OS and Networks Commons^™

Applying Grounded Theory Methods To Digital Forensics Research, Ahmed Almarzooqi, Andrew Jones, Richard Howley

Annual ADFSL Conference on Digital Forensics, Security and Law

Deciding on a suitable research methodology is challenging for researchers. In this paper, grounded theory is presented as a systematic and comprehensive qualitative methodology in the emergent field of digital forensics research. This paper applies grounded theory in a digital forensics research project undertaken to study how organisations build and manage digital forensics capabilities. This paper gives a step-by-step guideline to explain the procedures and techniques of using grounded theory in digital forensics research. The paper gives a detailed explanation of how the three grounded theory coding methods (open, axial, and selective coding) can be used in digital forensics research. …

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

Semantic, Cognitive, And Perceptual Computing: Paradigms That Shape Human Experience, Amit P. Sheth, Pramod Anantharam, Cory Henson

Kno.e.sis Publications

Unlike machine-centric computing, in which efficient data processing takes precedence over contextual tailoring, human-centric computation provides a personalized data interpretation that most users find highly relevant to their needs. The authors show how semantic, cognitive, and perceptual computing paradigms work together to produce actionable information.

Semantic Memory Modeling And Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Semantic memory plays a critical role in reasoning and decision making. It enables an agent to abstract useful knowledge learned from its past experience. Based on an extension of fusion adaptive resonance theory network, this paper presents a novel self-organizing memory model to represent and learn various types of semantic knowledge in a unified manner. The proposed model, called fusion adaptive resonance theory for multimemory learning, incorporates a set of neural processes, through which it may transfer knowledge and cooperate with other long-term memory systems, including episodic memory and procedural memory. Specifically, we present a generic learning process, under which …

Concurrent Compaction In Jvm Garbage Collection, Jacob P. Opdahl

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper provides a brief overview of both garbage collection (GC) of memory and parallel processing. We then cover how parallel processing applies to GC. Specifically, these concepts are focused within the context of the Java Virtual Machine (JVM). With that foundation, we look at various algorithms that perform compaction of fragmented memory during the GC process. These algorithms are designed to run concurrent to the application running. Such concurrently compacting GC behavior stems from a desire to reduce \stop-the-world" pauses of an application.

Robust Decision Making For Stochastic Network Design, Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon

Research Collection School Of Computing and Information Systems

We address the problem of robust decision making for stochastic network design. Our work is motivated by spatial conservation planning where the goal is to take management decisions within a fixed budget to maximize the expected spread of a population of species over a network of land parcels. Most previous work for this problem assumes that accurate estimates of different network parameters (edge activation probabilities, habitat suitability scores) are available, which is an unrealistic assumption. To address this shortcoming, we assume that network parameters are only partially known, specified via interval bounds. We then develop a decision making approach that …

Nlu Framework For Voice Enabling Non-Native Applications On Smart Devices, Soujanya Lanka, Deepika Panthania, Pooja Kushalappa, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Voice is a critical user interface on smart devices (wearables, phones, speakers, televisions) to access applications (or services) available on them. Unfortunately, only a few native applications (provided by the OS developer) are typically voice enabled in devices of today. Since, the utility of a smart device is determined more by the strength of external applications developed for the device, voice enabling non-native applications in a scalable, seamless manner within the device is a critical use case and is the focus of our work. We have developed a Natural Language Understanding (NLU) framework that uses templates supported by the application …

802.11ac Wireless Standard, Brent Marshall

A with Honors Projects

In this student paper, the author compares wireless standard 802.11ac to 802.11n standard. In 2011 the IEEE began development of the newest wireless 802.11 standard. This standard would be known as 802.11ac. Development of this standard continued until 2013 and was approved in January 2014. The new standard was touted as having many improvements over the 802.11n standard. Improvements such as higher data rates, more capacity, being ideal for multimedia, and being more robust.

A Study Of Social Web Data On Buprenorphine Abuse Using Semantic Web Technology, Raminta Daniulaityte, Amit P. Sheth

Kno.e.sis Publications

The Specific Aims of this application are to use a paradigmatic approach that combines Semantic Web technology, Natural Language Processing and Machine Learning techniques to:

1) Describe drug users’ knowledge, attitudes, and behaviors related to the non-medical use of Suboxone and Subutex as discussed on Web-based forums.
2) Identify and describe temporal patterns of non-medical use of Suboxone and Subutex as discussed on Web-based forums.

The research was carried out by an interdisciplinary team of members of the Center for Interventions, Treatment and Addictions Research (CITAR) and the Ohio Center of Excellence in Knowledge- enabled Computing (Kno.e.sis) at Wright State …

Building The Web Of Knowledge With Smart Iot Applications, Amelie Gyrard, Pankesh Patel, Amit P. Sheth, Martin Serrano

Kno.e.sis Publications

The Internet of Things (IoT) is experiencing fast adoption because of its positive impact to change all aspects of our lives, from agriculture in rural areas, to health and wellness, to smart home and smart-x applications in cities. The development of IoT applications and deployment of smart IoT-based solutions is just starting; smart IoT applications will modify our physical world and our interaction with cyber spaces, from how we remotely control appliances at home to how we care for patients or elderly persons. The massive deployment of IoT devices represents a tremendous economic impact and at the same time offers …

Co-Evolution Of Rdf Datasets, Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour, Sören Auer, Maria-Esther Vidal

Kno.e.sis Publications

Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, …

Secure And Authenticated Message Dissemination In Vehicular Ad Hoc Networks And An Incentive-Based Architecture For Vehicular Cloud, Kiho Lim

Theses and Dissertations--Computer Science

Vehicular ad hoc Networks (VANETs) allow vehicles to form a self-organized network. VANETs are likely to be widely deployed in the future, given the interest shown by industry in self-driving cars and satisfying their customers various interests. Problems related to Mobile ad hoc Networks (MANETs) such as routing, security, etc.have been extensively studied. Even though VANETs are special type of MANETs, solutions proposed for MANETs cannot be directly applied to VANETs because all problems related to MANETs have been studied for small networks. Moreover, in MANETs, nodes can move randomly. On the other hand, movement of nodes in VANETs are …

An Indicator Of Inclusion With Applications To Computer Vision, Florentin Smarandache, Ovidiu Ilie Sandru

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present an algorithmic process of necessary operations for the automatic movement of a predefined object from a video image in the target region of that image, intended to facilitate the implementation of specialized software applications in solving this kind of problems.

On The Limits And Practice Of Automatically Designing Self-Stabilization, Alex Klinkhamer

Dissertations, Master's Theses and Master's Reports

A protocol is said to be self-stabilizing when the distributed system executing it is guaranteed to recover from any fault that does not cause permanent damage. Designing such protocols is hard since they must recover from all possible states, therefore we investigate how feasible it is to synthesize them automatically. We show that synthesizing stabilization on a fixed topology is NP-complete in the number of system states. When a solution is found, we further show that verifying its correctness on a general topology (with any number of processes) is undecidable, even for very simple unidirectional rings. Despite these negative results, …

Maia And Mandos: Tools For Integrity Protection On Arbitrary Files, Paul J. Bonamy

Dissertations, Master's Theses and Master's Reports

We present the results of our dissertation research, which focuses on practical means of protecting system data integrity. In particular, we present Maia, a language for describing integrity constraints on arbitrary file types, and Mandos, a Linux Security Module which uses verify-on-close to enforce mandatory integrity guarantees. We also provide details of a Maia-based verifier generator, demonstrate that Maia and Mandos introduce minimal delay in performing their tasks, and include a selection of sample Maia specifications.