Systems Architecture Commons^™

Windows Kernel Hijacking Is Not An Option: Memoryranger Comes To The Rescue Again, Igor Korkin

Journal of Digital Forensics, Security and Law

The security of a computer system depends on OS kernel protection. It is crucial to reveal and inspect new attacks on kernel data, as these are used by hackers. The purpose of this paper is to continue research into attacks on dynamically allocated data in the Windows OS kernel and demonstrate the capacity of MemoryRanger to prevent these attacks. This paper discusses three new hijacking attacks on kernel data, which are based on bypassing OS security mechanisms. The first two hijacking attacks result in illegal access to files open in exclusive access. The third attack escalates process privileges, without applying ...

Witness For Two-Site Enabled Coordination, Sriram Priyatham Siram

Master's Projects

Many replicated data services utilize majority quorums to safely replicate data changes in the presence of server failures. Majority quorum-based services require a simple majority of the servers to be operational for the service to stay available. A key limitation of the majority quorum is that if a service is composed of just two servers, progress cannot be made even if a single server fails because the majority quorum size is also two. This is called the Two-Server problem. A problem similar to the Two-Server problem occurs when a service’s servers are spread across only two failure domains. Servers ...

Machine Learning Using Serverless Computing, Vidish Naik

Master's Projects

Machine learning has been trending in the domain of computer science for quite some time. Newer and newer models and techniques are being developed every day. The adoption of cloud computing has only expedited the process of training machine learning. With its variety of services, cloud computing provides many options for training machine learning models. Leveraging these services is up to the user. Serverless computing is an important service offered by cloud service providers. It is useful for short tasks that are event-driven or periodic. Machine learning training can be divided into short tasks or batches to take advantage of ...

Introduction To Assembly Language Programming: From Soup To Nuts: Arm Edition, Charles W. Kann

Open Textbooks

This is an ARM Assembly Language Textbook designed to be used in classes such as Computer Organization, Operating Systems, Compilers, or any other class that needs to provide the students with a overall of Arm Assembly Language. As with all Soup to Nuts books, it is intended to be a resource where each chapter builds on the material from previous chapters, and leads the reader from a rudimentary knowledge of assembly language to a point where they can use it in their studies.

Analysis Of Theoretical And Applied Machine Learning Models For Network Intrusion Detection, Jonah Baron

Masters Theses & Doctoral Dissertations

Network Intrusion Detection System (IDS) devices play a crucial role in the realm of network security. These systems generate alerts for security analysts by performing signature-based and anomaly-based detection on malicious network traffic. However, there are several challenges when configuring and fine-tuning these IDS devices for high accuracy and precision. Machine learning utilizes a variety of algorithms and unique dataset input to generate models for effective classification. These machine learning techniques can be applied to IDS devices to classify and filter anomalous network traffic. This combination of machine learning and network security provides improved automated network defense by developing highly-optimized ...

Brave New World Reboot: Technology’S Role In Consumer Manipulation And Implications For Privacy And Transparency, Allie Mertensotto

Marketing Undergraduate Honors Theses

Most consumers are aware that our data is being obtained and collected through the use of our devices we keep in our homes or even on our person throughout the day. But, it is understated how much data is being collected. Conversations you have with your peers – in a close proximity of a device – are being used to tailor advertising. The advertisements you receive on your devices are uniquely catered to your individual person, due to the fact it consistently uses our data to produce efficient and personal ads. On the flip side, our government is also tapping into our ...

Characteristic Reassignment For Hardware Trojan Detection, Noah Waller

Graduate Theses and Dissertations

With the current business model and increasing complexity of hardware designs, third-party Intellectual Properties (IPs) are prevalently incorporated into first-party designs. However, the use of third-party IPs increases security concerns related to hardware Trojans inserted by attackers. A core threat posed by Hardware Trojans is the difficulty in detecting such malicious insertions/alternations in order to prevent the damage. This thesis work provides major improvements on a soft IP analysis methodology and tool known as the Structural Checking tool, which analyzes Register-Transfer Level (RTL) soft IPs for determining their functionalities and screening for hardware Trojans. This is done by breaking ...

Network-Based Detection And Prevention System Against Dns-Based Attacks, Yasir Faraj Mohammed

Graduate Theses and Dissertations

Individuals and organizations rely on the Internet as an essential environment for personal or business transactions. However, individuals and organizations have been primary targets for attacks that steal sensitive data. Adversaries can use different approaches to hide their activities inside the compromised network and communicate covertly between the malicious servers and the victims. The domain name system (DNS) protocol is one of these approaches that adversaries use to transfer stolen data outside the organization's network using various forms of DNS tunneling attacks. The main reason for targeting the DNS protocol is because DNS is available in almost every network ...

Trust Models And Risk In The Internet Of Things, Jeffrey Hemmes

Regis University Faculty Publications

The Internet of Things (IoT) is envisaged to be a large-scale, massively heterogeneous ecosystem of devices with varying purposes and capabilities. While architectures and frameworks have focused on functionality and performance, security is a critical aspect that must be integrated into system design. This work proposes a method of risk assessment of devices using both trust models and static capability profiles to determine the level of risk each device poses. By combining the concepts of trust and secure device fingerprinting, security mechanisms can be more efficiently allocated across networked IoT devices. Simultaneously, devices can be allowed a greater degree of ...

Non-Hazardous Industrial Solid Waste Tracking System, Justin Tank

Masters Theses & Doctoral Dissertations

The Olmsted Non-Hazardous Industrial Solid Waste Tracking System allows waste generators of certain materials to electronically have their waste assessments evaluated, approved, and tracked through a simple online process. The current process of manually requesting evaluations, prepopulating tracking forms, and filling them out on triplicate carbonless forms is out of sync with other processes in the department. Complying with audit requirements requires pulling physical copies and providing them physically to fulfill information requests.

Waste generators in Minnesota are required to track their waste disposals for certain types of industrial waste streams. This ensures waste is accounted for at the point ...

Iot Based Agriculture 4.0: Challenges And Opportunities, Halimjon Khujamatov, Temur Toshtemirov Mr., Doston Turayevich Khasanov Mr., Nasiba Saburova Ms., Ilhom Ikromovich Xamroyev Mr.

Bulletin of TUIT: Management and Communication Technologies

In recent years, the world's population growth has been intensifying, resulting in specific problems related to the depletion of natural resources, food shortages, declining fertile lands, and changing weather conditions. This paper has been discussed the use of IoT technology as a solution to such problems.

At the same time, the emergence of IoT technology has given rise to a new research direction in agriculture. Soil analysis and monitoring using Zigbee wireless sensor network technology, which is part of the IoT, will enable the creation of an IoT ecosystem as well as the development of smart agriculture. In addition ...

Building And Using Digital Libraries For Etds, Edward A. Fox

The Journal of Electronic Theses and Dissertations

Despite the high value of electronic theses and dissertations (ETDs), the global collection has seen limited use. To extend such use, a new approach to building digital libraries (DLs) is needed. Fortunately, recent decades have seen that a vast amount of “gray literature” has become available through a diverse set of institutional repositories as well as regional and national libraries and archives. Most of the works in those collections include ETDs and are often freely available in keeping with the open-access movement, but such access is limited by the services of supporting information systems. As explained through a set of ...

Towards Identity Relationship Management For Internet Of Things, Mohammad Muntasir Nur

Masters Theses & Doctoral Dissertations

Identity and Access Management (IAM) is in the core of any information systems. Traditional IAM systems manage users, applications, and devices within organizational boundaries, and utilize static intelligence for authentication and access control. Identity federation has helped a lot to deal with boundary limitation, but still limited to static intelligence – users, applications and devices must be under known boundaries. However, today’s IAM requirements are much more complex. Boundaries between enterprise and consumer space, on premises and cloud, personal devices and organization owned devices, and home, work and public places are fading away. These challenges get more complicated for Internet ...

Efficacy Of Incident Response Certification In The Workforce, Samuel Jarocki

Masters Theses & Doctoral Dissertations

Numerous cybersecurity certifications are available both commercially and via institutes of higher learning. Hiring managers, recruiters, and personnel accountable for new hires need to make informed decisions when selecting personnel to fill positions. An incident responder or security analyst's role requires near real-time decision-making, pervasive knowledge of the environments they are protecting, and functional situational awareness. This concurrent mixed methods paper studies whether current commercial certifications offered in the cybersecurity realm, particularly incident response, provide useful indicators for a viable hiring candidate.

Managers and non-managers alike do prefer hiring candidates with an incident response certification. Both groups affirmatively believe ...

Block The Root Takeover: Validating Devices Using Blockchain Protocol, Sharmila Paul

Masters Theses & Doctoral Dissertations

This study addresses a vulnerability in the trust-based STP protocol that allows malicious users to target an Ethernet LAN with an STP Root-Takeover Attack. This subject is relevant because an STP Root-Takeover attack is a gateway to unauthorized control over the entire network stack of a personal or enterprise network. This study aims to address this problem with a potentially trustless research solution called the STP DApp. The STP DApp is the combination of a kernel /net modification called stpverify and a Hyperledger Fabric blockchain framework in a NodeJS runtime environment in userland. The STP DApp works as an Intrusion ...

Traversing Nat: A Problem, Tyler Flaagan

Masters Theses & Doctoral Dissertations

This quasi-experimental before-and-after study measured and analyzed the impacts of adding security to a new bi-directional Network Address Translation (NAT). Literature revolves around various types of NAT, their advantages and disadvantages, their security models, and networking technologies’ adoption. The study of the newly created secure bi-directional model of NAT showed statistically significant changes in the variables than another model using port forwarding. Future research of how data will traverse networks is crucial in an ever-changing world of technology.

Load Balancing And Resource Allocation In Smart Cities Using Reinforcement Learning, Aseel Alorbani

Electronic Thesis and Dissertation Repository

Today, smart city technology is being adopted by many municipal governments to improve their services and to adapt to growing and changing urban population. Implementing a smart city application can be one of the most challenging projects due to the complexity, requirements and constraints. Sensing devices and computing components can be numerous and heterogeneous. Increasingly, researchers working in the smart city arena are looking to leverage edge and cloud computing to support smart city development. This approach also brings a number of challenges. Two of the main challenges are resource allocation and load balancing of tasks associated with processing data ...

Hybrid Cloud Workload Monitoring As A Service, Shreya Kundu

Master's Projects

Cloud computing and cloud-based hosting has become embedded in our daily lives. It is imperative for cloud providers to make sure all services used by both enterprises and consumers have high availability and elasticity to prevent any downtime, which impacts negatively for any business. To ensure cloud infrastructures are working reliably, cloud monitoring becomes an essential need for both businesses, the provider and the consumer. This thesis project reports on the need of efficient scalable monitoring, enumerating the necessary types of metrics of interest to be collected. Current understanding of various architectures designed to collect, store and process monitoring data ...

Incremental Design-Space Model Checking Via Reusable Reachable State Approximations, Rohit Dureja, Kristin Yvonne Rozier

Aerospace Engineering Publications

The design of safety-critical systems often requires design space exploration: comparing several system models that differ in terms of design choices, capabilities, and implementations. Model checking can compare different models in such a set, however, it is continuously challenged by the state space explosion problem. Therefore, learning and reusing information from solving related models becomes very important for future checking efforts. For example, reusing variable ordering in BDD-based model checking leads to substantial performance improvement. In this paper, we present a SAT-based algorithm for checking a set of models. Our algorithm, FuseIC3, extends IC3 to minimize time spent in exploring ...

Secure Network Access Via Ldap, Nicholas Valaitis

Williams Honors College, Honors Research Projects

Networks need the ability to be access by secure accounts and users. The goal of this project is to configure and expand on LDAP configurations with considerations for AAA via TACACS+ and Radius for network equipment. This will provide adequate security for any given network in terms of access and prevent lose of access to devices which happens all to often with locally configured accounts on devices.

Automated Discovery Of Network Cameras In Heterogeneous Web Pages, Ryan Dailey, Aniesh Chawla, Andrew Liu, Sripath Mishra, Ling Zhang, Josh Majors, Yung-Hisang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Reduction in the cost of Network Cameras along with a rise in connectivity enables entities all around the world to deploy vast arrays of camera networks. Network cameras offer real-time visual data that can be used for studying traffic patterns, emergency response, security, and other applications. Although many sources of Network Camera data are available, collecting the data remains difficult due to variations in programming interface and website structures. Previous solutions rely on manually parsing the target website, taking many hours to complete. We create a general and automated solution for aggregating Network Camera data spread across thousands of uniquely ...

Improving Energy Efficiency Through Compiler Optimizations, Jack Beckitt-Marshall

Honors Projects

Abstract--- Energy efficiency is becoming increasingly important for computation, especially in the context of the current climate crisis. The aim of this experiment was to see if the compiler could reduce energy usage without rewriting programs themselves. The experimental setup consisted of compiling programs using the Clang compiler using a set of compiler flags, and then measuring energy usage and execution time on an AMD Ryzen processor. Three experiments were performed: a random exploration of compiler flags, utilization of SIMD, as well as benchmarking real world applications. It was found that the compiler was able to reduce execution time, especially ...

Spatial And Graphical Data Processing: Spatial Crowdsourcing And Quasi-Clique Enumeration, Hooman Hashemi

Creative Components

In this report, data processing in two realms, spatial and graphical, has been studied. In the first chapter of this work, we explain spatial crowdsourcing and how it incorporates the context of physical location and enables assignments of workers to tasks not only based on matching skills but also on the (relative) whereabouts in time. Most of the works in this field have assumed a kind of steadiness of the dynamic of the essential parameters that were used to generate the worker and task pairs. In this work, we address the problem of reassignment of workers and tasks pair due ...

On Studying Distributed Machine Learning, Simeon Eberz

Senior Honors Theses

The Internet of Things (IoT) is utilizing Deep Learning (DL) for applications such as voice or image recognition. Processing data for DL directly on IoT edge devices reduces latency and increases privacy. To overcome the resource constraints of IoT edge devices, the computation for DL inference is distributed between a cluster of several devices. This paper explores DL, IoT networks, and a novel framework for distributed processing of DL in IoT clusters. The aim is to facilitate and simplify deployment, testing, and study of a distributed DL system, even without physical devices. The contributions of this paper are a deployment ...

Xtreme-Noc: Extreme Gradient Boosting Based Latency Model For Network-On-Chip Architectures, Ilma Sheriff

All Graduate Theses, Dissertations, and Other Capstone Projects

Multiprocessor System-on-Chip (MPSoC) integrating heterogeneous processing elements (CPU, GPU, Accelerators, memory, I/O modules ,etc.) are the de-facto design choice to meet the ever-increasing performance/Watt requirements from modern computing machines. Although at consumer level the number of processing elements (PE) are limited to 8-16, for high end servers, the number of PEs can scale up to hundreds. A Network-on-Chip (NoC) is a microscale network that facilitates the packetized communication among the PEs in such complex computational systems. Due to the heterogeneous integration of the cores, execution of diverse (serial and parallel) applications on the PEs, application mapping strategies, and ...

Hierarchical Visual Concept Interpretation For Medical Image Classification, Mohammed Khaleel, Wallapak Tavanapong, Johnny Wong, Junghwan Oh, Piet De Groen

Computer Science Conference Presentations, Posters and Proceedings

Most state-of-the-art local interpretation methods explain the behavior of deep learning classification models by assigning importance scores to image pixels based on how influential each pixel was towards the final decision. These interpretations are unable to provide further details to aid understanding of a complex concept in a domain such as medicine. We propose a novel Hierarchical Visual Concept (HVC) interpretation framework for CNN-based image classification models. As an explanation of the classification decision of a given image, HVC presents a concept hierarchy of most relevant visual concepts at multiple semantic levels. These concepts are automatically learned during training such ...

Evaluation Of Reliability Indicators Of Mobile Communication System Bases, Dilmurod Davronbekov, Utkir Karimovich Matyokubov, Malika Ilkhamovna Abdullayeva

Bulletin of TUIT: Management and Communication Technologies

In this study, the reliability of mobile system base stations (BTS) is assessed by analyzing data obtained on faults in about 200 BTS over a six-month period. Five BTSs with the highest number of failures and duration of failure were selected in these BTSs. Based on the data obtained, reliability parameters were calculated and compared.

The study used Weibull’s dismissal process distribution method. The breakdown times of each BTS were sorted. In all five BTS, it was found that β(where the value of β is the approximate value obtained from the values of the smallest squares of the ...

A Framework For Identifying Host-Based Artifacts In Dark Web Investigations, Arica Kulm

Masters Theses & Doctoral Dissertations

The dark web is the hidden part of the internet that is not indexed by search engines and is only accessible with a specific browser like The Onion Router (Tor). Tor was originally developed as a means of secure communications and is still used worldwide for individuals seeking privacy or those wanting to circumvent restrictive regimes. The dark web has become synonymous with nefarious and illicit content which manifests itself in underground marketplaces containing illegal goods such as drugs, stolen credit cards, stolen user credentials, child pornography, and more (Kohen, 2017). Dark web marketplaces contribute both to illegal drug usage ...

Modular Neural Networks For Low-Power Image Classification On Embedded Devices, Abhinav Goel, Sara Aghajanzadeh, Caleb Tung, Shuo-Han Chen, George K. Thiruvathukal, Yung-Hisang Lu

Computer Science: Faculty Publications and Other Works

Embedded devices are generally small, battery-powered computers with limited hardware resources. It is difficult to run deep neural networks (DNNs) on these devices, because DNNs perform millions of operations and consume significant amounts of energy. Prior research has shown that a considerable number of a DNN’s memory accesses and computation are redundant when performing tasks like image classification. To reduce this redundancy and thereby reduce the energy consumption of DNNs, we introduce the Modular Neural Network Tree architecture. Instead of using one large DNN for the classifier, this architecture uses multiple smaller DNNs (called modules) to progressively classify images ...

Tpr: Text-Aware Preference Ranking For Recommender Systems, Yu-Neng Chuang, Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai, Yuan Fang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Textual data is common and informative auxiliary information for recommender systems. Most prior art utilizes text for rating prediction, but rare work connects it to top-N recommendation. Moreover, although advanced recommendation models capable of incorporating auxiliary information have been developed, none of these are specifically designed to model textual information, yielding a limited usage scenario for typical user-to-item recommendation. In this work, we present a framework of text-aware preference ranking (TPR) for top-N recommendation, in which we comprehensively model the joint association of user-item interaction and relations between items and associated text. Using the TPR framework, we construct a joint ...