Computer Sciences Commons^™

Context-Based Autosuggest On Graph Data, Hai Nguyen

Master's Projects

Autosuggest is an important feature in any search applications. Currently, most applications only suggest a single term based on how frequent that term appears in the indexed documents or how often it is searched upon. These approaches might not provide the most relevant suggestions because users often enter a series of related query terms to answer a question they have in mind. In this project, we implemented the Smart Solr Suggester plugin using a context-based approach that takes into account the relationships among search keywords. In particular, we used the keywords that the user has chosen so far in the …

A Scalable Search Engine Aggregator, Pooja Mishra

Master's Projects

The ability to display different media sources in an appropriate way is an integral part of search engines such as Google, Yahoo, and Bing, as well as social networking sites like Facebook, etc. This project explores and implements various media-updating features of the open source search engine Yioop [1]. These include news aggregation, video conversion and email distribution. An older, preexisting news update feature of Yioop was modified and scaled so that it can work on many machines. We redesigned and modified the user interface associated with a distributed news updater feature in Yioop. This project also introduced a video …

Continuous Monitoring System Based On Systems' Environment, Eli Weintraub, Yuval Cohen

Annual ADFSL Conference on Digital Forensics, Security and Law

We present a new framework (and its mechanisms) of a Continuous Monitoring System (CMS) having new improved capabilities, and discuss its requirements and implications. The CMS is based on the real-time actual configuration of the system and the environment rather than a theoretic or assumed configuration. Moreover, the CMS predicts organizational damages taking into account chains of impacts among systems' components generated by messaging among software components. In addition, the CMS takes into account all organizational effects of an attack. Its risk measurement takes into account the consequences of a threat, as defines in risk analysis standards. Loss prediction is …

Html5 Zero Configuration Covert Channels: Security Risks And Challenges, Jason Farina, Mark Scanlon, Stephen Kohlmann, Nhien-An Le-Khac, Tahar Kechadi

Annual ADFSL Conference on Digital Forensics, Security and Law

In recent months there has been an increase in the popularity and public awareness of secure, cloudless file transfer systems. The aim of these services is to facilitate the secure transfer of files in a peer-to-peer (P2P) fashion over the Internet without the need for centralized authentication or storage. These services can take the form of client installed applications or entirely web browser based interfaces. Due to the P2P nature, there is generally no limit to the file sizes involved or to the volume of data transmitted - and where these limitations do exist they will be purely reliant on …

Measuring Hacking Ability Using A Conceptual Expertise Task, Justin S. Giboney, Jeffrey G. Proudfoot, Sanjay Goel, Joseph S. Valacich

Annual ADFSL Conference on Digital Forensics, Security and Law

Hackers pose a continuous and unrelenting threat to organizations. Industry and academic researchers alike can benefit from a greater understanding of how hackers engage in criminal behavior. A limiting factor of hacker research is the inability to verify that self-proclaimed hackers participating in research actually possess their purported knowledge and skills. This paper presents current work in developing and validating a conceptual-expertise based tool that can be used to discriminate between novice and expert hackers. The implications of this work are promising since behavioral information systems researchers operating in the information security space will directly benefit from the validation of …

Invited Paper - A Profile Of Prolonged, Persistent Ssh Attack On A Kippo Based Honeynet, Craig Valli, Priya Rabadia, Andrew Woodard

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper is an investigation focusing on activities detected by SSH honeypots that utilised kippo honeypot software. The honeypots were located across a variety of geographical locations and operational platforms. The honeynet has suffered prolonged, persistent and attack from a /24 network which appears to be of Chinese geographical origin. In addition to these attacks, other attackers have been successful in compromising real hosts in a wide range of other countries that were subsequently involved in attacking the honeypot machines in the honeynet.

Keywords: Cyber Security, SSH, Secure Shell, Honeypots, Kippo

Inivited Paper - Potential Changes To Ediscovery Rules In Federal Court: A Discussion Of The Process, Substantive Changes And Their Applicability And Impact On Virginia Practice, Joseph J. Schwerha, Susan L. Mitchell, John W. Bagby

Annual ADFSL Conference on Digital Forensics, Security and Law

The Federal Rules of Civil Procedure (FRCP) are subject to a unique process also once used in revising the Federal Rules of Evidence (FRE). Today, this process is followed in revisions of the FRCP, the Federal Rules of Criminal Procedure and the Federal Bankruptcy Rules. This unique rulemaking process differs significantly from traditional notice and comment rulemaking required for a majority of federal regulatory agencies under the Administrative Procedure Act (APA).1 Most notably, rule-making for the federal courts’ procedural matters remain unaffected by the invalidation of legislative veto. It is still widely, but wrongly believed, that the legislative veto was …

On The Network Performance Of Digital Evidence Acquisition Of Small Scale Devices Over Public Networks, Irvin Homem, Spyridon Dosis

Annual ADFSL Conference on Digital Forensics, Security and Law

While cybercrime proliferates – becoming more complex and surreptitious on the Internet – the tools and techniques used in performing digital investigations are still largely lagging behind, effectively slowing down law enforcement agencies at large. Real-time remote acquisition of digital evidence over the Internet is still an elusive ideal in the combat against cybercrime. In this paper we briefly describe the architecture of a comprehensive proactive digital investigation system that is termed as the Live Evidence Information Aggregator (LEIA). This system aims at collecting digital evidence from potentially any device in real time over the Internet. Particular focus is made …

A Review Of Recent Case Law Related To Digital Forensics: The Current Issues, Kelly A. Cole, Shruti Gupta, Dheeraj Gurugubelli, Marcus K. Rogers

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital forensics is a new field without established models of investigation. This study uses thematic analysis to explore the different issues seen in the prosecution of digital forensic investigations. The study looks at 100 cases from different federal appellate courts to analyze the cause of the appeal. The issues are categorized into one of four categories, ‘search and seizure’, ‘data analysis’, ‘presentation’ and ‘legal issues’. The majority of the cases reviewed related to the search and seizure activity.

Keywords: Computer Investigation, Case Law, Digital Forensics, Legal Issues, and Courts

Two Algorithms For Finding Edge Colorings In Regular Bipartite Multigraphs, Patricia T. Neckowicz

Dartmouth College Undergraduate Theses

For a d-regular bipartite multigraph, an edge coloring is equivalent to a decomposition of the edge set into d perfect matchings. When d is a power of 2, we can recursively perform Euler partitions to find the perfect matchings. When d is not a power of 2, however, we eventually reach a subproblem graph of odd degree where we can no longer perform an Euler partition. We propose two different algorithms that address this case. Both algorithms make use of an auxiliary matching, called dummy edges, to make the degree of the graph even. In the first algorithm, dummy edges …

A New Cyber Forensic Philosophy For Digital Watermarks In The Context Of Copyright Laws, Vinod P. Bhattathiripad, Sneha Sudhakaran, Roshna K. Thalayaniyil

Annual ADFSL Conference on Digital Forensics, Security and Law

The objective of this paper is to propose a new cyber forensic philosophy for watermark in the context of copyright laws for the benefit of the forensic community and the judiciary worldwide. The paper first briefly introduces various types of watermarks, and then situates watermarks in the context of the ideaexpression dichotomy and the copyright laws. It then explains the forensic importance of watermarks and proposes a forensic philosophy for them in the context of copyright laws. Finally, the paper stresses the vital need to incorporate watermarks in the forensic tests to establish software copyright infringement and also urges the …

A Survey Of Software-Based String Matching Algorithms For Forensic Analysis, Yi-Ching Liao

Annual ADFSL Conference on Digital Forensics, Security and Law

Employing a fast string matching algorithm is essential for minimizing the overhead of extracting structured files from a raw disk image. In this paper, we summarize the concept, implementation, and main features of ten software-based string matching algorithms, and evaluate their applicability for forensic analysis. We provide comparisons between the selected software-based string matching algorithms from the perspective of forensic analysis by conducting their performance evaluation for file carving. According to the experimental results, the Shift-Or algorithm (R. Baeza-Yates & Gonnet, 1992) and the Karp-Rabin algorithm (Karp & Rabin, 1987) have the minimized search time for identifying the locations of …

Investigating Forensics Values Of Windows Jump Lists Data, Ahmad Ghafarian

Annual ADFSL Conference on Digital Forensics, Security and Law

Starting with Windows 7, Microsoft introduced a new feature to the Windows Operating Systems called Jump Lists. Jump Lists stores information about user activities on the host machine. These activities may include links to the recently visited web pages, applications executed, or files processed. Computer forensics investigators may find traces of misuse in Jump Lists auto saved files. In this research, we investigate the forensics values of Jump Lists data. Specifically, we use several tools to view Jump Lists data on a virtual machine. We show that each tool reveal certain types of information about user’s activity on the host …

An Empirical Comparison Of Widely Adopted Hash Functions In Digital Forensics: Does The Programming Language And Operating System Make A Difference?, Satyendra Gurjar, Ibrahim Baggili, Frank Breitinger, Alice Fischer

Annual ADFSL Conference on Digital Forensics, Security and Law

Hash functions are widespread in computer sciences and have a wide range of applications such as ensuring integrity in cryptographic protocols, structuring database entries (hash tables) or identifying known files in forensic investigations. Besides their cryptographic requirements, a fundamental property of hash functions is efficient and easy computation which is especially important in digital forensics due to the large amount of data that needs to be processed when working on cases. In this paper, we correlate the runtime efficiency of common hashing algorithms (MD5, SHA-family) and their implementation. Our empirical comparison focuses on C-OpenSSL, Python, Ruby, Java on Windows and …

Two Challenges Of Stealthy Hypervisors Detection: Time Cheating And Data Fluctuations, Igor Korkin

Annual ADFSL Conference on Digital Forensics, Security and Law

Hardware virtualization technologies play a significant role in cyber security. On the one hand these technologies enhance security levels, by designing a trusted operating system. On the other hand these technologies can be taken up into modern malware which is rather hard to detect. None of the existing methods is able to efficiently detect a hypervisor in the face of countermeasures such as time cheating, temporary self-uninstalling, memory hiding etc. New hypervisor detection methods which will be described in this paper can detect a hypervisor under these countermeasures and even count several nested ones. These novel approaches rely on the …

Driver Telematics Analysis, Karthik Vakati

Master's Projects

For automobile insurance firms, telemetric analysis represents a valuable and growing way to identify the risk associated with each driver. The pricing decisions of an insurer are best accounted for if they are made considering the driver’s behavior instead of just the vehicle characteristics and the best way to understand a driver’s behavior is to leverage the telemetric analysis. Decisions made on such factors can eventually lead to increased premium or reduced liability for unsafe or reckless drivers and can also help in transitioning the burden to the policies that lead to increased liability.

The dataset provided for this project …

Maximizing The Speed Of Influence In Social Networks, Yubo Wang

Master's Projects

Influence maximization in social networks is the problem of selecting a limited

size of influential users as seed nodes so that the influence from these seed nodes can propagate to the largest number of other nodes in the network. Previous studies in influence maximization focused on three areas, i.e., designing propagation models, improving algorithms of seed-node selection and exploiting the structure of social networks. However, most of these studies ignored the time constraint in influence propagation. In this paper, I studied how to maximize influence propagation in a given time, i.e., maximizing the speed of influence propagation in social networks. …

Using Neural Networks For Image Classification, Tim Kang

Master's Projects

This paper will focus on applying neural network machine learning methods to images for the purpose of automatic detection and classification. The main advantage of using neural network methods in this project is its adeptness at fitting non­linear data and its ability to work as an unsupervised algorithm. The algorithms will be run on common, publically available datasets, namely the MNIST and CIFAR­10, so that our results will be easily reproducible.

Multiblock Discriminant Analysis For Integrative Genomic Study, Mingon Kang, Dong-Chul Kim, Chunyu Liu, Jean Gao

Computer Science Faculty Publications

Human diseases are abnormal medical conditions in which multiple biological components are complicatedly involved. Nevertheless, most contributions of research have been made with a single type of genetic data such as Single Nucleotide Polymorphism (SNP) or Copy Number Variation (CNV). Furthermore, epigenetic modifications and transcriptional regulations have to be considered to fully exploit the knowledge of the complex human diseases as well as the genomic variants. We call the collection of the multiple heterogeneous data “multiblock data.” In this paper, we propose a novel Multiblock Discriminant Analysis (MultiDA) method that provides a new integrative genomic model for the multiblock analysis …

Look Sharp! How Eye Tracking And Memory Explain Susceptibility To Phishing, Ian Jones, Anthony Vance

Journal of Undergraduate Research

Warning messages are one of the last lines of defense in computer security and are fundamental to users’ security interactions with technology. Consequently, researchers have actively sought to understand how users interact with security warnings and why warnings are so pervasively ignored. A key contributor to the disregard of security warnings is habituation—i.e., the diminishing of attention because of frequent exposure to warning. Although habituation has been inferred as a factor in many security-warning studies, little research has examined habituation in the context of security directly because habituation as a mental state is difficult to observe using conventional methods. …

Software Application And Mobile Optimization, Timothy Yu

Undergraduate University Honors Capstones

Most software applications have yet to be optimized for mobile devices, such as smartphones and tablets. Such is the case with Gallaudet University’s enterprise information systems, Bison, the university’s administration system, including all records except for finances and Blackboard, the university’s learning management system. A two-part project addressed this lack of mobile optimization with Bison. The first part was the Residence Life Sticker Project intended to familiarize the developer with Gallaudet’s internal IT systems. It involved developing a web form for the Office of Residence Life to record receipt of ID card stickers, handbooks, and release room consent information. The …

Static Analysis Of Malicious Java Applets, Nikitha Ganesh

Master's Projects

In this research, we consider the problem of detecting malicious Java applets, based on static analysis. In general, dynamic analysis is more informative, but static analysis is more efficient, and hence more practical. Consequently, static analysis is preferred, provided we can obtain results comparable to those obtained using dynamic analysis. We conducted experiments with the machine learning technique, Hidden Markov Model (HMM). We show that in some cases a static technique can detect malicious Java applets with greater accuracy than previously published research that relied on dynamic analysis.

Sociobot: Twitter For Command And Control Of A Botnet, Ismeet Kaur Makkar

Master's Projects

A botnet is a collection of computers controlled by a botmaster, often used for malicious activity. Social network provides an ideal medium for botnets to spread their reach. In this research, we develop and analyze a botnet that uses Twitter for its command and control channel. We use this botnet to perform a distributed denial of service attack on a web server, and we utilize the biological epidemic models to analyze the spread of the botnet using Twitter.

Combining Dynamic And Static Analysis For Malware Detection, Anusha Damodaran

Master's Projects

Well-designed malware can evade static detection techniques, such as signature scanning. Dynamic analysis strips away one layer of obfuscation and hence such an approach can potentially provide more accurate detection results. However, dynamic analysis is generally more costly than static analysis. In this research, we analyze the effectiveness of using dynamic analysis to enhance the training phase, while using only static techniques in the detection phase. Relative to a fully static approach, the additional overhead is minimal, since training is essentially one-time work.

Frameshift: Shift Your Attention, Shift The Story, Tim Tregubov, Rukmini Goswami

Dartmouth College Master’s Theses

Attention is a limited resource that intrinsically dictates our perceptions, memories, and behaviors. Further, visuospatial attention correlates highly with user engagement, heart rate, and arousal. Artists and interactive game designers strive to capture and direct attention, yet even in the most carefully crafted graphic narratives viewer eye paths -- a proxy for attention -- vary up to 20 percent. Our aim is to use attentional measures to enrich graphic novel narratives.FrameShift uses eye tracking to measure reader attention and changes text and visual elements later on in the story accordingly. We have built an extensible framework for using attention to …

Exploring How Dual-Task Interference Influences End-User Secure Behavior, K Shane Reeves, Jeffrey Jenkins

Journal of Undergraduate Research

Finding ways to help people behave securely is of great value and importance to companies worldwide. Policies are often created to help enforce secure behavior; however, policies are not always followed, even if they seem simple and clear.

Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su

MODVIS Workshop

We propose a combinatorial approach built on Grenander’s pattern theory to generate semantic interpretations of video events of human activities. The basic units of representations, termed generators, are linked with each other using pairwise connections, termed bonds, that satisfy predefined relations. Different generators are specified for different levels, from (image) features at the bottom level to (human) actions at the highest, providing a rich representation of items in a scene. The resulting configurations of connected generators provide scene interpretations; the inference goal is to parse given video data and generate high-probability configurations. The probabilistic structures are imposed using energies that …

Two Correspondence Problems Easier Than One, Aaron Michaux, Zygmunt Pizlo

MODVIS Workshop

Computer vision research rarely makes use of symmetry in stereo reconstruction despite its established importance in perceptual psychology. Such stereo reconstructions produce visually satisfying figures with precisely located points and lines, even when input images have low or moderate resolution. However, because few invariants exist, there are no known general approaches to solving symmetry correspondence on real images. The problem is significantly easier when combined with the binocular correspondence problem, because each correspondence problem provides strong non-overlapping constraints on the solution space. We demonstrate a system that leverages these constraints to produce accurate stereo models from pairs of binocular images …

Characterization Of Common Videos With Signatures Extracted From Frame Transition Profiles, Abhiram Reddy Gaddampalli

Student Work

People have access to a tremendous amount of video nowadays, both on television and Internet. The amount of video that a viewer has to choose from is so large that it is infeasible for a human to go through it all to find a video of interest. Organizing video into categories will make the process of large number of videos much faster and improves the ease of access. A profile created by observing the rate at which the contents of video frame changes helps in categorization of videos in different types. The experiments we conducted on three types of videos …

Formal Aspects Of Non-Rigid-Shape-From-Motion Perception, Vicky Froyen, Qasim Zaidi

MODVIS Workshop

Our world is full of objects that deform over time, for example animals, trees and clouds. Yet, the human visual system seems to readily disentangle object motions from non-rigid deformations, in order to categorize objects, recognize the nature of actions such as running or jumping, and even to infer intentions. A large body of experimental work has been devoted to extracting rigid structure from motion, but there is little experimental work on the perception of non-rigid 3-D shapes from motion (e.g. Jain, 2011). Similarly, until recently, almost all formal work had concentrated on the rigid case. In the last fifteen …