OS and Networks Commons^™

Towards A Robust Sparse Data Representation In Wireless Sensor Networks, Abu Alsheik Mohammad, Shaowei Lin, Hwee-Pink Tan, Dusit Niyato

Research Collection School Of Computing and Information Systems

Compressive sensing has been successfully used for optimized operations in wireless sensor networks. However, raw data collected by sensors may be neither originally sparse nor easily transformed into a sparse data representation. This paper addresses the problem of transforming source data collected by sensor nodes into sparse representation with a few nonzero elements. Our contributions that address three major issues include: 1) an effective method that extracts population sparsity of the data, 2) a sparsity ratio guarantee scheme, and 3) a customized leaerning algorithm of the sparsifying dictionary. We introduce an unsupervised neural network to extract an intrinsic sparse coding …

Scalable Euclidean Embedding For Big Data, Zohreh S. Alavi, Sagar Sharma, Lu Zhou, Keke Chen

Kno.e.sis Publications

Euclidean embedding algorithms transform data defined in an arbitrary metric space to the Euclidean space, which is critical to many visualization techniques. At big-data scale, these algorithms need to be scalable to massive dataparallel infrastructures. Designing such scalable algorithms and understanding the factors affecting the algorithms are important research problems for visually analyzing big data. We propose a framework that extends the existing Euclidean embedding algorithms to scalable ones. Specifically, it decomposes an existing algorithm into naturally parallel components and non-parallelizable components. Then, data parallel implementations such as MapReduce and data reduction techniques are applied to the two categories of …

An Apache Hadoop Framework For Large-Scale Peptide Identification, Harinivesh Donepudi

Masters Theses & Specialist Projects

Peptide identification is an essential step in protein identification, and Peptide Spectrum Match (PSM) data set is huge, which is a time consuming process to work on a single machine. In a typical run of the peptide identification method, PSMs are positioned by a cross correlation, a statistical score, or a likelihood that the match between the trial and hypothetical is correct and unique. This process takes a long time to execute, and there is a demand for an increase in performance to handle large peptide data sets. Development of distributed frameworks are needed to reduce the processing time, but …

Evaluating A Potential Commercial Tool For Healthcare Application For People With Dementia, Tanvi Banerjee, Pramod Anantharam, William L. Romine, Larry Wayne Lawhorne

Kno.e.sis Publications

The widespread use of smartphones and sensors has made physiology, environment, and public health notifications amenable to continuous monitoring. Personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context, converting relevant medical knowledge into actionable information for better and timely decisions. We apply these principles in the healthcare domain of dementia. Specifically, in this study we validate one of our sensor platforms to ascertain whether it will be suitable for detecting physiological changes that may help us detect changes in people with dementia. This study shows …

Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel

Computer Science Faculty Publications

Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him- or herself. In the field of speech language pathology, the approach of VSM has been successfully used for treatment of language in children with Autism and in individuals with fluency disorder of stuttering. Technical challenges remain in creating VSM contents that depict previously unseen behaviors. In this paper, we propose a novel system that synthesizes new video sequences for VSM treatment of patients with voice disorders. Starting with a video recording of a voice-disorder patient, the proposed …

Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni

Kno.e.sis Publications

With the advent of the web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these online services to share and seek health real-time information has in- creased exponentially. OHIS use web search engines or microblogging search services to seek out latest, relevant as well as reliable health in- formation. When OHIS turn to microblogging search services to search real-time content, trends and breaking news, etc. the search results are not promising. Two major challenges exist in the current microblogging search engines are keyword based techniques and results do not contain real-time information. To address these challenges, …

"Time For Dabs": Analyzing Twitter Data On Butane Hash Oil Use, Raminta Daniulaityte, Robert G. Carlson, Farahnaz Golroo, Sanjaya Wijeratne, Edward W. Boyer, Silvia S. Martins, Ramzi W. Nahhas, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Trust Management: Multimodal Data Perspective, Krishnaprasad Thirunarayan

Kno.e.sis Publications

No abstract provided.

Replica Placement For Availability In The Worst Case, Peng Li, Debin Gao, Mike Reiter

Research Collection School Of Computing and Information Systems

We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects which nodes to fail to minimize the number of objects that remain available. We specifically explore placement strategies based on combinatorial structures called t-packings; provide a lower bound for the object availability they offer; show that these placements offer availability that is c-competitive with optimal; propose an efficient algorithm for computing …

Entity Recommendations Using Hierarchical Knowledge Bases, Siva Kumar Cheekula, Pavan Kapanipathi, Derek Doran, Prateek Jain, Amit P. Sheth

Kno.e.sis Publications

Recent developments in recommendation algorithms have focused on integrating Linked Open Data to augment traditional algorithms with background knowledge. These developments recognize that the integration of Linked Open Data may or better performance, particularly in cold start cases. In this paper, we explore if and how a specific type of Linked Open Data, namely hierarchical knowledge, may be utilized for recommendation systems. We propose a content-based recommendation approaches that adapts a spreading activation algorithm over the DBpedia category structure to identify entities of interest to the user. Evaluation of the algorithm over the Movielens dataset demonstrates that our method yields …

Tracking Criminals On Facebook: A Case Study From A Digital Forensics Reu Program, Daniel Weiss, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

The 2014 Digital Forensics Research Experience for Undergraduates (REU) Program at the University of Alabama at Birmingham (UAB) focused its summer efforts on tracking criminal forums and Facebook groups. The UAB-REU Facebook team was provided with a list of about 60 known criminal groups on Facebook, with a goal to track illegal information posted in these groups and ultimately store the information in a searchable database for use by digital forensic analysts. Over the course of about eight weeks, the UAB-REU Facebook team created a database with over 400 Facebook groups conducting criminal activity along with over 100,000 unique users …

Towards A Digital Forensics Competency-Based Program: Making Assessment Count, Rose Shumba

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper describes an approach that UMUC has initiated to revise its graduate programs to a Competency-Based Education (CBE) curriculum. The approach, which is Learning Demonstration (LD) centric, includes the identification of learning goals and competences, identification and description of the LDs, mapping of the LDs to the competences, scripting the LDs, placing the LDs into the respective courses, validating the developed materials, and the development of the open learning resources. Programs in the Cybersecurity and Information Assurance Department, including the Digital Forensics and Cyber Investigations program, are being revised. An LD centric approach to curriculum development helps align programs …

Phishing Intelligence Using The Simple Set Comparison Tool, Jason Britt, Alan Sprague, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

Phishing websites, phish, attempt to deceive users into exposing their passwords, user IDs, and other sensitive information by imitating legitimate websites, such as banks, product vendors, and service providers. Phishing investigators need fast automated tools to analyze the volume of phishing attacks seen today. In this paper, we present the Simple Set Comparison tool. The Simple Set Comparison tool is a fast automated tool that groups phish by imitated brand allowing phishing investigators to quickly identify and focus on phish targeting a particular brand. The Simple Set Comparison tool is evaluated against a traditional clustering algorithm over a month's worth …

Identifying Common Characteristics Of Malicious Insiders, Nan Liang, David Biros

Annual ADFSL Conference on Digital Forensics, Security and Law

Malicious insiders account for large proportion of security breaches or other kinds of loss for organizations and have drawn attention of both academics and practitioners. Although methods and mechanism have been developed to monitor potential insider via electronic data monitoring, few studies focus on predicting potential malicious insiders. Based on the theory of planned behavior, certain cues should be observed or expressed when an individual performs as a malicious insider. Using text mining to analyze various media content of existing insider cases, we strive to develop a method to identify crucial and common indicators that an individual might be a …

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

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 …

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. …

Domain Specific Document Retrieval Framework On Near Real-Time Social Health Data, Swapnil Soni

Kno.e.sis Publications

With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …

Analyzing The Social Media Footprint Of Street Gangs, Sanjaya Wijeratne, Derek Doran, Amit P. Sheth, Jack Dustin

Kno.e.sis Publications

Gangs utilize social media as a way to maintain threatening virtual presences, to communicate about their activities, and to intimidate others. Such usage has gained the attention of many justice service agencies that wish to create better crime prevention and judicial services. However, these agencies use analysis methods that are labor intensive and only lead to basic, qualitative data interpretations. This paper presents the architecture of a modern platform to discover the structure, function, and operation of gangs through the lens of social media. Preliminary analysis of social media posts shared in the greater Chicago, IL region demonstrate the platform’s …

Self-Organizing Neural Networks Integrating Domain Knowledge And Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Jacek M. Zurada

Research Collection School Of Computing and Information Systems

The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforcement learning (RL), domain knowledge cannot be inserted directly. In this paper, we show how self-organizing neural networks designed for online and incremental adaptation can integrate domain knowledge and RL. Specifically, symbol-based domain knowledge is translated into numeric patterns before inserting into the self-organizing neural networks. To ensure effective use of domain knowledge, we present an analysis of how the inserted knowledge is used by …