Information Security Commons^™

Privacy Preserving For Multiple Computer Vision Tasks, Amala Varghese Wilson

Master's Projects

Privacy-preserving visual recognition is an important area of research that is gaining momentum in the field of computer vision. In a production environment, it is critical to have neural network models learn continually from user data. However, sharing raw user data with a server is less desirable from a regulatory, security and privacy perspective. Federated learning addresses the problem of privacy- preserving visual recognition. More specifically, we closely examine and dissect a framework known as Dual User Adaptation (DUA) presented by Lange et al. at CVPR 2020, due to its novel idea of bringing about user-adaptation on both the server-side …

Identifying Bots On Twitter With Benford’S Law, Sanmesh Bhosale

Master's Projects

Over time Online Social Networks (OSNs) have grown exponentially in terms of active users and have now become an influential factor in the formation of public opinions. Due to this, the use of bots and botnets for spreading misinformation on OSNs has become a widespread concern. The biggest example of this was during the 2016 American Presidential Elections, where Russian bots on Twitter pumped out fake news to influence the election results.

Identifying bots and botnets on Twitter is not just based on visual analysis and can require complex statistical methods to score a profile based on multiple features and …

Extending The Quality Of Secure Service Model To Multi-Hop Networks, Paul M. Simon, Scott R. Graham

Faculty Publications

Rarely are communications networks point-to-point. In most cases, transceiver relay stations exist between transmitter and receiver end-points. These relay stations, while essential for controlling cost and adding flexibility to network architectures, reduce the overall security of the respective network. In an effort to quantify that reduction, we extend the Quality of Secure Service (QoSS) model to these complex networks, specifically multi-hop networks. In this approach, the quantification of security is based upon probabilities that adversarial listeners and disruptors gain access to or manipulate transmitted data on one or more of these multi-hop channels. Message fragmentation and duplication across available channels …

Analyzing And Detecting Android Malware And Deepfake, Md Shohel Rana

Dissertations

Rapid advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) over the past several decades have produced a variety of technologies and tools that, among numerous cybersecurity issues, have enticed cybercriminals and hackers to design malware for the Android operating systems and/or manipulate multimedia. For example, high-quality and realistic fake videos, images, or audios have been created to spread misinformation and propaganda, foment political discord and hate, or even harass and blackmail people; these manipulated, high-quality and realistic videos became known recently as Deepfake. There has been much work done in recent years on malware analysis and …

Performance Assessment Of Some Phishing Predictive Models Based On Minimal Feature Corpus, Orunsolu Abdul Abiodun, Sodiya A.S, Kareem S.O, Oladimeji G. B Mr.

Journal of Digital Forensics, Security and Law

Phishing is currently one of the severest cybersecurity challenges facing the emerging online community. With damages running into millions of dollars in financial and brand losses, the sad tale of phishing activities continues unabated. This led to an arms race between the con artists and online security community which demand a constant investigation to win the cyberwar. In this paper, a new approach to phishing is investigated based on the concept of minimal feature set on some selected remarkable machine learning algorithms. The goal of this is to select and determine the most efficient machine learning methodology without undue high …

An Analysis Of Significant Cyber Incidents And The Impact On The Past, Present, And Future, Seth E. Smith

Cybersecurity Undergraduate Research Showcase

This report discusses data collected on significant cybersecurity incidents from the early 2000s to present. The first part of the report addresses previously discussed information, data, and literature (e.g. case studies), pertinent to cybersecurity incidents. The findings from this study are framed by scholarly sources and information from the Federal Bureau of Investigation, a number of notable universities, and literature online, of which all support information discussed within this report. The second part of the report discusses data compiled upon analyzing significant cyber incidents and events from the Center for Strategic and International Affairs (CSIS). Finally, the last portion of …

Analytical Approach To Biometric Security And How It Affects Privacy, Torré A. Williams

Cybersecurity Undergraduate Research Showcase

In this time where the world is using technology every day, there is going to be a need for some type of security to take place to protect its citizens from unwanted harm or danger. The use of any authentication methods is becoming very essential for a lot of companies and even for your own personal belongings. The use of biometric technology has offered companies the chance to upgrade their security system. This has also provided easier ways that people authenticate themselves as who they say they are. Due to their growth of usage, there is a privacy and security …

Video Snapshot: Single Image Motion Expansion Via Invertible Motion Embedding, Qianshu Zhu, Chu Han, Guoqiang Han, Tien-Tsin Wong, Shengfeng He

Research Collection School Of Computing and Information Systems

Unlike images, finding the desired video content in a large pool of videos is not easy due to the time cost of loading and watching. Most video streaming and sharing services provide the video preview function for a better browsing experience. In this paper, we aim to generate a video preview from a single image. To this end, we propose two cascaded networks, the motion embedding network and the motion expansion network. The motion embedding network aims to embed the spatio-temporal information into an embedded image, called video snapshot. On the other end, the motion expansion network is proposed to …

Collaborcrack: A Collaborative Password Cracking Solution For Windows Penetration Testing, Andrew Griess

Theses/Capstones/Creative Projects

Cybersecurity professionals attempt to crack password hashes during penetration tests to determine if they are strong enough. A password hash is a way to encode a password securely. This paper describes a proof-of-concept program called CollaborCrack, a team-based password cracking solution. CollaborCrack addresses the issues of computational complexity, remote cracking security, duplication of work, and the cost associated with password cracking. To address computational complexity, CollaborCrack enables remote password cracking. Remote cracking requires additional safeguards, which CollaborCrack mitigates by storing sensitive information locally. To reduce the duplication of work, CollaborCrack provides a shared interface designed around collaboration and teamwork. CollaborCrack …

Beginning The Information Security Journey For Small And Medium Enterprises Through Business Continuity Planning And Infrastructure Automation, Aaron Chamberlain

Electronic Theses, Projects, and Dissertations

Technology has become an essential component of enterprises, driving productivity, innovation, and defining entire processes and product categories. However, these advances come with additional risk; the devices that drive an enterprise can fail at any time or be attacked by malicious actors. Larger enterprises have learned to deal with these risks, but small and medium-sized enterprises (SMEs) have been largely left behind. This project sought to investigate the cybersecurity-related problems SMEs experience and what SMEs can do to solve them. In addition, the project examines the types of information security incidents that occur within SMEs and their financial preparedness for …

Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay

All Theses

The cybersecurity of power systems is jeopardized by the threat of spoofing and man-in-the-middle style attacks due to a lack of physical layer device authentication techniques for operational technology (OT) communication networks. OT networks cannot support the active probing cybersecurity methods that are popular in information technology (IT) networks. Furthermore, both active and passive scanning techniques are susceptible to medium access control (MAC) address spoofing when operating at Layer 2 of the Open Systems Interconnection (OSI) model. This thesis aims to analyze the role of deep learning in passively authenticating Ethernet devices by their communication signals. This method operates at …

Hrpdf: A Software-Based Heterogeneous Redundant Proactive Defense Framework For Programmable Logic Controller, Ke Liu, Jing-Yi Wang, Qiang Wei, Zhen-Yong Zhang, Jun Sun, Rong-Kuan Ma, Rui-Long Deng

Research Collection School Of Computing and Information Systems

Programmable logic controllers (PLCs) play a critical role in many industrial control systems, yet face increasingly serious cyber threats. In this paper, we propose a novel PLC-compatible software-based defense mechanism, called Heterogeneous Redundant Proactive Defense Framework (HRPDF). We propose a heterogeneous PLC architecture in HRPDF, including multiple heterogeneous, equivalent, and synchronous runtimes, which can thwart multiple types of attacks against PLC without the need of external devices. To ensure the availability of PLC, we also design an inter-process communication algorithm that minimizes the overhead of HRPDF. We implement a prototype system of HRPDF and test it in a real-world PLC …

Data Fusion For Trust Evaluation, Zheng Yan, Qinghua Zheng, Laurence T. Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Trust evaluation is a process to quantify trust by analyzing the data related to the factors that affect trust. It has been widely applied in many fields to facilitate decision making, system entity collaboration and security establishment. For example, in social networking, trust evaluation helps users make a social decision, reduce the risk of social interactions, and ensure the quality of a social networking environment. In digital communications, trust evaluation can be applied to detect malicious nodes, filter unwanted traffic and improve communication security. In e-commerce and cloud services, trust evaluation helps users selecting an appropriate product or service from …

Broadcast Authenticated Encryption With Keyword Search, Xueqiao Liu, Kai He, Guomin Yang, Willy Susilo, Joseph Tonien, Qiong Huang

Research Collection School Of Computing and Information Systems

The emergence of public-key encryption with keyword search (PEKS) has provided an elegant approach to enable keyword search over encrypted content. Due to its high computational complexity proportional to the number of intended receivers, the trivial way of deploying PEKS for data sharing with multiple receivers is impractical, which motivates the development of a new PEKS framework for broadcast mode. However, existing works suffer from either the vulnerability to keyword guessing attacks (KGA) or high computation and communication complexity. In this work, a new primitive for keyword search in broadcast mode, named broadcast authenticated encryption with keyword search (BAEKS), is …

Deriving Invariant Checkers For Critical Infrastructure Using Axiomatic Design Principles, Cheah Huei Yoong, Venkata Reddy Palleti, Rajib Ranjan Maiti, Arlindo Silva, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPSs) in critical infrastructure face serious threats of attack, motivating research into a wide variety of defence mechanisms such as those that monitor for violations of invariants, i.e. logical properties over sensor and actuator states that should always be true. Many approaches for identifying invariants attempt to do so automatically, typically using data logs, but these can miss valid system properties if relevant behaviours are not well-represented in the data. Furthermore, as the CPS is already built, resolving any design flaws or weak points identified through this process is costly. In this paper, we propose a systematic …

An Assessment Of Image-Cloaking Techniques Against Automated Face Recognition For Biometric Privacy, Brandon Scott Ledford

Theses and Dissertations

Over the past two decades, Americans have aggressively increased the amount of facial data uploaded to the internet primarily via social media. This data is largely unprotected due to the dire lack of existing regulations protecting users from large scale face recognition in the United States, where the value of data trade is in the tens of billions. In its current state, facial privacy in the United States depends on American corporations opting not to collect the public data, an option rarely chosen. Much research has been done in the area of suppressing recognition abilities, giving users the ability to …

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

A Fine-Grained Attribute Based Data Retrieval With Proxy Re-Encryption Scheme For Data Outsourcing Systems, Hanshu Hong, Ximeng Liu, Zhixin Sun

Research Collection School Of Computing and Information Systems

Attribute based encryption is suitable for data protection in data outsourcing systems such as cloud computing. However, the leveraging of encryption technique may retrain some routine operations over the encrypted data, particularly in the field of data retrieval. This paper presents an attribute based date retrieval with proxy re-encryption (ABDR-PRE) to provide both fine-grained access control and retrieval over the ciphertexts. The proposed scheme achieves fine-grained data access management by adopting KP-ABE mechanism, a delegator can generate the re-encryption key and search indexes for the ciphertexts to be shared over the target delegatee’s attributes. Throughout the process of data sharing, …

Functional Signatures: New Definition And Constructions, Qingwen Guo, Qiong Huang, Sha Ma, Meiyan Xiao, Guomin Yang, Willy Susilo

Research Collection School Of Computing and Information Systems

Functional signatures (FS) enable a master authority to delegate its signing privilege to an assistant. Concretely, the master authority uses its secret key sk(F) to issue a signing key sk(f) for a designated function f is an element of F-FS and sends both f and sk(f) to the assistant E, which is then able to compute a signature sigma(f) with respect to pk(F) for a message y in the range of f. In this paper, we modify the syntax of FS slightly to support the application scenario where a certificate of authorization is necessary. Compared with the original FS, our …

Concise Mercurial Subvector Commitments: Definitions And Constructions, Yannan Li, Willy Susilo, Guomin Yang, Tran Viet Xuan Phuong, Yong Yu, Dongxi Liu

Research Collection School Of Computing and Information Systems

Vector commitment and its variants have attracted a lot of attention recently as they have been exposed to a wide range of applications in blockchain. Two special extensions of vector commitments, namely subvector commitments and mercurial commitments, have been proposed with attractive features that are desirable in many applications. Nevertheless, to the best of our knowledge, a single construction satisfying all those attractive features is still missing. In this work, we analyze those important properties and propose a new primitive called mercurial subvector commitments, which are efficiently updatable, mercurial hiding, position binding, and aggregatable. We formalize the system model and …

Detecting Malicious Vbscripts Using Anomaly Host Based Ids Based On Principal Component Analysis (Pca), Racha M. El-Sokkary

Archived Theses and Dissertations

No abstract provided.

Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry

Computer Science Faculty Research

The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this …

Memory Forensics Comparison Of Apple M1 And Intel Architecture Using Volatility Framework, Joshua Duke

LSU Master's Theses

Memory forensics allows an investigator to get a full picture of what is occurring on-device at the time that a memory sample is captured and is frequently used to detect and analyze malware. Malicious attacks have evolved from living on disk to having persistence mechanisms in the volatile memory (RAM) of a device and the information that is captured in memory samples contains crucial information for full forensic analysis by cybersecurity professionals. Recently, Apple unveiled computers containing a custom designed system on a chip (SoC) called the M1 that is based on ARM architecture. Our research focused on the differences …

The Maritime Domain Awareness Center– A Human-Centered Design Approach, Gary Gomez

Political Science & Geography Faculty Publications

This paper contends that Maritime Domain Awareness Center (MDAC) design should be a holistic approach integrating established knowledge about human factors, decision making, cognitive tasks, complexity science, and human information interaction. The design effort should not be primarily a technology effort that focuses on computer screens, information feeds, display technologies, or user interfaces. The existence of a room with access to vast amounts of information and wall-to-wall video screens of ships, aircraft, weather data, and other regional information does not necessarily correlate to possessing situation awareness. Fundamental principles of human-centered information design should guide MDAC design and technology selection, and …

Don't Bite The Bait: Phishing Attack For Internet Banking (E-Banking), Ilker Kara

Journal of Digital Forensics, Security and Law

Phishing attacks are based on obtaining desired information from users quickly and easily with the help of misdirecting, panicking, curiosity, or excitement. Most of the phishing web sites are designed on internet banking(e-banking) and the attackers can acquire financial information of misled users with the tactics and discourses they develop. Despite the increase of prevention techniques against phishing attacks day by day, an effective solution could not be found for this issue due to the human factor. Because of this reason, real phishing attack studies are essential to study and analyze the attackers’ attack techniques and strategies. This study focused …

Developing An International Framework For Addressing Non-State Actors In Cyberspace, Joanna C. Di Scipio

Cybersecurity Undergraduate Research Showcase

On May 7, 2021, Colonial Pipeline shut down its operations following a ransomware attack by the criminal group DarkSide (Bordoff, 2021). It took five days to resume normal operations, but this short period led to panic buying, rising prices, and significant gas shortages. The attack underscores an emerging threat in the landscape of cybersecurity: critical infrastructure attacks carried out by non-state actors.

Self-Supervised Perceptual Ad-Blocker, Killian Robinson

Cybersecurity Undergraduate Research Showcase

This project proposes a new self-supervised ad-blocker to minimize the amount of human effort required to effectively combat pushed advertisements. Current ad-blocker models are expensive to develop and not always effective in identifying advertisements. We investigated the possibility of solving these problems with the introduction of a deep learning, self-supervised ad-blocker model. More specifically, the proposed ad-blocker will be trained in a self-supervised fashion to tackle the issue of lacking labelled training data. The proposed solution was prototyped using Pytorch and achieved a detection accuracy of 81% on a diverse selection of popular websites.

Protection Of Patient Privacy On Mobile Device Machine Learning, Matthew Nguyen

Cybersecurity Undergraduate Research Showcase

An existing StudentLife Study mobile dataset was evaluated and organized to be applied to different machine learning methods. Different variables like user activity, exercise, sleep, study space, social, and stress levels are optimized to train a model that could predict user stress level. The different machine learning methods would test if both patient data privacy and training efficiency can be ensured.

Gdpr, Pipl & Lgpd: Privacy Regulations & Policies Across The Globe, Raymond H. Geistel

Cybersecurity Undergraduate Research Showcase

Several privacy laws around the world are adopting similar regulations to the GPDR; this has effects on privacy policies of companies providing services in across multiple countries & continents. While these regulations share many attributes, their differing requirements can make things difficult for companies regarding said policies. Automation could be a potential solution to both analyze and compare regulations from different nations & international organizations, analyze and monitor privacy policy adherence to said regulations.

How Secure Are Android And Apple’S Operating Systems And Based Applications Against Cyber Attacks And Cyber Crime, Marlowe Cosby Jr.

Cybersecurity Undergraduate Research Showcase

Smartphone has become an important part of our everyday life. Android and apple are the two most used operating system (OS) for smart phones. We usually store important information in our smart phone, e.g.: credit card, bank account, driving ID, SSN. As a result, Android and Apple operating systems and applications have both been subject to a wide number of vulnerabilities and attacks. This directly effects many people being that they are the global leaders of users within their platforms reaching billions of people daily. It is important that smartphones receive better defense and security. In this paper, we aim …