Other Computer Sciences Commons^™

Covert6: A Tool To Corroborate The Existence Of Ipv6 Covert Channels, Raymond A. Hansen, Lourdes Gino, Dominic Savio

Annual ADFSL Conference on Digital Forensics, Security and Law

Covert channels are any communication channel that can be exploited to transfer information in a manner that violates the system’s security policy. Research in the field has shown that, like many communication channels, IPv4 and the TCP/IP protocol suite have been susceptible to covert channels, which could be exploited to leak data or be used for anonymous communications. With the introduction of IPv6, researchers are acutely aware that many vulnerabilities of IPv4 have been remediated in IPv6. However, a proof of concept covert channel system was demonstrated in 2006. A decade later, IPv6 and its related protocols have undergone major …

Acceleration Of Statistical Detection Of Zero-Day Malware In The Memory Dump Using Cuda-Enabled Gpu Hardware, Igor Korkin, Iwan Nesterow

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper focuses on the anticipatory enhancement of methods of detecting stealth software. Cyber security detection tools are insufficiently powerful to reveal the most recent cyber-attacks which use malware. In this paper, we will present first an idea of the highest stealth malware, as this is the most complicated scenario for detection because it combines both existing anti-forensic techniques together with their potential improvements. Second, we will present new detection methods which are resilient to this hidden prototype. To help solve this detection challenge, we have analyzed Windows’ memory content using a new method of Shannon Entropy calculation; methods of …

Using Computer Behavior Profiles To Differentiate Between Users In A Digital Investigation, Shruti Gupta, Marcus Rogers

Annual ADFSL Conference on Digital Forensics, Security and Law

Most digital crimes involve finding evidence on the computer and then linking it to a suspect using login information, such as a username and a password. However, login information is often shared or compromised. In such a situation, there needs to be a way to identify the user without relying exclusively on login credentials. This paper introduces the concept that users may show behavioral traits which might provide more information about the user on the computer. This hypothesis was tested by conducting an experiment in which subjects were required to perform common tasks on a computer, over multiple sessions. The …

Current Challenges And Future Research Areas For Digital Forensic Investigation, David Lillis, Brett A. Becker, Tadhg O’Sullivan, Mark Scanlon

Annual ADFSL Conference on Digital Forensics, Security and Law

Given the ever-increasing prevalence of technology in modern life, there is a corresponding increase in the likelihood of digital devices being pertinent to a criminal investigation or civil litigation. As a direct consequence, the number of investigations requiring digital forensic expertise is resulting in huge digital evidence backlogs being encountered by law enforcement agencies throughout the world. It can be anticipated that the number of cases requiring digital forensic analysis will greatly increase in the future. It is also likely that each case will require the analysis of an increasing number of devices including computers, smartphones, tablets, cloud-based services, Internet …

Forensic Analysis Of Ares Galaxy Peer-To-Peer Network, Frank Kolenbrander, Nhien-An Le-Khac, Tahar Kechadi

Annual ADFSL Conference on Digital Forensics, Security and Law

Child Abuse Material (CAM) is widely available on P2P networks. Over the last decade several tools were made for 24/7 monitoring of peer-to-peer (P2P) networks to discover suspects that use these networks for downloading and distribution of CAM. For some countries the amount of cases generated by these tools is so great that Law Enforcement (LE) just cannot handle them all. This is not only leading to backlogs and prioritizing of cases but also leading to discussions about the possibility of disrupting these networks and sending warning messages to potential CAM offenders. Recently, investigators are reporting that they are creating …

Keynote Speaker, Chuck Easttom

Annual ADFSL Conference on Digital Forensics, Security and Law

Conference Keynote Speaker, Chuck Easttom

Multiple Sequence Alignment With Pro Le Hidden Markov Models, Shubhangi Rakhonde

Master's Projects

The human genome consists of various patterns and sequences that are of biolog- ical signi cance. Capturing these patterns can help us in resolving various mysteries related to the genome, like how genomes evolve, how diseases occur due to genetic mutation, how viruses mutate to cause new disease and what is the cure for these diseases. All these applications are covered in the study of bioinformatics.

One of the very common tasks in bioinformatics involves simultaneous alignment of a number of biological sequences. In bioinformatics, this is widely known as Mul- tiple Sequence Alignment. Multiple sequence alignments help in grouping …

Interactive Computer Science Exercises In Edx, Hong Le

Master's Projects

This project focuses on improving online learning courses for Computer Science. My approach is to create a platform in which interactive exercises can be implemented for students to work on. Methodology includes creating plugins for interactive exercises using XBlock, a component architecture for building independent online courses on edX. The exercises are based on existing exercises like CodeCheck and Wiley’s InterActivities Exercise System. In order to integrate these exercises, I implemented CodeCheck XBlock and Interactive XBlock. These Xblocks allow students to work on interactive exercises on edX, and instructors to view and download students’ submissions.

Visualization Of Deep Convolutional Neural Networks, Dingwen Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Deep learning has achieved great accuracy in large scale image classification and scene recognition tasks, especially after the Convolutional Neural Network (CNN) model was introduced. Although a CNN often demonstrates very good classification results, it is usually unclear how or why a classification result is achieved. The objective of this thesis is to explore several existing visualization approaches which offer intuitive visual results. The thesis focuses on three visualization approaches: (1) image masking which highlights the region of image with high influence on the classification, (2) Taylor decomposition back-propagation which generates a per pixel heat map that describes each pixel's …

Design And Implementation Of Asymptotically Optimal Mesh Slicing Algorithms Using Parallel Processing, Christopher Dant

MS in Computer Science Project Reports

Mesh slicing is the process of taking a three dimensional model and reducing it to 2.5 dimensional layers that together create a layered representation of the model. The process is used in layered additive manufacturing, three dimensional voxelization, and other similar problems in computational geometry. The slicing process is computationally expensive, and the time required to slice an object can inhibit the viability of layered manufacturing in some industries. We designed and developed a fast implementation of the slicing process, called Sunder, that uses new asymptotically optimal algorithms and takes advantage of parallel processing platforms. To our knowledge, no other …

Internet Of Things-Based Smart Classroom Environment, Amir R. Atabekov

Master of Science in Computer Science Theses

Internet of Things (IoT) is a novel paradigm that is gaining ground in the Computer Science field. There’s no doubt that IoT will make our lives easier with the advent of smart thermostats, medical wearable devices, connected vending machines and others. One important research direction in IoT is Resource Management Systems (RMS). In the current state of RMS research, very few studies were able to take advantage of indoor localization which can be very valuable, especially in the context of smart classrooms. For example, indoor localization can be used to dynamically generate seat map of students in a classroom. Indoor …

Improving Electroencephalography-Based Imagined Speech Recognition With A Simultaneous Video Data Stream, Sarah J. Stolze

Computer Science and Computer Engineering Undergraduate Honors Theses

Electroencephalography (EEG) devices offer a non-invasive mechanism for implementing imagined speech recognition, the process of estimating words or commands that a person expresses only in thought. However, existing methods can only achieve limited predictive accuracy with very small vocabularies; and therefore are not yet sufficient to enable fluid communication between humans and machines. This project proposes a new method for improving the ability of a classifying algorithm to recognize imagined speech recognition, by collecting and analyzing a large dataset of simultaneous EEG and video data streams. The results from this project suggest confirmation that complementing high-dimensional EEG data with similarly …

Cest: City Event Summarization Using Twitter, Deepa Mallela

Computer Science Graduate Projects and Theses

Twitter, with 288 million active users, has become the most popular platform for continuous real-time discussions. This leads to huge amounts of information related to the real-world, which has attracted researchers from both academia and industry. Event detection on Twitter has gained attention as one of the most popular domains of interest within the research community. Unfortunately, existing event detection methodologies have yet to fully explore Twitter metadata and instead rely solely on identifying events based on prior information or focus on events that belong to specific categories. Given the heavy volume of tweets that discuss events, summarization techniques can …

Acceleration Of Ddscat Computation By Parallelization On A Supercomputer, Manoj V. Seeram

Chemical Engineering Undergraduate Honors Theses

The DDSCAT software is enabled for use of MPI or OpenMP to distribute calculation of different particle orientations amongst multiple processors on a high performance system. Run times for these simulations have been tested to take hours or days however and simulating varying orientations is not always necessary. If a simulation with only one particle orientation is submitted, DDSCAT could still potentially parallelize the simulation by wavelength calculations but it is unknown if this is the case. In this paper, we will be (i) quantifying the reduction in computation time that MPI provides relative to an equivalent MPI disabled simulation …

Gecka3d: A 3d Game Engine For Commonsense Knowledge Acquisition, Erik Cambria, Tam Nguyen, Brian Cheng, Kenneth Kwok, Jose Sepulveda

Computer Science Faculty Publications

Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. In this paper, we introduce a novel 3D game engine for commonsense knowledge acquisition (GECKA3D) which aims to collect commonsense from game designers through the development of serious games. GECKA3D integrates the potential of serious games and games with a purpose. This provides a platform for the acquisition of reusable and multi-purpose knowledge and also enables the development of games that can provide entertainment value and …

Identification Of Small Endogenous Viral Elements Within Host Genomes, Edward C. Davis Jr.

Boise State University Theses and Dissertations

A parallel string matching software architecture has been developed (incorporating several algorithms) to identify small genetic sequences in large genomes. Endogenous viral elements (EVEs) are sequences originating in the genomes of viruses that have become integrated into the chromosomes of sperm or egg cells of infected hosts, and passed to subsequent generations. EVEs have been identified in all seven classes of viruses and in the species of all kingdoms of life. Viruses from groups V and VI are considered in this thesis, including HIV and Ebola, within host genomes ranging from bacteria to humans. This database of small endogenous viral …

A Study Of Android Malware Detection Techniques And Machine Learning, Balaji Baskaran, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Android OS is one of the widely used mobile Operating Systems. The number of malicious applications and adwares are increasing constantly on par with the number of mobile devices. A great number of commercial signature based tools are available on the market which prevent to an extent the penetration and distribution of malicious applications. Numerous researches have been conducted which claims that traditional signature based detection system work well up to certain level and malware authors use numerous techniques to evade these tools. So given this state of affairs, there is an increasing need for an alternative, really tough malware …

Extended Pixel Representation For Image Segmentation, Deeptha Girish, Vineeta Singh, Anca Ralescu

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We explore the use of extended pixel representation for color based image segmentation using the K-means clustering algorithm. Various extended pixel representations have been implemented in this paper and their results have been compared. By extending the representation of pixels an image is mapped to a higher dimensional space. Unlike other approaches, where data is mapped into an implicit features space of higher dimension (kernel methods), in the approach considered here, the higher dimensions are defined explicitly. Preliminary experimental results which illustrate the proposed approach are promising.

An Autonomic Computing System Based On A Rule-Based Policy Engine And Artificial Immune Systems, Rahmira Rufus, William Nick, Joseph Shelton, Albert Esterline

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

Autonomic computing systems arose from the notion that complex computing systems should have properties like those of the autonomic nervous system, which coordinates bodily functions and allows attention to be directed to more pressing needs. An autonomic system allows the system administrator to specify high-level policies, which the system maintains without administrator assistance. Policy enforcement can be done with a rule based system such as Jess (a java expert system shell). An autonomic system must be able to monitor itself, and this is often a limiting factor. We are developing an automatic system that has a policy engine and uses …

Towards The Development Of A Cyber Analysis & Advisement Tool (Caat) For Mitigating De-Anonymization Attacks, Siobahn Day, Henry Williams, Joseph Shelton, Gerry Dozier

MAICS: The Modern Artificial Intelligence and Cognitive Science Conference

We are seeing a rise in the number of Anonymous Social Networks (ASN) that claim to provide a sense of user anonymity. However, what many users of ASNs do not know that a person can be identified by their writing style.

In this paper, we provide an overview of a number of author concealment techniques, their impact on the semantic meaning of an author's original text, and introduce AuthorCAAT, an application for mitigating de-anonymization attacks. Our results show that iterative paraphrasing performs the best in terms of author concealment and performs well with respect to Latent Semantic Analysis.