OS and Networks Commons^™

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 …

A Partial Replication Load Balancing Technique For Distributed Data As A Service On The Cloud, Klaithem Saeed Al Nuaimi

Dissertations

Data as a service (DaaS) is an important model on the Cloud, as DaaS provides clients with different types of large files and data sets in fields like finance, science, health, geography, astronomy, and many others. This includes all types of files with varying sizes from a few kilobytes to hundreds of terabytes. DaaS can be implemented and provided using multiple data centers located at different locations and usually connected via the Internet. When data is provided using multiple data centers it is referred to as distributed DaaS. DaaS providers must ensure that their services are fast, reliable, and efficient. …

Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua

Computer Science Faculty Publications

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …

Secure And Reliable Routing Protocol For Transmission Data In Wireless Sensor Mesh Networks, Nooh Adel Bany Muhammad

Dissertations

Abstract

Sensor nodes collect data from the physical world then exchange it until it reaches the intended destination. This information can be sensitive, such as battlefield surveillance. Therefore, providing secure and continuous data transmissions among sensor nodes in wireless network environments is crucial. Wireless sensor networks (WSN) have limited resources, limited computation capabilities, and the exchange of data through the air and deployment in accessible areas makes the energy, security, and routing major concerns in WSN. In this research we are looking at security issues for the above reasons. WSN is susceptible to malicious activities such as hacking and physical …

A Nested Recursive Logit Model For Route Choice Analysis, Tien Mai, Mogens Fosgerau, Emma Frejinger

Research Collection School Of Computing and Information Systems

We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination. The value …

Measuring Centralities For Transportation Networks Beyond Structures, Yew-Yih Cheng, Lee Ka Wei, Roy, Ee-Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with the network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of …

Big Data And Smart Cities, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Gaussian Weighted Neighborhood Connectivity Of Nonlinear Line Attractor For Learning Complex Manifolds, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Electrical and Computer Engineering Faculty Publications

The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA …

Context-Driven Automatic Subgraph Creation For Literature-Based Discovery, Delroy H. Cameron, Ramakanth Kavuluru, Thomas Rindflesch, Amit P. Sheth, Krishnaprasad Thirunarayan, Olivier Bodenreider

Kno.e.sis Publications

Background: Literature-based discovery (LBD) is characterized by uncovering hidden associations in non-interacting scientific literature. Prior approaches to LBD include use of: 1) domain expertise and structured background knowledge to manually filter and explore the literature, 2) distributional statistics and graph-theoretic measures to rank interesting connections and 3) heuristics to help eliminate spurious connections. However, manual approaches to LBD are not scalable and purely distributional approaches may not be sufficient to obtain insights into the meaning of poorly understood associations. While several graph-based approaches have the potential to elucidate associations, their effectiveness has not been fully demonstrated. A considerable degree of …

Towards An Integrated Model Of The Mental Lexicon, Natawut Monaikul

All Student Theses and Dissertations

Several models have been proposed attempting to describe the mental lexicon-the abstract organization of words in the human mind. Numerous studies have shown that by representing the mental lexicon as a network, where nodes represent words and edges connect similar words using a metric based on some word feature, a small-world structure is formed. This property, pervasive in many real-world networks, implies processing efficiency and resiliency to node deletion within the system, explaining the need for such a robust network as the mental lexicon. However, each model considered a single word feature at a time, such as semantic or phonological …

Memory Dynamics In Attractor Networks, Guoqi Li, Kiruthika Ramanathan, Ning Ning, Luping Shi, Changyun Wen

Research Collection School Of Computing and Information Systems

As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this paper, we propose a new energy function, which is nonnegative and attains zero values only at the desired memory patterns. An attractor network is designed based on the proposed energy function. It is shown that the desired memory patterns are stored as the stable equilibrium points of the attractor network. To retrieve a memory pattern, an initial stimulus input is presented …

Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen

Computer Science Faculty Publications

People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …