Computer Sciences Commons^™

On Identities In Modern Networks, Libor Polcak, Radek Hranick, Tomas Martınek

Journal of Digital Forensics, Security and Law

Communicating parties inside computer networks use different kind of identifiers. Some of these identifiers are stable, e.g., logins used to access a specific service, some are only temporary, e.g., dynamically assigned IP addresses. This paper tackles several challenges of lawful interception that emerged in modern networks. The main contribution is the graph model that links identities learnt from various sources distributed in a network. The inferred identities result into an interception of more detailed data in conformance with the issued court order. The approach deals with network address translation, short-lived identifiers and simultaneous usage of different identities. The approach was …

Exploring Forensic Implications Of The Fusion Drive, Shruti Gupta, Marcus Rogers

Journal of Digital Forensics, Security and Law

This paper explores the forensic implications of Apple’s Fusion Drive. The Fusion Drive is an example of auto-tiered storage. It uses a combination of a flash drive and a magnetic drive. Data is moved between the drives automatically to maximize system performance. This is different from traditional caches because data is moved and not simply copied. The research included understanding the drive structure, populating the drive, and then accessing data in a controlled setting to observe data migration strategies. It was observed that all the data is first written to the flash drive with 4 GB of free space always …

Multi-Stakeholder Case Prioritization In Digital Investigations, Joshua I. James

Journal of Digital Forensics, Security and Law

This work examines the problem of case prioritization in digital investigations for better utilization of limited criminal investigation resources. Current methods of case prioritization, as well as observed prioritization methods used in digital forensic investigation laboratories are examined. After, a multi-stakeholder approach to case prioritization is given that may help reduce reputational risk to digital forensic laboratories while improving resource allocation. A survey is given that shows differing opinions of investigation priority between Law Enforcement and the public that is used in the development of a prioritization model. Finally, an example case is given to demonstrate the practicality of the …

An Efficient Similarity Digests Database Lookup – A Logarithmic Divide & Conquer Approach, Frank Breitinger, Christian Rathgeb, Harald Baier

Journal of Digital Forensics, Security and Law

Investigating seized devices within digital forensics represents a challenging task due to the increasing amount of data. Common procedures utilize automated file identification, which reduces the amount of data an investigator has to examine manually. In the past years the research field of approximate matching arises to detect similar data. However, if n denotes the number of similarity digests in a database, then the lookup for a single similarity digest is of complexity of O(n). This paper presents a concept to extend existing approximate matching algorithms, which reduces the lookup complexity from O(n) to O(log(n)). Our proposed approach is based …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

From The Editor, Ibrahim Baggili

Journal of Digital Forensics, Security and Law

In this issue we have three papers that have made the cut. The first paper titled “The Cost of Privacy: Riley v. California’s Impact on Cell Phone Searches” is timely. In 2014 there was a unanimous decision that requires a warrant for all cell phone searches. This has some strong implications on the forensic analysis of mobile phones, and to that end, this article discusses and summarizes this legal precedent with its practical implications.

Leveraging Decentralization To Extend The Digital Evidence Acquisition Window: Case Study On Bittorrent Sync, Mark Scanlon, Jason Farina, Nhien A. Khac, Tahar Kechadi

Journal of Digital Forensics, Security and Law

File synchronization services such as Dropbox, Google Drive, Microsoft OneDrive, Apple iCloud, etc., are becoming increasingly popular in today’s always-connected world. A popular alternative to the aforementioned services is BitTorrent Sync. This is a decentralized/cloudless file synchronization service and is gaining significant popularity among Internet users with privacy concerns over where their data is stored and who has the ability to access it. The focus of this paper is the remote recovery of digital evidence pertaining to files identified as being accessed or stored on a suspect’s computer or mobile device. A methodology for the identification, investigation, recovery and verification …

Book Review: The X-Ways Forensics Practitioner's Guide, Linda Lau

Journal of Digital Forensics, Security and Law

Brett Shavers is a former law enforcement officer, a digital forensics examiner, an adjunct instructor, and a frequent speaker at many conferences. After writing his first book, titled Placing the Suspect Behind the Keyboard: Using Digital Forensics and Investigative Techniques to Identify Cybercrime Suspects, he co-wrote his 2nd book with Eric Zimmerman and Jimmy Weg, who is a knowledgeable technical editor. Both Brett and Eric are experts in cyber forensics, with many years of law enforcement experience at both the state and federal levels.

The Cost Of Privacy: Riley V. California’S Impact On Cell Phone Searches, Jennifer L. Moore, Jonathan Langton, Joseph Pochron

Journal of Digital Forensics, Security and Law

Riley v. California is the United States Supreme Court’s first attempt to regulate the searches of cell phones by law enforcement. The 2014 unanimous decision requires a warrant for all cell phone searches incident to arrest absent an emergency. This work summarizes the legal precedent and analyzes the limitations and practical implications of the ruling. General guidelines for members of the criminal justice system at all levels consistent with the Supreme Court’s decision are provided.

Quantifying Relevance Of Mobile Digital Evidence As They Relate To Case Types: A Survey And A Guide For Best Practice, Shahzad Saleem, Ibrahim Baggili, Oliver Popov

Journal of Digital Forensics, Security and Law

In this work, a survey was conducted to help quantify the relevance of nineteen types of evidence (such as SMS) to seven types of digital investigations associated with mobile devices (MD) (such as child pornography). 97 % of the respondents agreed that every type of digital evidence has a different level of relevance to further or solve a particular investigation. From 55 serious participants, a dataset of 5,772 responses regarding the relevance of nineteen types of digital evidence for all the seven types of digital investigations was obtained. The results showed that (i) SMS belongs to the most relevant type …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Developing A Conceptual Framework For Modeling Deviant Cyber Flash Mob: A Socio-Computational Approach Leveraging Hypergraph Constructs, Samer Al-Khateeb, Nitin Agarwal

Journal of Digital Forensics, Security and Law

In a Flash Mob (FM) a group of people get together in the physical world perform an unpredicted act and disperse quickly. Cyber Flash Mob (CFM) is the cyber manifestation of flash mob coordinated primarily using social media. Deviant Cyber Flash Mob (or, DCFM) is a special case of CFM, which is categorized as the new face of transnational crime organizations (TCOs). The DCFM phenomenon can be considered as a form of a cyber-collective action that is defined as an action aiming to improve group’s conditions (such as, status or power). In this paper, we conduct a conceptual analysis of …

Intelligent Sensing Based On Low Cost Unmanned Aerial Vehicles (Uav) For Bridge Condition Assessment, Theodore Teates, Austin Boyd, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The eventual completion of this project envisions the use of an Unmanned Aerial Vehicle (UAV) to inspect bridge infrastructure. This project may also be expanded to encompass general object detection and inspection in order to unburden this technology so that it may reach its fullest potential. The project requires research and development in three distinct areas of image processing, control structures, and integration of systems. Initial undergraduate research sets the base knowledge for the overall project, explores the areas of concentration that are desired to expand upon in the future project, and provides a base UAV model that new researchers …

Sensor Selection And Integration To Improve Video Segmentation In Complex Environments, Adam R. Reckley, Wei-Wen Hsu, Chung-Hao Chen, Gangfeng Ma, E-Wen Huang

Electrical & Computer Engineering Faculty Publications

Background subtraction is often considered to be a required stage of any video surveillance system being used to detect objects in a single frame and/or track objects across multiple frames in a video sequence. Most current state-of-the-art techniques for object detection and tracking utilize some form of background subtraction that involves developing a model of the background at a pixel, region, or frame level and designating any elements that deviate from the background model as foreground. However, most existing approaches are capable of segmenting a number of distinct components but unable to distinguish between the desired object of interest and …

Neutrosophic Logic Approaches Applied To ”Rabot” Real Time Control, Alexandru Gal, Luige Vladareanu, Florentin Smarandache, Hongnian Yu, Mincong Deng

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present a way of deciding which control law should operate at a time for a mobile walking robot. The proposed deciding method is based on the new research field, called Neutrosophic Logic. The results are presented as a simulated system for which the output is related to the inputs according to the Neutrosophic Logic.

Scale-Up And On-Line Monitoring Of Gas-Solid Systems Using Advanced And Non-Invasive Measurement Techniques, Muthanna H. Al-Dahhan, Shreekanta Aradhya, Faraj Zaid, Neven Ali, Thaar Aljuwaya

Chemical and Biochemical Engineering Faculty Research & Creative Works

Industry relies on gas-solid systems for numerous processes. Flow dynamics play an important role in achieving the desired results. The present study proposes, validates and demonstrates a novel mechanistic scale-up approach based on maintaining similar radial profile or cross sectional distribution of gas holdup in two different gas-solid systems in order to achieve hydrodynamics similarity using advanced measurement techniques. This new methodology for scale-up and design has been implemented on gas-solid spouted bed which has been used for drying, granulation and coating. The development can be extrapolated to other gas-solid systems encountered in phosphate processes.

An Online Outlier Identification And Removal Scheme For Improving Fault Detection Performance, Hasan Ferdowsi, Sarangapani Jagannathan, Maciej Jan Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be …

Building A Scalable And High-Performance Key-Value Store System, Yuehai Xu

Wayne State University Dissertations

Contemporary web sites can store and process very large amounts of data. To provide timely service to their users, they have adopted key-value (KV) stores, which is a simple but effective caching infrastructure atop the conventional databases that store these data, to boost performance. Examples are Facebook, Twitter and Amazon. As yet little is known about the realistic workloads outside of the companies that operate them, this dissertation work provides a detailed workload study on Facebook's Memcached, which is one of the world's largest KV deployment. We analyze the Memcached workload from the perspective of server-side performance, request composition, caching …

The Design, Analysis, & Application Of Multi-Modal Real-Time Embedded Systems, Masud Ahmed

Wayne State University Dissertations

For many hand-held computing devices (e.g., smartphones), multiple operational modes are preferred because of their flexibility. In addition to their designated purposes, some of these devices provide a platform for different types of services, which include rendering of high-quality multimedia. Upon such devices, temporal isolation among co-executing applications is very important to ensure that each application receives an acceptable level of quality-of-service. In order to provide strong guarantees on services, multimedia applications and real-time control systems maintain timing constraints in the form of deadlines for recurring tasks. A flexible real-time multi-modal system will ideally provide system designers the option to …

A Decision Making Tool For Sustainable Design In Construction, Enda Collins

Theses

This report defines sustainability and sustainable development before any research is carried out. This is necessary so that the research carried out further in the report makes sense and there is a reason for including such items in this report. The need for this project and what the project aims to achieve is also highlighted in the introduction of this report.

Sustainability is made up of three equal parts; social, economic and environmental. This report goes through each item and gives examples of each type of development. Having discussed sustainability in a broad sense the report then focuses on Legislation …

Solving A New Bi-Objective Joint Replenishment Inventory Model With Modified Rand And Genetic Algorithms, Ommolbanin Yousefi, Seyed Jafar Sadjadi

Turkish Journal of Electrical Engineering and Computer Sciences

There are many cases in real inventory systems where more than one objective must be optimized. The main purpose of this research is to develop a multiobjective joint replenishment problem (JRP), where one objective is the minimization of the total inventory investment and another is the minimization of the total inventory ordering and holding costs. To solve the suggested model, 3 algorithms are proposed. In the first algorithm, the existing RAND method, called the best heuristic for solving the JRP, is modified and a new heuristic algorithm is developed to be applicable to the JRP with 2 objectives. The second …

Contrast Enhancement Using Linear Image Combinations Algorithm (Ceulica) For Enhancing Brain Magnetic Resonance Images, Burak Yilmaz, Yüksel Özbay

Turkish Journal of Electrical Engineering and Computer Sciences

Brain magnetic resonance imaging (MRI) images support important information about brain diseases for physicians. Morphological alterations in brain tissues indicate the probable existence of a disease in many cases. Proper estimation of these tissues, measuring their sizes, and analyzing their image patterns are parts of the diagnosis process. Therefore, the interpretability and perceptibility level of the MRI image is valuable for physicians. In this paper, a new image contrast enhancement algorithm based on linear combinations is presented. The proposed algorithm is focused on improving the interpretability and perceptibility of the image information. An MRI image is presented to the algorithm, …

Online Feature Selection And Classification With Incomplete Data, Habi̇l Kalkan

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a classification system in which learning, feature selection, and classification for incomplete data are simultaneously carried out in an online manner. Learning is conducted on a predefined model including the class-dependent mean vectors and correlation coefficients, which are obtained by incrementally processing the incoming observations with missing features. A nearest neighbor with a Gaussian mixture model, whose parameters are also estimated from the trained model, is used for classification. When a testing observation is received, the algorithm discards the missing attributes on the observation and ranks the available features by performing feature selection on the model that …

Model-Free Controller With An Observer Applied In Real-Time To A 3-Dof Helicopter, Ahsene Boubakir, Salim Labiod, Fares Boudjema, Franck Plestan

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a model-free controller with an observer is presented for a class of uncertain continuous-time multiinput-multioutput nonlinear dynamic systems. The proposed model-free control law consists of 2 parts: the first part is a linear control term used to specify the dynamics of the closed loop system, and the second part is a compensator of the effects of uncertainties and external disturbances. The compensator is synthesized from an estimator of the effects of uncertainties and disturbances based on the Lyapunov approach. In order to estimate the unavailable states of the controlled system, a linear state observer is designed. All …

A User-Oriented Network Forensic Analyser: The Design Of A High-Level Protocol Analyser, D Joy, F Li, N L. Clarke, S M. Furnell

Australian Digital Forensics Conference

Network forensics is becoming an increasingly important tool in the investigation of cyber and computer-assisted crimes. Unfortunately, whilst much effort has been undertaken in developing computer forensic file system analysers (e.g. Encase and FTK), such focus has not been given to Network Forensic Analysis Tools (NFATs). The single biggest barrier to effective NFATs is the handling of large volumes of low-level traffic and being able to exact and interpret forensic artefacts and their context – for example, being able extract and render application-level objects (such as emails, web pages and documents) from the low-level TCP/IP traffic but also understand how …

Combating Integrity Attacks In Industrial Control Systems, Chad Arnold

Browse all Theses and Dissertations

Industrial Control Systems are vulnerable to integrity attacks because of connectivity to the external Internet and trusted internal networking components that can become compromised. Integrity attacks can be modeled, analyzed, and sometimes remedied by exploiting properties of physical devices and reasoning about the trust worthiness of ICS communication components.

Industrial control systems (ICS) monitor and control the processes of public utility that society depends on - the electric power grid, oil and gas pipelines, transportation, and water facilities. Attacks that impact the operations of these critical assets could have devastating consequences. The complexity and desire to interconnect ICS components have …

A Novel Synergistic Model Fusing Electroencephalography And Functional Magnetic Resonance Imaging For Modeling Brain Activities, Konstantinos Michalopoulos

Browse all Theses and Dissertations

Study of the human brain is an important and very active area of research. Unraveling the way the human brain works would allow us to better understand, predict and prevent brain related diseases that affect a significant part of the population. Studying the brain response to certain input stimuli can help us determine the involved brain areas and understand the mechanisms that characterize behavioral and psychological traits.

In this research work two methods used for the monitoring of brain activities, Electroencephalography (EEG) and functional Magnetic Resonance (fMRI) have been studied for their fusion, in an attempt to bridge together the …

Automated Complexity-Sensitive Image Fusion, Brian Patrick Jackson

Browse all Theses and Dissertations

To construct a complete representation of a scene with environmental obstacles such as fog, smoke, darkness, or textural homogeneity, multisensor video streams captured in diferent modalities are considered. A computational method for automatically fusing multimodal image streams into a highly informative and unified stream is proposed. The method consists of the following steps: 1. Image registration is performed to align video frames in the visible band over time, adapting to the nonplanarity of the scene by automatically subdividing the image domain into regions approximating planar patches

2. Wavelet coefficients are computed for each of the input frames in each modality …

The Properties Of Property Alignment On The Semantic Web, Michelle Andreen Cheatham

Browse all Theses and Dissertations

Ontology alignment is an important step in enabling computers to query and reason across the many linked datasets on the semantic web. This is a difficult challenge because the ontologies underlying different linked datasets can vary in terms of subject area coverage, level of abstraction, ontology modeling philosophy, and even language. The alignment approach presented here centers on string similarity metrics. Nearly all ontology alignment systems use a string similarity metric in one form or another, but it seems that the choice of a particular metric is often arbitrary. We begin this dissertation with the most comprehensive survey to date …

A Decision Framework For Optimal Pairing Of Wind And Demand Response Resources, C. Lindsay Anderson, Judith Cardell

Engineering: Faculty Publications

Day-ahead electricity markets do not readily accommodate power from intermittent resources such as wind because of the scheduling difficulties presented by the uncertainty and variability in these resources. Numerous entities have developed methods to improve wind forecasting and thereby reduce the uncertainty in a day-ahead schedule for wind power generation. This paper introduces a decision framework for addressing the inevitable remaining variability resulting from imperfect forecasts. The framework uses a paired resource, such as demand response, gas turbine, or storage, to mitigate the generation scheduling errors due to wind forecast error. The methodology determines the cost-effective percentage, or adjustment factor, …