OS and Networks Commons^™

Deaddrop: Message Passing Without Metadata Leakage, Davis Mike Arndt

Computer Science and Software Engineering

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 …

Augmented Personalized Health: Using Semantically Integrated Multimodal Data For Patient Empowered Health Management Strategies, Amit P. Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, R. Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra

Kno.e.sis Publications

Healthcare as we know it is in the process of going through a massive change from:

1. Episodic to continuous

2. Disease-focused to wellness and quality of life focused

3. Clinic-centric to anywhere a patient is

4. Clinician controlled to patient empowered

5. Being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven URL: https://mhealth.md2k.org/2018-tech-showcase-home

Extension Of Cpe 454 Operating System, Joseph Nathaniel Arhar

Computer Science and Software Engineering

This project extended on the operating system I wrote in CPE 454 by adding additional features on top of the existing implementation. In order to implement them, I researched operating system design patterns and hardware details. I used wiki.osdev.org for most research, just like I did in CPE 454. The source code for the project is at https://github.com/josepharhar/jos.

Music Popularity, Diffusion And Recommendation In Social Networks: A Fusion Analytics Approach, Jing Ren

Dissertations and Theses Collection (Open Access)

Streaming music and social networks offer an easy way for people to gain access to a massive amount of music, but there are also challenges for the music industry to design for promotion strategies via the new channels. My dissertation employs a fusion of machine-based methods and explanatory empiricism to explore music popularity, diffusion, and promotion in the social network context.

Region-Aware Reflection Removal With Unified Content And Gradient Priors, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Wen Gao, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing the undesired reflections in images taken through the glass is of broad application to various image processing and computer vision tasks. Existing single image-based solutions heavily rely on scene priors such as separable sparse gradients caused by different levels of blur, and they are fragile when such priors are not observed. In this paper, we notice that strong reflections usually dominant a limited region in the whole image, and propose a region-aware reflection removal approach by automatically detecting and heterogeneously processing regions with and without reflections. We integrate content and gradient priors to jointly achieve missing contents restoration, as …

Crrn: Multi-Scale Guided Concurrent Reflection Removal Network, Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot

Research Collection School Of Computing and Information Systems

Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks. Non-learning based methods utilize different handcrafted priors such as the separable sparse gradients caused by different levels of blurs, which often fail due to their limited description capability to the properties of real-world reflections. In this paper, we propose the Concurrent Reflection Removal Network (CRRN) to tackle this problem in a unified framework. Our proposed network integrates image appearance information and multi-scale gradient information with human perception inspired loss function, and is trained on a new dataset with 3250 reflection images …

Survey Of Randomization Defenses On Cloud Computing, Jianming Fu, Yan Lin, Xiuwen Liu, Xu Zhang

Research Collection School Of Computing and Information Systems

Cloud computing has changed the processing mode on resources of individuals and industries by providing computing and storage services to users. However, existing defenses on cloud, such as virtual machine monitoring and integrity detection, cannot counter against attacks result from the homogeneity and vulnerability of services effectively. In this paper, we have investigated the threats on cloud computing platform from the perspective of cloud service, service interface and network interface, such as code reuse attack, side channel attack and SQL injection. Code reuse attack chains code snippets (gadgets) located in binaries to bypass Data Execution Prevention (DEP). Side channel attack …

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.

Towards Mitigating Co-Incident Peak Power Consumption And Managing Energy Utilization In Heterogeneous Clusters, Renan Delvalle Rueda

Graduate Dissertations and Theses

As data centers continue to grow in scale, the resource management software needs to work closely with the hardware infrastructure to provide high utilization, performance, fault tolerance, and high availability. Apache Mesos has emerged as a leader in this space, providing an abstraction over the entire cluster, data center, or cloud to present a uniform view of all the resources. In addition, frameworks built on Mesos such as Apache Aurora, developed within Twitter and later contributed to the Apache Software Foundation, allow massive job submissions with heterogeneous resource requirements. The availability of such tools in the Open Source space, with …

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 …

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

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 …

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

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. …

Evaluation Of Routing Protocols With Ftp And P2p, Tyler Wilson, Eman Abdelfattah, Samir Hamada

School of Computer Science & Engineering Faculty Publications

One of the decisions that need to be made when designing and configuring a computer network in which routing protocol should be used. This paper presents a simulation of a high load File Transfer Protocol (FTP) Application and a high load Peer to Peer (P2P) Application using Riverbed Academic Modeler 17.5. The simulation is configured and run in a World environment to replicate a global network. Each simulation employs either RIP, OSPF, or EIGRP routing protocol. The queuing delay, throughput, link utilization, and IP packets dropped are used as performance parameters to determine which routing protocol is the most efficient …

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 …

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

Graduate 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 …

An Industry-Based Study On The Efficiency Benefits Of Utilising Public Cloud Infrastructure And Infrastructure As Code Tools In The It Environment Creation Process, Shane Callanan

Masters

The traditional approaches to IT infrastructure management typically involve the procuring, housing and running of company-owned and maintained physical servers. In recent years, alternative solutions to IT infrastructure management based on public cloud technologies have emerged. Infrastructure as a Service (IaaS), also known as public cloud infrastructure, allows for the on-demand provisioning of IT infrastructure resources via the Internet. Cloud Service Providers (CSP) such as Amazon Web Services (AWS) offer integration of their cloud-based infrastructure with Infrastructure as Code (IaC) tools. These tools allow for the entire configuration of public cloud based infrastructure to be scripted out and defined as …

Empirical Risk Landscape Analysis For Understanding Deep Neural Networks, Pan Zhou, Jiashi Feng

Research Collection School Of Computing and Information Systems

This work aims to provide comprehensive landscape analysis of empirical risk in deep neural networks (DNNs), including the convergence behavior of its gradient, its stationary points and the empirical risk itself to their corresponding population counterparts, which reveals how various network parameters determine the convergence performance. In particular, for an l-layer linear neural network consisting of di neurons in the i-th layer, we prove the gradient of its empirical risk uniformly converges to the one of its population risk, at the rate of O(r 2l p l √ maxi dis log(d/l)/n). Here d is the total weight dimension, s is …

Learning Latent Characteristics Of Locations Using Location-Based Social Networking Data, Thanh Nam Doan

Dissertations and Theses Collection (Open Access)

This dissertation addresses the modeling of latent characteristics of locations to describe the mobility of users of location-based social networking platforms. With many users signing up location-based social networking platforms to share their daily activities, these platforms become a gold mine for researchers to study human visitation behavior and location characteristics. Modeling such visitation behavior and location characteristics can benefit many use- ful applications such as urban planning and location-aware recommender sys- tems. In this dissertation, we focus on modeling two latent characteristics of locations, namely area attraction and neighborhood competition effects using location-based social network data. Our literature survey …

Bayesian Network Modeling And Inference Of Gwas Catalog, Qiuping Pan

Graduate 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 and …

Breathing-Based Authentication On Resource-Constrained Iot Devices Using Recurrent Neural Networks, Jagmohan Chauhan, Suranga Seneviratne, Yining Hu, Archan Misra, Aruna Seneviratne, Youngki Lee

Research Collection School Of Computing and Information Systems

Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor smart homes. However, the feasibility and performance ofthese inferences on resource-constrained devices remain largelyunexplored. The authors compare traditional machine-learningmodels with deep-learning RNN models for an end-to-endauthentication system based on breathing acoustics.

Next Generation Tcp/Ip Side Channels, Xu Zhang

Computer Science ETDs

Side channel techniques have been developed in recent years to fulfill various tasks in modern computer network measurements. However, due to their nature, these techniques are typically limited in terms of both fidelity and their ability to be used on the real Internet without raising ethical concerns because of packet rates. I propose the next generation of TCP/IP side channel techniques that exploit information flow in modern systems’ network stacks to overcome weaknesses in previous techniques. The proposed work is novel, non-intrusive, and can carry out measurements with high fidelity. I achieved this by deeply understanding the behaviors of modern …

Virtualization In Wireless Sensor Networks: Fault Tolerant Embedding For Internet Of Things, Omprakash Kaiwartya, Abdul Hanan Abdullah, Yue Cao, Jaime Lloret, Sushil Kumar, Rajiv Ratn Shah, Mukesh Prasad, Shiv Prakash

Research Collection School Of Computing and Information Systems

Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for IoT. Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering fault tolerance and communication delay as two conflicting objectives. An adapted non-dominated sorting based genetic algorithm (A-NSGA) is developed to …

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 …

Pattern-Of-Life Modeling Using Data Leakage In Smart Homes, Steven M. Beyer

Theses and Dissertations

This work investigates data leakage in smart homes by providing a Smart Home Automation Architecture (SHAA) and a device classifier and pattern-of-life analysis tool, CITIoT (Classify, Identify, and Track Internet of things). CITIoT was able to capture traffic from SHAA and classify 17 of 18 devices, identify 95% of the events that occurred, and track when users were home or away with near 100% accuracy. Additionally, a mitigation tool, MIoTL (Mitigation of IoT Leakage) is provided to defend against smart home data leakage. With mitigation, CITIoT was unable to identify motion and camera devices and was inundated with an average …