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Deaddrop: Message Passing Without Metadata Leakage, Davis Mike Arndt 2018 California Polytechnic State University, San Luis Obispo

Deaddrop: Message Passing Without Metadata Leakage, Davis Mike Arndt

Computer Science

Even when network data is encrypted, observers can make inferences about content based on collected metadata. DeadDrop is an exploratory API designed to protect the metadata of a conversation from both outside observers and the facilitating server. To do so, DeadDrop servers are passed no recipient address, instead relying upon the recipient to check for messages of their own volition. In addition, the recipient downloads a copy of every encrypted message on the server to prevent even the server from knowing to whom each message is intended. To these purposes, DeadDrop is mostly successful. However, it does not obscure all ...


Contents, ADFSL 2018 Embry-Riddle Aeronautical University

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.


Front Matter, ADFSL 2018 Embry-Riddle Aeronautical University

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 2018 Technology Research Centre, DPG

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 2018 Embry-Riddle Aeronautical University

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 2018 East Central University, Ada Oklahoma

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 2018 Embry-Riddle Aeronautical University

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 ...


Forensic Analysis Of The Exfat Artifacts, Yves Vandermeer, An Lekhac, Tahar Kechadi, Joe Carthy 2018 Norwegian Police University College

Forensic Analysis Of The Exfat Artifacts, Yves Vandermeer, An Lekhac, Tahar Kechadi, Joe Carthy

Annual ADFSL Conference on Digital Forensics, Security and Law

Although keeping some basic concepts inherited from FAT32, the exFAT file system introduces many differences, such as the new mapping scheme of directory entries. The combination of exFAT mapping scheme with the allocation of bitmap files and the use of FAT leads to new forensic possibilities. The recovery of deleted files, including fragmented ones and carving becomes more accurate compared with former forensic processes. Nowadays, the accurate and sound forensic analysis is more than ever needed, as there is a high risk of erroneous interpretation. Indeed, most of the related work in the literature on exFAT structure and forensics, is ...


Unmanned Aerial Vehicle Forensic Investigation Process: Dji Phantom 3 Drone As A Case Study, Alan Roder, Kim-Kwang Raymond Choo, Nhien-A Le-Khac 2018 University of Texas at San Antonio

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 ...


Detection And Recovery Of Anti-Forensic (Vault) Applications On Android Devices, Michaila Duncan, Umit Karabiyik 2018 Sam Houston State University

Detection And Recovery Of Anti-Forensic (Vault) Applications On Android Devices, Michaila Duncan, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Significant number of mobile device users currently employ anti-forensics applications, also known as vault or locker applications, on their mobile devices in order to hide files such as photos. Because of this, investigators are required to spend a large portion of their time manually looking at the applications installed on the device. Currently, there is no automated method of detecting these anti-forensics applications on an Android device. This work presents the creation and testing of a vault application detection system to be used on Android devices. The main goal of this work is twofold: (i) Detecting and reporting the presence ...


Hypervisor-Based Active Data Protection For Integrity And Confidentiality Of Dynamically Allocated Memory In Windows Kernel, Igor Korkin 2018 Embry-Riddle Aeronautical University

Hypervisor-Based Active Data Protection For Integrity And Confidentiality Of Dynamically Allocated Memory In Windows Kernel, Igor Korkin

Annual ADFSL Conference on Digital Forensics, Security and Law

One of the main issues in the OS security is providing trusted code execution in an untrusted environment. During executing, kernel-mode drivers dynamically allocate memory to store and process their data: Windows core kernel structures, users’ private information, and sensitive data of third-party drivers. All this data can be tampered with by kernel-mode malware. Attacks on Windows-based computers can cause not just hiding a malware driver, process privilege escalation, and stealing private data but also failures of industrial CNC machines. Windows built-in security and existing approaches do not provide the integrity and confidentiality of the allocated memory of third-party drivers ...


Improving The Efficacy Of Context-Aware Applications, Jon C. Hammer 2018 University of Arkansas, Fayetteville

Improving The Efficacy Of Context-Aware Applications, Jon C. Hammer

Theses and Dissertations

In this dissertation, we explore methods for enhancing the context-awareness capabilities of modern computers, including mobile devices, tablets, wearables, and traditional computers. Advancements include proposed methods for fusing information from multiple

logical sensors, localizing nearby objects using depth sensors, and building models to better understand the content of 2D images.

First, we propose a system called Unagi, designed to incorporate multiple logical sensors into a single framework that allows context-aware application developers to easily test new ideas and create novel experiences. Unagi is responsible for collecting data, extracting

features, and building personalized models for each individual user. We demonstrate the ...


Dynamic 3d Network Data Visualization, Brok Stafford 2018 University of Arkansas, Fayetteville

Dynamic 3d Network Data Visualization, Brok Stafford

Computer Science and Computer Engineering Undergraduate Honors Theses

Monitoring network traffic has always been an arduous and tedious task because of the complexity and sheer volume of network data that is being consistently generated. In addition, network growth and new technologies are rapidly increasing these levels of complexity and volume. An effective technique in understanding and managing a large dataset, such as network traffic, is data visualization. There are several tools that attempt to turn network traffic into visual stimuli. Many of these do so in 2D space and those that are 3D lack the ability to display network patterns effectively. Existing 3D network visualization tools lack user ...


Bayesian Network Modeling And Inference Of Gwas Catalog, Qiuping Pan 2018 University of Arkansas, Fayetteville

Bayesian Network Modeling And Inference Of Gwas Catalog, Qiuping Pan

Theses and Dissertations

Genome-wide association studies (GWASs) have received an increasing attention to understand genotype-phenotype relationships. The Bayesian network has been proposed as a powerful tool for modeling single-nucleotide polymorphism (SNP)-trait associations due to its advantage in addressing the high computational complex and high dimensional problems. Most current works learn the interactions among genotypes and phenotypes from the raw genotype data. However, due to the privacy issue, genotype information is sensitive and should be handled by complying with specific restrictions. In this work, we aim to build Bayesian networks from publicly released GWAS statistics to explicitly reveal the conditional dependency between SNPs ...


Malware For Macintosh, Nathan C. Shinabarger, Josiah E. Bills, Richard W. Lively, Noah S. Shinabarger 2018 Cedarville University

Malware For Macintosh, Nathan C. Shinabarger, Josiah E. Bills, Richard W. Lively, Noah S. Shinabarger

The Research and Scholarship Symposium

Technology is a cornerstone of modern society. Unfortunately, it seems that every new piece of technology is accompanied by five computer-security breaches elsewhere. Most people associate hacks with Windows computers. This is a problem because Apple computers, and other non-Windows systems, are also extremely vulnerable to attacks and risk being compromised. Dolos is a piece of malware we developed intended to exploit the macOS Sierra operating system. It provides a framework for running exploits and comes built in with certain control and data exfiltration capabilities. Dolos also helps destroy the misconception of "the impenetrable Macintosh computer" by showing that Apple ...


Automated Man-In-The-Middle Attack Against Wi‑Fi Networks, Martin Vondráček, Jan Pluskal, Ondřej Ryšavý 2018 Brno University of Technology, Brno, Czech Republic

Automated Man-In-The-Middle Attack Against Wi‑Fi Networks, Martin Vondráček, Jan Pluskal, Ondřej Ryšavý

Journal of Digital Forensics, Security and Law

Currently used wireless communication technologies suffer security weaknesses that can be exploited allowing to eavesdrop or to spoof network communication. In this paper, we present a practical tool that can automate the attack on wireless security. The developed package called wifimitm provides functionality for the automation of MitM attacks in the wireless environment. The package combines several existing tools and attack strategies to bypass the wireless security mechanisms, such as WEP, WPA, and WPS. The presented tool can be integrated into a solution for automated penetration testing. Also, a popularization of the fact that such attacks can be easily automated ...


Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya KANDAPPU, Archan MISRA, Shih Fen CHENG, Randy TANDRIANSYAH, Hoong Chuin LAU 2018 Singapore Management University

Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau

Research Collection School Of Information Systems

By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade ...


Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz KHAN, Nirmalya ROY, Archan MISRA 2018 Singapore Management University

Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz Khan, Nirmalya Roy, Archan Misra

Research Collection School Of Information Systems

We investigate the problem of making human activityrecognition (AR) scalable–i.e., allowing AR classifiers trainedin one context to be readily adapted to a different contextualdomain. This is important because AR technologies can achievehigh accuracy if the classifiers are trained for a specific individualor device, but show significant degradation when the sameclassifier is applied context–e.g., to a different device located ata different on-body position. To allow such adaptation withoutrequiring the onerous step of collecting large volumes of labeledtraining data in the target domain, we proposed a transductivetransfer learning model that is specifically tuned to the propertiesof convolutional neural ...


Back Matter, ADFSL 2018 Embry-Riddle Aeronautical University

Back Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.


Front Matter, ADFSL 2018 Embry-Riddle Aeronautical University

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.


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