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Metadata-Driven Threat Classification Of Network Endpoints Appearing In Malware, Andrew G. West, Aziz Mohaisen 2014 SelectedWorks

Metadata-Driven Threat Classification Of Network Endpoints Appearing In Malware, Andrew G. West, Aziz Mohaisen

Andrew G. West

Networked machines serving as binary distribution points, C&C channels, or drop sites are a ubiquitous aspect of malware infrastructure. By sandboxing malcode one can extract the network endpoints (i.e., domains and URL paths) contacted during execution. Some endpoints are benign, e.g., connectivity tests. Exclusively malicious destinations, however, can serve as signatures enabling network alarms. Often these behavioral distinctions are drawn by expert analysts, resulting in considerable cost and labeling latency.

Leveraging 28,000 expert-labeled endpoints derived from ~100k malware binaries this paper characterizes those domains/URLs towards prioritizing manual efforts and automatic signature generation. Our analysis focuses ...


Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart 2014 University of Nebraska - Lincoln

Decaf: A New Event Detection Logic For The Purpose Of Fusing Delineated-Continuous Spatial Information, Kerry Q. Hart

Computer Science and Engineering: Theses, Dissertations, and Student Research

Geospatial information fusion is the process of synthesizing information from complementary data sources located at different points in space and time. Spatial phenomena are often measured at discrete locations by sensor networks, technicians, and volunteers; yet decisions often require information about locations where direct measurements do not exist. Traditional methods assume the spatial phenomena to be either discrete or continuous, an assumption that underlies and informs all subsequent analysis. Yet certain phenomena defy this dichotomy, alternating as they move across spatial and temporal scales. Precipitation, for example, appears continuous at large scales, but it can be temporally decomposed into discrete ...


Tweet Mapper Visualization Software, Andrew W. Nash, Shawn M. Cox, Michael T. Adams 2014 University of Tennessee, Knoxville

Tweet Mapper Visualization Software, Andrew W. Nash, Shawn M. Cox, Michael T. Adams

University of Tennessee Honors Thesis Projects

No abstract provided.


Capturing And Analyzing Network Traffic From Common Mobile Devices For Security And Privacy, Billy Overton 2014 East Tennessee State University

Capturing And Analyzing Network Traffic From Common Mobile Devices For Security And Privacy, Billy Overton

Undergraduate Honors Theses

Mobile devices such as tablets and smartphones are becoming more common, and they are holding more information. This includes private information such as contacts, financial data, and passwords. At the same time these devices have network capability with access to the Internet being a prime feature. Little research has been done in observing the network traffic produced by these mobile devices. To determine if private information was being transmitted without user knowledge, the mobile capture lab and a set of procedures have been created to observe, capture and analyze the network traffic produced by mobile devices. The effectiveness of the ...


Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, David Jia Wei Low, David Lo, Michael Finegold 2014 Singapore Management University

Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, David Jia Wei Low, David Lo, Michael Finegold

Research Collection School Of Information Systems

Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of different ads. To this end, we develop a Hierarchical Importance-aware Factorization Machine (HIFM), which provides an effective generic latent factor framework that incorporates importance weights and hierarchical ...


A Self-Adaptive Framework For Failure Avoidance In Configurable Software, Jacob Swanson 2014 University of Nebraska - Lincoln

A Self-Adaptive Framework For Failure Avoidance In Configurable Software, Jacob Swanson

Computer Science and Engineering: Theses, Dissertations, and Student Research

Many software systems today are highly-configurable, meaning the user can customize their instance of the application, adding and removing features as needed. However, this configurability makes it harder to ensure that faults will not escape testing and manifest as failures in the field. This is because many failures are configuration-dependent; they will appear under certain combinations of features configurations, but not others. Once faults are found and reported in the field, there can be a long lag time (days, weeks or even months) until patches are created and released to fix them. In the meantime, users will continue to use ...


On The Privacy Concerns Of Url Query Strings, Andrew G. West, Adam J. Aviv 2014 SelectedWorks

On The Privacy Concerns Of Url Query Strings, Andrew G. West, Adam J. Aviv

Andrew G. West

URLs often utilize query strings (i.e., key-value pairs appended to the URL path) as a means to pass session parameters and form data. Often times these arguments are not privacy sensitive but are necessary to render the web page. However, query strings may also contain tracking mechanisms, user names, email addresses, and other information that users may not wish to reveal. In isolation such URLs are not particularly problematic, but the growth of Web 2.0 platforms such as social networks and micro-blogging means URLs (often copy-pasted from web browsers) are increasingly being publicly broadcast.

This position paper argues ...


The Security Of Simplified Data Encryption Standard, Brandon Barker 2014 Boise State University

The Security Of Simplified Data Encryption Standard, Brandon Barker

College of Arts and Sciences Presentations

The Data Encryption Standard (DES) is the most widely used symmetric key cryptosystem in the commercial world. DES was published in 1975 by the National Bureau of Standards, and since then it and its variants have been commonly used. DES is utilized in many modern industries and products including the Blackberry, electronic financial transactions, and access cards to corporate offices. An efficient but secure cryptosystem is challenging to produce and even after it has been deemed “secure” new attacks and vulnerabilities are often discovered. By investigating the algebraic structure of a simplified version of DES we are able to analyze ...


Studies Of Charge Collection In Diamond-Based Particle Detectors At The Lhc, Jared Smith 2014 University of Tennessee, Knoxville

Studies Of Charge Collection In Diamond-Based Particle Detectors At The Lhc, Jared Smith

EURēCA: Exhibition of Undergraduate Research and Creative Achievement

From the event website: "The Exhibition of Undergraduate Research and Creative Achievement (EURēCA) is an annual event that showcases research and creative activities by currently enrolled undergraduate students in collaboration with a University of Tennessee, Knoxville faculty mentor. "


Aidr: Artificial Intelligence For Disaster Response, Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, Sarah Vieweg 2014 SelectedWorks

Aidr: Artificial Intelligence For Disaster Response, Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, Sarah Vieweg

Muhammad Imran

We present AIDR (Artificial Intelligence for Disaster Response), a platform designed to perform automatic classification of crisis-related microblog communications. AIDR enables humans and machines to work together to apply human intelligence to large-scale data at high speed.

The objective of AIDR is to classify messages that people post during disasters into a set of user-defined categories of information (e.g., "needs", "damage", etc.) For this purpose, the system continuously ingests data from Twitter, processes it (i.e., using machine learning classification techniques) and leverages human-participation (through crowdsourcing) in real-time. AIDR has been successfully tested to classify informative vs. non-informative tweets ...


Automated Mentor Assignment In Blended Learning Environments, Chris BOESCH, Kevin STEPPE 2014 Singapore Management University

Automated Mentor Assignment In Blended Learning Environments, Chris Boesch, Kevin Steppe

Research Collection School Of Information Systems

In this paper we discuss the addition of automatic assignment of mentors during inclass lab work to an existing online platform for programing practice. SingPath is an web based tool for users to practice programming in several software languages. The platform started as a tool to provide students with online feedback on solutions to programming problems and expanded over time to support different of blended learning needs for a variety of classes and classroom settings. The SingPath platform supports traditional self-directed learning mechanisms such as badges and completion metrics as well as features for use in classrooms, such as tournaments ...


Marick Test Matrix, Alan Ridlehoover 2014 SelectedWorks

Marick Test Matrix, Alan Ridlehoover

Alan Ridlehoover

No abstract provided.


Defect Localization Using Dynamic Call Tree Mining And Matching And Request Replication: An Alternative To Qos-Aware Service Selection, Anis Yousefi 2014 McMaster University

Defect Localization Using Dynamic Call Tree Mining And Matching And Request Replication: An Alternative To Qos-Aware Service Selection, Anis Yousefi

Open Access Dissertations and Theses

This thesis is concerned with two separate subjects; (i) Defect localization using tree mining and tree matching, and (ii) Quality-of-service-aware service selection; it is divided into these parts accordingly.

In the first part of this thesis we present a novel technique for defect localization which is able to localize call-graph-affecting defects using tree mining and tree matching techniques. In this approach, given a set of successful executions and a failing execution and by following a series of analyses we generate an extended report of suspicious method calls. The proposed defect localization technique is implemented as a prototype and evaluated using ...


On The Number Of Distinct Squares In Strings, Mei Jiang 2014 McMaster University

On The Number Of Distinct Squares In Strings, Mei Jiang

Open Access Dissertations and Theses

We investigate the problem of the maximum number of distinct primitively rooted squares in a string. In comparison to considering general strings, the number of distinct symbols in the string is introduced as an additional parameter of the problem. Let S(d,n) = max {s(x) | x is a (d,n)-string}, where s(x) denotes the number of distinct primitively rooted squares in a string x and a (d,n)-string denotes a string of length n with exactly d distinct symbols.

Inspired by the d-step approach which was instrumental in Santos' tackling of the Hirsch conjecture, we introduce ...


The Use Of The Blackboard Architecture For A Decision Making System For The Control Of Craft With Various Actuator And Movement Capabilities, Jeremy Straub, Hassan Reza 2014 SelectedWorks

The Use Of The Blackboard Architecture For A Decision Making System For The Control Of Craft With Various Actuator And Movement Capabilities, Jeremy Straub, Hassan Reza

Jeremy Straub

This paper provides an overview of an approach to the control of multiple craft with heterogeneous movement and actuation characteristics that is based on the Blackboard software architecture. An overview of the Blackboard architecture is provided. Then, the operational and mission requirements that dictate the need for autonomous control are characterized and the utility of the Blackboard architecture is for meeting these requirements is discussed. The performance of a best-path solver and naïve solver are compared. The results demonstrate that the best-path solver outperforms the naïve solver in the amount of time taken to generate a solution; however, the number ...


Semantic Privacy Policies For Service Description And Discovery In Service-Oriented Architecture, Diego Z. Garcia, Miriam A M Capretz, M. Beatriz F. Toledo 2014 Western University

Semantic Privacy Policies For Service Description And Discovery In Service-Oriented Architecture, Diego Z. Garcia, Miriam A M Capretz, M. Beatriz F. Toledo

Electrical and Computer Engineering Publications

Privacy preservation in Service-Oriented Architecture (SOA) is an open problem. This paper focuses on the areas of service description and discovery. The problems in these areas are that currently it is not possible to describe how a service provider deals with information received from a service consumer as well as discover a service that satisfies the privacy preferences of a consumer. There is currently no framework which offers a solution that supports a rich description of privacy policies and their integration in the process of service discovery. Thus, the main goal of this paper is to propose a privacy preservation ...


Artificial Neural Networks And Their Applications, David Kimmey 2014 Indiana University – Purdue University Fort Wayne

Artificial Neural Networks And Their Applications, David Kimmey

IPFW Student Research and Creative Endeavor Symposium

Artificial Neural Networks (ANNs) are computational models inspired by the central nervous system, and they are capable of machine learning and pattern recognition. In addition, ANNs are increasing in popularity for solving many industry, business, and science problems. For example, ANNs are used in automotive systems, manufacturing quality control, financial prediction, and in the medical field—spotting cancerous cells. ANN models are composed of many nonlinear computational elements operating in parallel, and usually are presented as systems of interconnected neurons that can compute values from inputs by feeding information through the network. This work presents the following six popular ANN ...


Discovery Of Course Enrollment Patterns Using Sequential Data Mining, Yei-Sol Woo 2014 Indiana University – Purdue University Fort Wayne

Discovery Of Course Enrollment Patterns Using Sequential Data Mining, Yei-Sol Woo

IPFW Student Research and Creative Endeavor Symposium

Most higher education institutions have their student management system which can produce valuable information. However the students’ data is huge and complicated, and it is hard to forecast students’ academic progress. Data mining is a process of extracting and identifying useful information and subsequent knowledge from large databases using statistical and computational analysis techniques. A new research community, educational data mining is recently growing which is intersection of data mining and pedagogy. This work presents the discovery of course sequence patterns from students’ enrollment data. The data was mined using a sequential pattern mining method which was originally developed for ...


Web-Based Student Peer Review: A Research Summary, Edward F. Gehringer 2014 SelectedWorks

Web-Based Student Peer Review: A Research Summary, Edward F. Gehringer

Edward F Gehringer

Interest in Web-based peer-review systems dates back nearly 20 years. Systems were built to let students give feedback to other students, mainly to help them improve their writing. But students are not necessarily effective peer reviewers. Left to their own devices, they will submit cursory reviews, which are not very helpful to their peers. Techniques have been developed to improve the quality of reviews. Calibration is one such technique. Students are asked to assess samples of writing that have previously been assessed by experts. Students must submit an evaluation “close enough” to the experts’ before they are allowed to review ...


Cluster-Based Epidemic Control Through Smartphone-Based Body Area Networks, Zhaoyang Zhang, Honggang Wang, Chonggang Wang, Hua (Julia) Fang 2014 University of Massachusetts Medical School

Cluster-Based Epidemic Control Through Smartphone-Based Body Area Networks, Zhaoyang Zhang, Honggang Wang, Chonggang Wang, Hua (Julia) Fang

Quantitative Health Sciences Publications and Presentations

Increasing population density, closer social contact, and interactions make epidemic control difficult. Traditional offline epidemic control methods (e.g., using medical survey or medical records) or model-based approach are not effective due to its inability to gather health data and social contact information simultaneously or impractical statistical assumption about the dynamics of social contact networks, respectively. In addition, it is challenging to find optimal sets of people to be isolated to contain the spread of epidemics for large populations due to high computational complexity. Unlike these approaches, in this paper, a novel cluster-based epidemic control scheme is proposed based on ...


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