solutions. In this thesis, we present an application-oriented approach to design a high quality network which is independent of the underlying communication technology. In this thesis, we propose a QoS architecture to "provide predictable performance to the end-to-end application users in a high quality networking environment." In …