Information Security Commons^™

Technological Tethereds: Potential Impact Of Untrustworthy Artificial Intelligence In Criminal Justice Risk Assessment Instruments, Sonia M. Gipson Rankin

Faculty Scholarship

Issues of racial inequality and violence are front and center in today’s society, as are issues surrounding artificial intelligence (AI). This Article, written by a law professor who is also a computer scientist, takes a deep dive into understanding how and why hacked and rogue AI creates unlawful and unfair outcomes, particularly for persons of color.

Black Americans are disproportionally featured in criminal justice, and their stories are obfuscated. The seemingly endless back-to-back murders of George Floyd, Breonna Taylor, and Ahmaud Arbery, and heartbreakingly countless others have finally shaken the United States from its slumbering journey towards intentional criminal justice …

Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya

Engineering Management & Systems Engineering Theses & Dissertations

The cyber domain is a great business enabler providing many types of enterprises new opportunities such as scaling up services, obtaining customer insights, identifying end-user profiles, sharing data, and expanding to new communities. However, the cyber domain also comes with its own set of risks. Cybersecurity risk assessment helps enterprises explore these new opportunities and, at the same time, proportionately manage the risks by establishing cyber situational awareness and identifying potential consequences. Anomaly detection is a mechanism to enable situational awareness in the cyber domain. However, anomaly detection also requires one of the most extensive sets of data and features …

Cybersecurity Legislation And Ransomware Attacks In The United States, 2015-2019, Joseph Skertic

Graduate Program in International Studies Theses & Dissertations

Ransomware has rapidly emerged as a cyber threat which costs the global economy billions of dollars a year. Since 2015, ransomware criminals have increasingly targeted state and local government institutions. These institutions provide critical infrastructure – e.g., emergency services, water, and tax collection – yet they often operate using outdated technology due to limited budgets. This vulnerability makes state and local institutions prime targets for ransomware attacks. Many states have begun to realize the growing threat from ransomware and other cyber threats and have responded through legislative action. When and how is this legislation effective in preventing ransomware attacks? This …

Robust And Universal Seamless Handover Authentication In 5g Hetnets, Yinghui Zhang, Robert H. Deng, Elisa Bertino, Dong Zheng

Research Collection School Of Computing and Information Systems

The evolving fifth generation (5G) cellular networks will be a collection of heterogeneous and backward-compatible networks. With the increased heterogeneity and densification of 5G heterogeneous networks (HetNets), it is important to ensure security and efficiency of frequent handovers in 5G wireless roaming environments. However, existing handover authentication mechanisms still have challenging issues, such as anonymity, robust traceability and universality. In this paper, we address these issues by introducing RUSH, a Robust and Universal Seamless Handover authentication protocol for 5G HetNets. In RUSH, anonymous mutual authentication with key agreement is enabled for handovers by exploiting the trapdoor collision property of chameleon …

Machine Learning Based Approaches Towards Robust Android Malware Detection, Jiayun Xu

Dissertations and Theses Collection (Open Access)

The Android platform is becoming increasingly popular and numerous applications (apps) have been developed by organizations to meet the ever increasing market demand over years. Naturally, security and privacy concerns on Android apps have grabbed considerable attention from both academic and industrial
communities. Many approaches have been proposed to detect Android malware in different ways so far, and most of them produce satisfactory performance under the given Android environment settings and labelled samples. However, existing approaches suffer the following robustness problems:

In many Android malware detection approaches, specific API calls are used to build the feature sets, and their feature …

Looking Back! Using Early Versions Of Android Apps As Attack Vectors, Yue Zhang, Jian Weng, Jia-Si Wneg, Lin Hou, Anjia Yang, Ming Li, Yang Xiang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Android platform is gaining explosive popularity. This leads developers to invest resources to maintain the upward trajectory of the demand. Unfortunately, as the profit potential grows higher, the chances of these Apps getting attacked also get higher. Therefore, developers improved the security of their Apps, which limits attackers ability to compromise upgraded versions of the Apps. However, developers cannot enhance the security of earlier versions that have been released on the Play Store. The earlier versions of the App can be subject to reverse engineering and other attacks. In this paper, we find that attackers can use these earlier versions …

Cyber Supply Chain Risk Management: Implications For The Sof Future Operating Environment, J. Philip Craiger, Laurie Lindamood-Craiger, Diane M. Zorri

Publications

The emerging Cyber Supply Chain Risk Management (C-SCRM) concept assists at all levels of the supply chain in managing and mitigating risks, and the authors define C-SCRM as the process of identifying, assessing, and mitigating the risks associated with the distributed and interconnected nature of information and operational technology products and service supply chains. As Special Operations Forces increasingly rely on sophisticated hardware and software products, this quick, well-researched monograph provides a detailed accounting of C-SCRM associated laws, regulations, instructions, tools, and strategies meant to mitigate vulnerabilities and risks—and how we might best manage the evolving and ever-changing array of …

The Challenges Of Identifying Dangers Online And Predictors Of Victimization, Catherine D. Marcum

International Journal of Cybersecurity Intelligence & Cybercrime

This short paper will provide an overview of the impressive pieces included in this issue of the International Journal of Cybersecurity Intelligence and Cybercrime. This issue includes articles on the following pertinent topic, utilizing a range of approaches and methodologies: 1) online credibility; 2) cyberbullying; and 3) unauthorized access of information. An emphasis on the importance of policy development and better protection of potential victims is a common thread throughout the issue.

Weakly Supervised Segmentation Via Instance-Aware Propagation, Huang Xin, Qianshu Zhu, Yongtuo Liu, Shengfeng He

Research Collection School Of Computing and Information Systems

Peak Response Map (PRM) highlighting the discriminative regions can be extracted from a pre-trained classification network. We can accurately localize instances of each class with the help of these response maps. However, these maps cannot provide reliable information for segmentation even with off-the-shelf object proposals. This is because neither PRM nor the proposals know which regions can be regarded as a complete instance. In this paper, we tackle this problem by proposing an Instance-aware Cue propagation Network (ICN) with a new proposal-matching strategy. In particular, the ICN aims to filter out background distractions and cover the complete instance, while our …

Improving Memory Forensics Through Emulation And Program Analysis, Ryan Dominick Maggio

LSU Doctoral Dissertations

Memory forensics is an important tool in the hands of investigators. However, determining if a computer is infected with malicious software is time consuming, even for experts. Tasks that require manual reverse engineering of code or data structures create a significant bottleneck in the investigative workflow. Through the application of emulation software and symbolic execution, these strains have been greatly lessened, allowing for faster and more thorough investigation. Furthermore, these efforts have reduced the barrier for forensic investigation, so that reasonable conclusions can be drawn even by non-expert investigators. While previously Volatility had allowed for the detection of malicious hooks …

Integrated Cyberattack Detection And Handling For Nonlinear Systems With Evolving Process Dynamics Under Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Safety-critical processes are becoming increasingly automated and connected. While automation can increase effciency, it brings new challenges associated with guaranteeing safety in the presence of uncertainty especially in the presence of control system cyberattacks. One of the challenges for developing control strategies with guaranteed safety and cybersecurity properties under suffcient conditions is the development of appropriate detection strategies that work with control laws to prevent undetected attacks that have immediate closed-loop stability consequences. Achieving this, in the presence of uncertainty brought about by plant/model mismatch and process dynamics that can change with time, requires a fundamental understanding of the characteristics …

Analysis Of System Performance Metrics Towards The Detection Of Cryptojacking In Iot Devices, Richard Matthews

Masters Theses & Doctoral Dissertations

This single-case mechanism study examined the effects of cryptojacking on Internet of Things (IoT) device performance metrics. Cryptojacking is a cyber-threat that involves stealing the computational resources of devices belonging to others to generate cryptocurrencies. The resources primarily include the processing cycles of devices and the additional electricity needed to power this additional load. The literature surveyed showed that cryptojacking has been gaining in popularity and is now one of the top cyberthreats. Cryptocurrencies offer anyone more freedom and anonymity than dealing with traditional financial institutions which make them especially attractive to cybercriminals. Other reasons for the increasing popularity of …

Analyzing The Effectiveness Of Legal Regulations And Social Consequences For Securing Data, Howard B. Goodman

Masters Theses & Doctoral Dissertations

There is a wide range of concerns and challenges related to stored data security – which range from privacy and management to operations readiness, These challenges span from financial to personal and public impact. With an abundance of regulations for the enforcement of data security and emerging requirements proposed every year, organizations cannot avoid the legal or social implications of inadequate data protection. Today, public spotlight and awareness are challenging organizations to enhance how data is protected more than at any other time. For this reason, organizations have made significant efforts to improve security.

When looking at precautions or changes, …

Encryption And Decryption With A Raspberry Pi Device, Taylor Powell

Undergraduate Research Symposium

The functioning of our modern digital world relies heavily on the security of modern encryption algorithms and their resistance to systematic attempts to access secure information. For the 2020 Department of Computer Science’s Raspberry Pi Programming Competition, I decided to explore encryption and decryption techniques available to any user with some programming knowledge and a desire to secure information from unwanted access.

I developed a program which allows a user to select between three types of encryption algorithms: a Caesar Cipher, a Vigenère Cipher, and a Stream Cipher. I also gave the user the option to further secure their encrypted …

A Constructive Direst Security Threat Modeling For Drone As A Service, Fahad E. Salamh, Umit Karabiyik, Marcus Rogers

Journal of Digital Forensics, Security and Law

The technology used in drones is similar or identical across drone types and components, with many common risks and opportunities. The purpose of this study is to enhance the risk assessment procedures for Drone as a Service (DaaS) capabilities. STRIDE is an acronym that includes the following security risks: Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privileges. The paper presents a modified STRIDE threat model and prioritize its desired properties (i.e., authenticity, integrity, non-reputability, confidentiality, availability, and authorization) to generate an appropriate DaaS threat model. To this end, the proposed DIREST threat model better meets the …

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 …

A Consent Framework For The Internet Of Things In The Gdpr Era, Gerald Chikukwa

Masters Theses & Doctoral Dissertations

The Internet of Things (IoT) is an environment of connected physical devices and objects that communicate amongst themselves over the internet. The IoT is based on the notion of always-connected customers, which allows businesses to collect large volumes of customer data to give them a competitive edge. Most of the data collected by these IoT devices include personal information, preferences, and behaviors. However, constant connectivity and sharing of data create security and privacy concerns. Laws and regulations like the General Data Protection Regulation (GDPR) of 2016 ensure that customers are protected by providing privacy and security guidelines to businesses. Data …

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.

Cybersecurity Education For Non-Technical Learners, Matthew Mcnulty

Masters Theses & Doctoral Dissertations

Today’s world is increasingly reliant on technology for school, work, entertainment, and general home use. Many jobs today could not be performed without the use of computer systems or other technology. As lives become intertwined with technology, everyone will inevitably encounter malicious, vulnerable, or privacy-compromising devices or services. Unfortunately, knowledge of how to deal with these cybersecurity and privacy issues is not something that falls within the domain of common knowledge for the everyday person. Additionally, there is a lack of work being done to understand the educational needs of various groups within the general public and educate them. This …

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 commercial …

Remote Monitoring Of Memory Data Structures For Malware Detection In A Talos Ii Architecture, Robert A. Willburn

Theses and Dissertations

New forms of malware, namely xC;leless malware and rootkits, pose a threat to traditional anti-malware. In particular, Rootkits have the capacity to obscure the present state of memory from the user space of a target machine. If thishappens, anti-malware running in the user space of an axB;ected machine cannot be trusted to operate properly. To combat this threat, this research proposes the remote monitoring of memory from a second, secure processor runningOpenBMC, serving as a baseboard management controller for a POWER9 processor, which is assumed vulnerable to exploitation. The baseboard management controller includes an application called pdbg, used for debugging …

Infiniband Network Monitoring: Challenges And Possibilities, Kyle D. Hintze

Theses and Dissertations

Within the realm of High Performance Computing, the InfiniBand Architecture is among the leading interconnects used today. Capable of providing high bandwidth and low latency, InfiniBand is finding applications outside the High Performance Computing domain. One of these is critical infrastructure, encompassing almost all essential sectors as the work force becomes more connected. InfiniBand is not immune to security risks, as prior research has shown that common traffic analyzing tools cannot effectively monitor InfiniBand traffic transmitted between hosts, due to the kernel bypass nature of the IBA in conjunction with Remote Direct Memory Access operations. If Remote Direct Memory Access …

Investigating The Adoption Of Hybrid Encrypted Cloud Data Deduplication With Game Theory, Xueqin Liang, Zheng Yan, Robert H. Deng, Qinghu Zheng

Research Collection School Of Computing and Information Systems

Encrypted data deduplication, along with different preferences in data access control, brings the birth of hybrid encrypted cloud data deduplication (H-DEDU for short). However, whether H-DEDU can be successfully deployed in practice has not been seriously investigated. Obviously, the adoption of H-DEDU depends on whether it can bring economic benefits to all stakeholders. But existing economic models of cloud storage fail to support H-DEDU due to complicated interactions among stakeholders. In this article, we establish a formal economic model of H-DEDU by formulating the utilities of all involved stakeholders, i.e., data holders, data owners, and Cloud Storage Providers (CSPs). Then, …

Privacy-Preserving Federated Deep Learning With Irregular Users, Guowen Xu, Hongwei Li, Yun Zhang, Shengmin Xu, Jianting Ning, Robert H. Deng

Research Collection School Of Computing and Information Systems

Federated deep learning has been widely used in various fields. To protect data privacy, many privacy-preserving approaches have also been designed and implemented in various scenarios. However, existing works rarely consider a fundamental issue that the data shared by certain users (called irregular users) may be of low quality. Obviously, in a federated training process, data shared by many irregular users may impair the training accuracy, or worse, lead to the uselessness of the final model. In this paper, we propose PPFDL, a Privacy-Preserving Federated Deep Learning framework with irregular users. In specific, we design a novel solution to reduce …

Fast Scene Labeling Via Structural Inference, Huaidong Zhang, Chu Han, Xiaodan Zhang, Yong Du, Xuemiao Xu, Guoqiang Han, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Scene labeling or parsing aims to assign pixelwise semantic labels for an input image. Existing CNN-based models cannot leverage the label dependencies, while RNN-based models predict labels within the local context. In this paper, we propose a fast LSTM scene labeling network via structural inference. A minimum spanning tree is used to build the image structure for constructing semantic relationships. This structure allows efficient generation of direct parent-child dependencies for arbitrary levels of superpixels, and thus structural relationships can be learned with LSTM. In particular, we propose a bi-directional recurrent network to model the information flow along the parent-child path. …

Privacy-Preserving Multi-Keyword Searchable Encryption For Distributed Systems, Xueqiao Liu, Guomin Yang, Willy Susilo, Joseph Tonien, Jian Shen

Research Collection School Of Computing and Information Systems

As cloud storage has been widely adopted in various applications, how to protect data privacy while allowing efficient data search and retrieval in a distributed environment remains a challenging research problem. Existing searchable encryption schemes are still inadequate on desired functionality and security/privacy perspectives. Specifically, supporting multi-keyword search under the multi-user setting, hiding search pattern and access pattern, and resisting keyword guessing attacks (KGA) are the most challenging tasks. In this article, we present a new searchable encryption scheme that addresses the above problems simultaneously, which makes it practical to be adopted in distributed systems. It not only enables multi-keyword …

Traceable Monero: Anonymous Cryptocurrency With Enhanced Accountability, Yannan Li, Guomin Yang, Wily Susilo, Yong Yu, Man Ho Au, Dongxi Liu

Research Collection School Of Computing and Information Systems

Monero provides a high level of anonymity for both users and their transactions. However, many criminal activities might be committed with the protection of anonymity in cryptocurrency transactions. Thus, user accountability (or traceability) is also important in Monero transactions, which is unfortunately lacking in the current literature. In this paper, we fill this gap by introducing a new cryptocurrency named Traceable Monero to balance the user anonymity and accountability. Our framework relies on a tracing authority, but is optimistic, in that it is only involved when investigations in certain transactions are required. We formalize the system model and security model …

Clustering Web Users By Mouse Movement To Detect Bots And Botnet Attacks, Justin L. Morgan

Master's Theses

The need for website administrators to efficiently and accurately detect the presence of web bots has shown to be a challenging problem. As the sophistication of modern web bots increases, specifically their ability to more closely mimic the behavior of humans, web bot detection schemes are more quickly becoming obsolete by failing to maintain effectiveness. Though machine learning-based detection schemes have been a successful approach to recent implementations, web bots are able to apply similar machine learning tactics to mimic human users, thus bypassing such detection schemes. This work seeks to address the issue of machine learning based bots bypassing …

Identification Of Lsb Image Steganography Using Cover Image Comparisons, Michael Pelosi, Chuck Easttom

Journal of Digital Forensics, Security and Law

Steganography has long been used to counter forensic investigation. This use of steganography as an anti-forensics technique is becoming more widespread. This requires forensic examiners to have additional tools to more effectively detect steganography. 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. This technique is embodied in a software implementation named CounterSteg. The CounterSteg software allows detailed analysis and comparison of both the original cover …

Backup And Recovery Mechanisms Of Cassandra Database: A Review, Karina Bohora, Amol Bothe, Damini Sheth, Rupali Chopade, V. K. Pachghare

Journal of Digital Forensics, Security and Law

Cassandra is a NoSQL database having a peer-to-peer, ring-type architecture. Cassandra offers fault-tolerance, data replication for higher availability as well as ensures no single point of failure. Given that Cassandra is a NoSQL database, it is evident that it lacks the amount of research that has gone into comparatively older and more widely and broadly used SQL databases. Cassandra’s growing popularity in recent times gives rise to the need of addressing any security-related or recovery-related concerns associated with its usage. This review paper discusses the existing deletion mechanism in Cassandra and presents some identified issues related to backup and recovery …