Computer Sciences Commons^™

Exploring Digital Evidence With Graph Theory, Imani Palmer, Boris Gelfand, Roy Campbell

Annual ADFSL Conference on Digital Forensics, Security and Law

The analysis phase of the digital forensic process is the most complex. The analysis phase remains very subjective to the views of the forensic practitioner. There are many tools dedicated to assisting the investigator during the analysis process. However, they do not address the challenges. Digital forensics is in need of a consistent approach to procure the most judicious conclusions from the digital evidence. The objective of this paper is to discuss the ability of graph theory, a study of related mathematical structures, to aid in the analysis phase of the digital forensic process. We develop a graph-based representation of …

Case Study: A New Method For Investigating Crimes Against Children, Hallstein Asheim Hansen, Stig Andersen, Stefan Axelsson, Svein Hopland

Annual ADFSL Conference on Digital Forensics, Security and Law

Investigations of crimes against children are often complex, both in terms of the varied and large amount of digital technology encountered and the offensive nature of the crimes. Such cases are numerous, large, and prioritised, requiring digital forensics competence. Earlier digital forensics was considered and treated as a typical forensic science like fingerprint analysis, performed in a laboratory isolated from the investigative team. This decoupled way of working has proved to be both inefficient and error prone.

At the Digital Forensic Unit of Oslo Police District we have developed a new way of working that addresses many of the problems …

Downstream Competence Challenges And Legal/Ethical Risks In Digital Forensics, Michael M. Losavio, Antonio Losavio

Annual ADFSL Conference on Digital Forensics, Security and Law

Forensic practice is an inherently human-mediated system, from processing and collection of evidence to presentation and judgment. This requires attention to human factors and risks which can lead to incorrect judgments and unjust punishments.

For digital forensics, such challenges are magnified by the relative newness of the discipline and the use of electronic evidence in forensic proceedings. Traditional legal protections, rules of procedure and ethics rules mitigate these challenges. Application of those traditions better ensures forensic findings are reliable. This has significant consequences where findings may impact a person's liberty or property, a person's life or even the political direction …

Digital Forensics Tool Selection With Multi-Armed Bandit Problem, Umit Karabiyik, Tugba Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool available on the market for their cases to make sure they do not overlook any evidence resides in suspect device within a reasonable time frame. This is however hard decision to make, since learning and testing all available tools make their job only harder. In this project, we define the digital forensics tool selection for a specific investigative task as a multi-armed bandit problem assuming that …

Detecting Deception In Asynchronous Text, Fletcher Glancy

Annual ADFSL Conference on Digital Forensics, Security and Law

Glancy and Yadav (2010) developed a computational fraud detection model (CFDM) that successfully detected financial reporting fraud in the text of the management’s discussion and analysis (MDA) portion of annual filings with the United States Securities and Exchange Commission (SEC). This work extends the use of the CFDM to additional genres, demonstrates the generalizability of the CFDM and the use of text mining for quantitatively detecting deception in asynchronous text. It also demonstrates that writers committing fraud use words differently from truth tellers.

Understanding Deleted File Decay On Removable Media Using Differential Analysis, James H. Jones Jr, Anurag Srivastava, Josh Mosier, Connor Anderson, Seth Buenafe

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital content created by picture recording devices is often stored internally on the source device, on either embedded or removable media. Such storage media is typically limited in capacity and meant primarily for interim storage of the most recent image files, and these devices are frequently configured to delete older files as necessary to make room for new files. When investigations involve such devices and media, it is sometimes these older deleted files that would be of interest. It is an established fact that deleted file content may persist in part or in its entirety after deletion, and identifying the …

Development Of A Professional Code Of Ethics In Digital Forensics, Kathryn C. Seigfried-Spellar, Marcus Rogers, Danielle M. Crimmins 2184089

Annual ADFSL Conference on Digital Forensics, Security and Law

Academics, government officials, and practitioners suggest the field of digital forensics is in need of a professional code of ethics. In response to this need, the authors developed and proposed a professional code of ethics in digital forensics. The current paper will discuss the process of developing the professional code of ethics, which included four sets of revisions based on feedback and suggestions provided by members of the digital forensic community. The final version of the Professional Code of Ethics in Digital Forensics includes eight statements, and we hope this is a step toward unifying the field of digital forensics …

Defining A Cyber Jurisprudence, Peter R. Stephenson Phd

Annual ADFSL Conference on Digital Forensics, Security and Law

Jurisprudence is the science and philosophy or theory of the law. Cyber law is a very new concept and has had, compared with other, older, branches of the law, little structured study. However, we have entered the cyber age and the law - on all fronts - is struggling to keep pace with technological advances in cyberspace. This research explores a possible theory and philosophy of cyber law, and, indeed, whether it is feasible to develop and interpret a body of law that addresses current and emerging challenges in cyber space.

While there is an expanding discussion of the nature …

Fast Filtering Of Known Png Files Using Early File Features, Sean Mckeown, Gordon Russell, Petra Leimich

Annual ADFSL Conference on Digital Forensics, Security and Law

A common task in digital forensics investigations is to identify known contraband images. This is typically achieved by calculating a cryptographic digest, using hashing algorithms such as SHA256, for each image on a given media, comparing individual digests with a database of known contraband. However, the large capacities of modern storage media, and increased time pressure on forensics examiners, necessitates that more efficient processing mechanisms be developed. This work describes a technique for creating signatures for images of the PNG format which only requires a tiny fraction of the file to effectively distinguish between a large number of images. Highly …

Detect Kernel-Mode Rootkits Via Real Time Logging & Controlling Memory Access, Satoshi Tanda, Irvin Homem, Igor Korkin

Annual ADFSL Conference on Digital Forensics, Security and Law

Modern malware and spyware platforms attack existing antivirus solutions and even Microsoft PatchGuard. To protect users and business systems new technologies developed by Intel and AMD CPUs may be applied. To deal with the new malware we propose monitoring and controlling access to the memory in real time using Intel VT-x with EPT. We have checked this concept by developing MemoryMonRWX, which is a bare-metal hypervisor. MemoryMonRWX is able to track and trap all types of memory access: read, write, and execute. MemoryMonRWX also has the following competitive advantages: fine-grained analysis, support of multi-core CPUs and 64-bit Windows 10. MemoryMonRWX …

Harnessing Predictive Models For Assisting Network Forensic Investigations Of Dns Tunnels, Irvin Homem, Panagiotis Papapetrou

Annual ADFSL Conference on Digital Forensics, Security and Law

In recent times, DNS tunneling techniques have been used for malicious purposes, however network security mechanisms struggle to detect them. Network forensic analysis has been proven effective, but is slow and effort intensive as Network Forensics Analysis Tools struggle to deal with undocumented or new network tunneling techniques. In this paper, we present a machine learning approach, based on feature subsets of network traffic evidence, to aid forensic analysis through automating the inference of protocols carried within DNS tunneling techniques. We explore four network protocols, namely, HTTP, HTTPS, FTP, and POP3. Three features are extracted from the DNS tunneled traffic: …

An Accidental Discovery Of Iot Botnets And A Method For Investigating Them With A Custom Lua Dissector, Max Gannon, Gary Warner, Arsh Arora

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper presents a case study that occurred while observing peer-to-peer network communications on a botnet monitoring station and shares how tools were developed to discover what ultimately was identified as Mirai and many related IoT DDOS Botnets. The paper explains how researchers developed a customized protocol dissector in Wireshark using the Lua coding language, and how this enabled them to quickly identify new DDOS variants over a five month period of study.

Kelihos Botnet: A Never-Ending Saga, Arsh Arora, Max Gannon, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper investigates the recent behavior of the Kelihos botnet, a spam-sending botnet that accounts for many millions of emails sent each day. The paper demonstrates how a team of students are able to perform a longitudinal malware study, making significant observations and contributions to the understanding of a major botnet using tools and techniques taught in the classroom. From this perspective the paper has two objectives: encouragement and observation. First, by providing insight into the methodology and tools used by student researchers to document and understand a botnet, the paper strives to embolden other academic programs to follow a …

We Are Alfred: Empathy Learned Through A Medical Education Virtual Reality Project, Barbara Swartzlander, Elizabeth Dyer, Marilyn R. Gugliucci

Library Services Faculty Posters

Poster describing project collaboration among University of New England (UNE) librarians and College of Osteopathic Medicine (COM) faculty, whose goal was to adopt technology which will teach UNECOM students to be empathic with older adults and familiarize medical students with information resources from the NIH/NLM related to older adult health. Technology tested was the Alfred Lab developed by Embodied Labs. First year medical students were required to complete the ‘We Are Alfred’ virtual reality module and a pre and post assessment. Descriptive statistics were applied to finite questions on pre and post assessments, and content analysis on open ended answers. …

Curiosity: Emergent Behavior Through Interacting Multi-Level Predictions, Douglas S. Blank, Lisa Meeden, James Marshall

Computer Science Faculty Research and Scholarship

Over the past 15 years our research group has been exploring models of developmental robotics and curiosity. Our research is based on the premise that intelligent behavior arises through emergent interactions between opposing forces in an open-ended, task-independent environment. In an initial experiment we constructed a recurrent neural network model where self-motivation was "an emergent property generated by the competing pressures that arise in attempting to balance predictability and novelty". The system first focused on its error, then learned to successfully predict its error, and finally became habituated to what caused the error. This process of focusing, learning, and habituating …

Software Development For Home Energy Audits: Reducing Energy Consumption In Harrisonburg Through Technology, Brantley E. Gilbert

Senior Honors Projects, 2010-2019

Fossil fuels play a vital role in our daily lives. Oil, natural gas, and coal powers our cars, heats our homes and water, and are used by power companies to generate the massive amounts of electricity used every day by the United States. However, this reliance on a finite source of energy is not sustainable. Fossil fuels such as these are non-renewable resources whose production will eventually be unable to keep up with the rate of consumption. Furthermore, the extraction of the stored energy in these fuels through combustion releases harmful substances into the environment, including toxins and greenhouse gases …

Investigating Trust And Trust Recovery In Human-Robot Interactions, Abigail L. Thomson

Celebration of Learning

As artificial intelligence and robotics continue to advance and be used in increasingly different functions and situations, it is important to look at how these new technologies will be used. An important factor in how a new resource will be used is how much it is trusted. This experiment was conducted to examine people’s trust in a robotic assistant when completing a task, how mistakes affect this trust, and if the levels of trust exhibited with a robot assistant were significantly different than if the assistant were human. The task was to watch a computer simulation of the three-cup monte …

Ispy: Threats To Individual And Institutional Privacy In The Digital World, Lori Andrews

All Faculty Scholarship

What type of information is collected, who is viewing it, and what law librarians can do to protect their patrons and institutions.

Digital Hegemonies: The Localness Of Search Engine Results, Andrea Ballatore, Mark Graham, Shilad Sen

Faculty Publications

Every day, billions of Internet users rely on search engines to find information about places to make decisions about tourism, shopping, and countless other economic activities. In an opaque process, search engines assemble digital content produced in a variety of locations around the world and make it available to large cohorts of consumers. Although these representations of place are increasingly important and consequential, little is known about their characteristics and possible biases. Analyzing a corpus of Google search results generated for 188 capital cities, this article investigates the geographic dimension of search results, focusing on searches such as “Lagos” and …

Optimized Forecasting Of Dominant U.S. Stock Market Equities Using Univariate And Multivariate Time Series Analysis Methods, Michael Schwartz

Computational and Data Sciences Theses

This dissertation documents an investigation into forecasting U.S. stock market equities via two very different time series analysis techniques: 1) autoregressive integrated moving average (ARIMA), and 2) singular spectrum analysis (SSA). Approximately 40% of the S&P 500 stocks are analyzed. Forecasts are generated for one and five days ahead using daily closing prices. Univariate and multivariate structures are applied and results are compared. One objective is to explore the hypothesis that a multivariate model produces superior performance over a univariate configuration. Another objective is to compare the forecasting performance of ARIMA to SSA, as SSA is a relatively recent development …

Proactive And Reactive Strategies To Handle Surges In Urban Crowds, Jiali Du

Dissertations and Theses Collection

Most urban infrastructures are built to cater a planned capacity, yet surges in usage do happen in times (can be either expected or unexpected), and this has long been a major challenge for urban planner. In this thesis, I propose to study approaches handle surges in urban crowd movement. In particular, the surges in demand studied are limited to situations where a large crowd of commuters/visitors gather in a small vicinity, and I am concerned with their movements both within the vicinity and out of the vicinity (the egress from the vicinity). Significant crowd build-ups and congestions can be observed …

Umass Memorial Healthcare Information System Job Ladder, Matthew Simoncini, Vamsi Kavuru, Antariksh Nanda, Tahaseen Mahaboob Basha, Vikram Patil

School of Professional Studies

The capstone project report emphasizes the importance of a job ladder and the need of an hour to implement it at UMASS Memorial health care. The scope of this project is to create a well-established job ladder at UMASS with pre-defined standards on job levels related to Information Technology department that would facilitate in hiring, developing and promoting employees at various stages.

A Learning Framework For The Ywca Central Massachusetts, Dayna Ankermann, Manjushree Burdekar, Priyanka Joshi, Ying Song, Yumeng Chen, Xing Xie

School of Professional Studies

After meeting with the Director of Wellness and Health Equity at the YWCA Central Massachusetts (which will be referred to as the YWCA from here on out), we learned that as a non-profit gym and health center, it is heavily underfunded. The main focus of the project was to determine how to upkeep the facility while bringing in new customers with limited resources and budget. Due to the needs of the YWCA, our group focused on six aspects: revenue stream, donor retention, increasing membership, customer experience, social media marketing, and membership fee structure. After completing extensive research, we were able …

Human Services Management (Hsm) Certificate Program Expansion To Western Massachusetts Feasibility Study, Paul Campbell, Patrick Deschenes, Maria Pacheco, Bradley Paul, Elizabeth Vittum, Jing Zhang

School of Professional Studies

One of the most popular cost-savings programs that the Providers’ Council currently offers its members is a Certificate in Nonprofit Human Service Management (HSM) provided in partnership with Clark University and Suffolk University. As human services providers are struggling to hire and retain qualified staff, the need to provide professional development opportunities to help grow and expand a skilled health and human services workforce is a critical issue facing nonprofit organizations and communities in Massachusetts. This feasibility study examines the viability of Providers’ Council and Clark University expanding its HSM Certificate Program to organizations and staff located in western Massachusetts. …

Somali National University, Sharmarke Abdulla, Nikala Pieroni, Jenna Caskie, Sergii Odnodvorets, Tanyue Gong, Lahari Dasari

School of Professional Studies

The executive summary presents an overview of the principal conclusions and recommendations for Somali National University Faculty of Education (FoEd) regarding the following concerns: Difficulty with recruiting high quality prospects to the FoEd; Ineffective and counterintuitive use of social media as a tool to improve brand equity, as well as as a tool to attract and communicate with prospective and current students; Unbalanced gender ratio of current student body; Absence of student services and student supports; Low student retention rate; Limited resources for academic advising; This document is the result of a Clark University School of Professional Studies Capstone Project.

Country 2.0: Upgrading Cities With Smart Technologies, Steven M. Miller

Asian Management Insights

Advancements in technology are being used to transform our cities into smart cities, but the process is not without its risks.

The Economics Of The Right To Be Forgotten, Byung-Cheol Kim, Jin Yeub Kim

Department of Economics: Faculty Publications

Scholars and practitioners debate whether to expand the scope of the right to be forgotten—the right to have certain links removed from search results—to encompass global search results. The debate centers on the assumption that the expansion will increase the incidence of link removal, which reinforces privacy while hampering free speech. We develop a game-theoretic model to show that the expansion of the right to be forgotten can reduce the incidence of link removal. We also show that the expansion does not necessarily enhance the welfare of individuals who request removal and that it can either improve or reduce societal …

Exploiting Contextual Information For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The problem of fine-grained tweet geolocation is to link tweets to their posting venues. We solve this in a learning to rank framework by ranking candidate venues given a test tweet. The problem is challenging as tweets are short and the vast majority are non-geocoded, meaning information is sparse for building models. Nonetheless, although only a small fraction of tweets are geocoded, we find that they are posted by a substantial proportion of users. Essentially, such users have location history data. Along with tweet posting time, these serve as additional contextual information for geolocation. In designing our geolocation models, we …

A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar

Research Collection School Of Computing and Information Systems

Environmental, regulatory and resource constraints affects the safety and efficiency of vessels navigating in and out of the ports. Movement of vessels under such constraints must be coordinated for improving safety and efficiency. Thus, we frame the vessel coordination problem as a multi-agent path-finding (MAPF) problem. We solve this MAPF problem using a Coordinated Path-Finding (CPF) algorithm. Based on the local search paradigm, the CPF algorithm improves on the aggregated path quality of the vessels iteratively. Outputs of the CPF algorithm are the coordinated trajectories. The Vessel Coordination Module (VCM) described here is the module encapsulating our MAPF-based approach for …

Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang

Research Collection School Of Computing and Information Systems

Social influence has attracted significant attention owing to the prevalence of social networks (SNs). In this paper, we study a new social influence problem, called personalized social influential tags exploration (PITEX), to help any user in the SN explore how she influences the network. Given a target user, it finds a size-k tag set that maximizes this user’s social influence. We prove the problem is NP-hard to be approximated within any constant ratio. To solve it, we introduce a sampling-based framework, which has an approximation ratio of 1−ǫ 1+ǫ with high probabilistic guarantee. To speedup the computation, we devise more …