Information Security Commons^™

Evaluating The Impacts Of Detecting X.509 Covert Channels, Cody Welu

Masters Theses & Doctoral Dissertations

This quasi-experimental before-and-after study examined the performance impacts of detecting X.509 covert channels in the Suricata intrusion detection system. Relevant literature and previous studies surrounding covert channels and covert channel detection, X.509 certificates, and intrusion detection system performance were evaluated. This study used Jason Reaves’ X.509 covert channel proof of concept code to generate malicious network traffic for detection (2018). Various detection rules for intrusion detection systems were created to aid in the detection of the X.509 covert channel. The central processing unit (CPU) and memory utilization impacts that each rule had on the intrusion detection system was studied and …

Cs04all: Cryptography Module, Hunter R. Johnson

Open Educational Resources

Cryptography module

This archive contains a series of lessons on cryptography suitable for use in a CS0 course. The only requirement is familiarity with Python, particularly dictionaries, lists, and file IO. It is also assumed that students know how to create stand-alone Python programs and interact with them through the terminal. Most of the work is done in Jupyter notebooks.

The material found in the notebooks is a combination of reading material, exercises, activities and assignments. Below are descriptions of each lesson or assignment and links to notebooks on Cocalc. The same files are available for batch download in this …

Image-Based Malware Classification: A Space Filling Curve Approach, Stephen O Shaughnessy

Conference Papers

Anti-virus (AV) software is effective at distinguishing between benign and malicious programs yet lack the ability to effectively classify malware into their respective family classes. AV vendors receive considerably large volumes of malicious programs daily and so classification is crucial to quickly identify variants of existing malware that would otherwise have to be manually examined. This paper proposes a novel method of visualizing and classifying malware using Space-Filling Curves (SFC's) in order to improve the limitations of AV tools. The classification models produced were evaluated on previously unseen samples and showed promising results, with precision, recall and accuracy scores of …

Virtual Hearings And Blockchain Technology Solutions In Criminal Law, Chantell Bergquist

Political Science Theses and Capstones

Technology has evolved and raided our personal and professional lives. Although the courts are not immune to the advancement and integration of technology, the courts are not keeping up with relevant technological advancements. Historically, courts have been hesitant to embrace new technologies despite the Federal Rules of Civil Procedure and the American Bar Association Model Rules of Professional Conduct. Rule 1 of the Federal Rules of Civil Procedure creates the right to a “just, speedy, and inexpensive determination of every action and proceeding.” Likewise, the American Bar Association Model Rules of Professional Conduct have determined attorneys must “keep abreast of …

Agent-Based Iot Coordination For Smart Cities Considering Security And Privacy, Iván García-Magariño, Geraldine Gray, Rajarajan Muttukrishnan, Waqar Asif

Conference papers

The interest in Internet of Things (IoT) is increasing steeply, and the use of their smart objects and their composite services may become widespread in the next few years increasing the number of smart cities. This technology can benefit from scalable solutions that integrate composite services of multiple-purpose smart objects for the upcoming large-scale use of integrated services in IoT. This work proposes an agent-based approach for supporting large-scale use of IoT for providing complex integrated services. Its novelty relies in the use of distributed blackboards for implicit communications, decentralizing the storage and management of the blackboard information in the …

Towards Secure And Fair Iiot-Enabled Supply Chain Management Via Blockchain-Based Smart Contracts, Amal Eid Alahmadi

Theses and Dissertations (Comprehensive)

Integrating the Industrial Internet of Things (IIoT) into supply chain management enables flexible and efficient on-demand exchange of goods between merchants and suppliers. However, realizing a fair and transparent supply chain system remains a very challenging issue due to the lack of mutual trust among the suppliers and merchants. Furthermore, the current system often lacks the ability to transmit trade information to all participants in a timely manner, which is the most important element in supply chain management for the effective supply of goods between suppliers and the merchants. This thesis presents a blockchain-based supply chain management system in the …

Evaluation And Understandability Of Face Image Quality Assessment, Mohammad I. Nouyed

Graduate Theses, Dissertations, and Problem Reports (ETD)

Face image quality assessment (FIQA) has been an area of interest to researchers as a way to improve the face recognition accuracy. By filtering out the low quality images we can reduce various difficulties faced in unconstrained face recognition, such as, failure in face or facial landmark detection or low presence of useful facial information. In last decade or so, researchers have proposed different methods to assess the face image quality, spanning from fusion of quality measures to using learning based methods. Different approaches have their own strength and weaknesses. But, it is hard to perform a comparative assessment of …

Intra-Exchange Cryptocurrency Arbitrage Bot, Eric Han

Master's Projects

Cryptocurrencies are defined as a digital currency in which encryption techniques are utilized to regulate generation of units of currency and verify the transfer of funds, independent of a central governing body such as a bank. Due to the large number of cryptocurrencies currently available, there inherently exists many price discrepancies due to market inefficiencies. Market inefficiencies occur when the price of assets do not reflect their true value. In fact, these types of pricing discrepancies exist in other financial markets, including fiat currency exchanges and stock exchanges. However, these discrepancies are more significant in the cryptocurrency domain due to …

Rationality And Efficient Verifiable Computation, Matteo Campanelli

Dissertations, Theses, and Capstone Projects

In this thesis, we study protocols for delegating computation in a model where one of the parties is rational. In our model, a delegator outsources the computation of a function f on input x to a worker, who receives a (possibly monetary) reward. Our goal is to design very efficient delegation schemes where a worker is economically incentivized to provide the correct result f(x). In this work we strive for not relying on cryptographic assumptions, in particular our results do not require the existence of one-way functions.

We provide several results within the framework of rational proofs introduced by Azar …

Building Test Anonymity Networks In A Cybersecurity Lab Environment, John Schriner

Student Theses

This paper explores current methods for creating test anonymity networks in a laboratory environment for the purpose of improving these networks while protecting user privacy. We first consider how each of these networks is research-driven and interested in helping researchers to conduct their research ethically. We then look to the software currently available for researchers to set up in their labs. Lastly we explore ways in which digital forensics and cybersecurity students could get involved with these projects and look at several class exercises that help students to understand particular attacks on these networks and ways they can help to …

Social Engineering In Non-Linear Warfare, Bill Gardner

Journal of Applied Digital Evidence

This paper explores the use of hacking, leaking, and trolling by Russia to influence the 2016 United States Presidential Elections. These tactics have been called “the weapons of the geek” by some researchers. By using proxy hackers and Russian malware to break into the email of the Democratic National Committee and then giving that email to Wikileaks to publish on the Internet, the Russian government attempted to swing the election in the favor of their preferred candidate.

The source of the malware used in the DNC hack was determined to be of Russian in nature and has been used on …

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Analysis Of Data Erasure Capability On Sshd Drives For Data Recovery, Andrew Blyth

Annual ADFSL Conference on Digital Forensics, Security and Law

Data Protection and Computer Forensics/Anti-Forensics has now become a critical area of concern for organizations. A key element to this is how data is sanitized at end of life. In this paper we explore Hybrid Solid State Hybrid Drives (SSHD) and the impact that various Computer Forensics and Data Recovery techniques have when performing data erasure upon a SSHD.

Knowledge Expiration In Security Awareness Training, Tianjian Zhang

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Positive Identification Of Lsb Image Steganography Using Cover Image Comparisons, Michael Pelosi, Nimesh Poudel, Pratap Lamichhane, Devon Lam, Gary Kessler, Joshua Macmonagle

Annual ADFSL Conference on Digital Forensics, Security and Law

In this paper we introduce a new software concept specifically designed to allow the digital forensics professional to clearly identify and attribute instances of LSB image steganography by using the original cover image in side-by-side comparison with a suspected steganographic payload image. The “CounterSteg” software allows detailed analysis and comparison of both the original cover image and any modified image, using sophisticated bit- and color-channel visual depiction graphics. In certain cases, the steganographic software used for message transmission can be identified by the forensic analysis of LSB and other changes in the payload image. The paper demonstrates usage and typical …

Exploring The Use Of Graph Databases To Catalog Artifacts For Client Forensics, Rose Shumba

Annual ADFSL Conference on Digital Forensics, Security and Law

Cloud computing has revolutionized the methods by which digital data is stored, processed, and transmitted. It is providing users with data storage and processing services, enabling access to resources through multiple devices. Although organizations continue to embrace the advantages of flexibility and scalability offered by cloud computing, insider threats are becoming a serious concern as cited by security researchers. Insiders can use authorized access to steal sensitive information, calling for the need for an investigation. This concept paper describes research in progress towards developing a Neo4j graph database tool to enhance client forensics. The tool, with a Python interface, allows …

Non-Use Of A Mobile Phone During Conducting Crime Can Also Be Evidential, Vinod Polpaya Bhattathiripad Ph D

Annual ADFSL Conference on Digital Forensics, Security and Law

Cyber-clever criminals who are aware of the consequence of using mobile phones during conducting crimes often stay away from their phones while involved in crimes. Some of them even change their handset and SIM card, subsequently. This article looks into how, intentional disassociation (and even unintentional non-use) of mobile phone in (non-cyber) crimes, can become evidential clues of the perpetrators’ involvement in criminal acts. With the help of a recent judicial episode, this article reveals how extremely careful and masterful handling of extensive and voluminous Call Details Records and tower dumps by a cyber-savvy investigating official can unearth evidential clues …

Unmanned Aerial Vehicle Forensic Investigation Process: Dji Phantom 3 Drone As A Case Study, Alan Roder, Kim-Kwang Raymond Choo, Nhien-A Le-Khac

Annual ADFSL Conference on Digital Forensics, Security and Law

Drones (also known as Unmanned Aerial Vehicles – UAVs) are a potential source of evidence in a digital investigation, partly due to their increasing popularity in our society. However, existing UAV/drone forensics generally rely on conventional digital forensic investigation guidelines such as those of ACPO and NIST, which may not be entirely fit-for-purpose. In this paper, we identify the challenges associated with UAV/drone forensics. We then explore and evaluate existing forensic guidelines, in terms of their effectiveness for UAV/drone forensic investigations. Next, we present our set of guidelines for UAV/drone investigations. Finally, we demonstrate how the proposed guidelines can be …

File Fragment Classification Using Neural Networks With Lossless Representations, Luke Hiester

Undergraduate Honors Theses

This study explores the use of neural networks as universal models for classifying file fragments. This approach differs from previous work in its lossless feature representation, with fragments’ bits as direct input, and its use of feedforward, recurrent, and convolutional networks as classifiers, whereas previous work has only tested feedforward networks. Due to the study’s exploratory nature, the models were not directly evaluated in a practical setting; rather, easily reproducible experiments were performed to attempt to answer the initial question of whether this approach is worthwhile to pursue further, especially due to its high computational cost. The experiments tested classification …

Comparative Study Of Deep Learning Models For Network Intrusion Detection, Brian Lee, Sandhya Amaresh, Clifford Green, Daniel Engels

SMU Data Science Review

In this paper, we present a comparative evaluation of deep learning approaches to network intrusion detection. A Network Intrusion Detection System (NIDS) is a critical component of every Internet connected system due to likely attacks from both external and internal sources. A NIDS is used to detect network born attacks such as Denial of Service (DoS) attacks, malware replication, and intruders that are operating within the system. Multiple deep learning approaches have been proposed for intrusion detection systems. We evaluate three models, a vanilla deep neural net (DNN), self-taught learning (STL) approach, and Recurrent Neural Network (RNN) based Long Short …

Blockchain In Payment Card Systems, Darlene Godfrey-Welch, Remy Lagrois, Jared Law, Russell Scott Anderwald, Daniel W. Engels

SMU Data Science Review

Payment cards (e.g., credit and debit cards) are the most frequent form of payment in use today. A payment card transaction entails many verification information exchanges between the cardholder, merchant, issuing bank, a merchant bank, and third-party payment card processors. Today, a record of the payment transaction often records to multiple ledgers. Merchant’s incur fees for both accepting and processing payment cards. The payment card industry is in dire need of technology which removes the need for third-party verification and records transaction details to a single tamper-resistant digital ledger. The private blockchain is that technology. Private blockchain provides a linked …

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …

Back Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Varying Instructional Approaches To Physical Extraction Of Mobile Device Memory, Joan Runs Through, Gary D. Cantrell

Journal of Digital Forensics, Security and Law

Digital forensics is a multidisciplinary field encompassing both computer science and criminal justice. This action research compared demonstrated skill levels of university students enrolled in a semester course in small device forensics with 54 hours of instruction in mobile forensics with an emphasis on physical techniques such as JTAG and Chip-Off extraction against the skill levels of industry professionals who have completed an accelerated 40 hour advanced mobile forensics training covering much of the same material to include JTAG and Chip-Off extraction. Participant backgrounds were also examined to determine if those participants with a background in computer science had an …

Secure And Efficient Delegation Of A Single And Multiple Exponentiations To A Single Malicious Server, Matluba Khodjaeva

Dissertations, Theses, and Capstone Projects

Group exponentiation is an important operation used in many cryptographic protocols, specifically public-key cryptosystems such as RSA, Diffie Hellman, ElGamal, etc. To expand the applicability of group exponentiation to computationally weaker devices, procedures were established by which to delegate this operation from a computationally weaker client to a computationally stronger server. However, solving this problem with a single, possibly malicious, server, has remained open since a formal cryptographic model was introduced by Hohenberger and Lysyanskaya in 2005. Several later attempts either failed to achieve privacy or only achieved constant security probability.

In this dissertation, we study and solve this problem …

Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang

Department of Computer Science Faculty Scholarship and Creative Works

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …

Efficiently Representing The Integer Factorization Problem Using Binary Decision Diagrams, David Skidmore

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Let p be a prime positive integer and let α be a positive integer greater than 1. A method is given to reduce the problem of finding a nontrivial factorization of α to the problem of finding a solution to a system of modulo p polynomial congruences where each variable in the system is constrained to the set {0,...,p − 1}. In the case that p = 2 it is shown that each polynomial in the system can be represented by an ordered binary decision diagram with size less than 20.25log₂(α)³ + 16.5log₂(α)² + …