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Articles 241 - 258 of 258
Full-Text Articles in Information Security
A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall
A Practitioner Survey Exploring The Value Of Forensic Tools, Ai, Filtering, & Safer Presentation For Investigating Child Sexual Abuse Material, Laura Sanchez, Cinthya Grajeda, Ibrahim Baggili, Cory Hall
Electrical & Computer Engineering and Computer Science Faculty Publications
For those investigating cases of Child Sexual Abuse Material (CSAM), there is the potential harm of experiencing trauma after illicit content exposure over a period of time. Research has shown that those working on such cases can experience psychological distress. As a result, there has been a greater effort to create and implement technologies that reduce exposure to CSAM. However, not much work has explored gathering insight regarding the functionality, effectiveness, accuracy, and importance of digital forensic tools and data science technologies from practitioners who use them. This study focused specifically on examining the value practitioners give to the tools …
The Role Of Previous Discourse In Identifying Public Textual Cyberbullying, Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill
The Role Of Previous Discourse In Identifying Public Textual Cyberbullying, Aurelia Power, Anthony Keane, Brian Nolan, Brian O'Neill
Articles
In this paper we investigate the contribution of previous discourse in identifying elements that are key to detecting public textual cyberbullying. Based on the analysis of our dataset, we first discuss the missing cyberbullying elements and the grammatical structures representative of discourse-dependent cyberbullying discourse. Then we identify four types of discourse dependent cyberbullying constructions: (1) fully inferable constructions, (2) personal marker and cyberbullying link inferable constructions, (3) dysphemistic element and cyberbullying link inferable constructions, and (4) dysphemistic element inferable constructions. Finally, we formalise a framework to resolve the missing cyberbullying elements that proposes several resolution algorithms. The resolution algorithms target …
Security Bug Report Classification Using Feature Selection, Clustering, And Deep Learning, Tanner D. Gantzer
Security Bug Report Classification Using Feature Selection, Clustering, And Deep Learning, Tanner D. Gantzer
Graduate Theses, Dissertations, and Problem Reports (ETD)
As the numbers of software vulnerabilities and cybersecurity threats increase, it is becoming more difficult and time consuming to classify bug reports manually. This thesis is focused on exploring techniques that have potential to improve the performance of automated classification of software bug reports as security or non-security related. Using supervised learning, feature selection was used to engineer new feature vectors to be used in machine learning. Feature selection changes the vocabulary used by selecting words with the greatest impact on classification. Feature selection was able to increase the F-Score across the datasets by increasing the precision. We also explored …
Automatic Detection Of Insecure Codes In Stack Overflow, Shifu Hou
Automatic Detection Of Insecure Codes In Stack Overflow, Shifu Hou
Graduate Theses, Dissertations, and Problem Reports (ETD)
As the popularity of modern social coding paradigm such as Stack Overflow grows, its potential security risks increase as well (e.g., insecure codes could be easily embedded and distributed). To address this largely overlooked issue, we bring a new insight to exploit social coding properties in addition to code content for automatic detection of insecure code snippets in Stack Overflow. To determine if the given code snippets are insecure, we not only analyze the code content, but also utilize various kinds of relations among users, badges, questions, answers, code snippets and keywords in Stack Overflow. To model the rich semantic …
Evaluation And Understandability Of Face Image Quality Assessment, Mohammad I. Nouyed
Evaluation And Understandability Of Face Image Quality Assessment, Mohammad I. Nouyed
Graduate Theses, Dissertations, and Problem Reports (ETD)
Face image quality assessment (FIQA) has been an area of interest to researchers as a way to improve the face recognition accuracy. By filtering out the low quality images we can reduce various difficulties faced in unconstrained face recognition, such as, failure in face or facial landmark detection or low presence of useful facial information. In last decade or so, researchers have proposed different methods to assess the face image quality, spanning from fusion of quality measures to using learning based methods. Different approaches have their own strength and weaknesses. But, it is hard to perform a comparative assessment of …
Dabke: Secure Deniable Attribute-Based Key Exchange Framework, Yangguang Tian, Yingjiu Li, Guomin Yang, Willy Susilo, Yi Mu, Hui Cui, Yinghui Zhang
Dabke: Secure Deniable Attribute-Based Key Exchange Framework, Yangguang Tian, Yingjiu Li, Guomin Yang, Willy Susilo, Yi Mu, Hui Cui, Yinghui Zhang
Research Collection School Of Computing and Information Systems
We introduce the first deniable attribute-based key exchange (DABKE) framework that is resilient to impersonation attacks. We define the formal security models for DABKE framework, and propose a generic compiler that converts any attribute-based key exchanges into deniable ones. We prove that it can achieve session key security and user privacy in the standard model, and strong deniability in the simulation-based paradigm. In particular, the proposed generic compiler ensures: 1) a dishonest user cannot impersonate other user's session participation in conversations since implicit authentication is used among authorized users; 2) an authorized user can plausibly deny his/her participation after secure …
Iot Forensics Curriculum: Is It A Myth Or Reality?, Bilge Karabacak, Kemal Aydin, Andy Igonor
Iot Forensics Curriculum: Is It A Myth Or Reality?, Bilge Karabacak, Kemal Aydin, Andy Igonor
All Faculty and Staff Scholarship
In this research paper, two questions are answered. The first question is "Should universities invest in the preparation of an IoT forensics curriculum?". The second question is "If the IoT forensics curriculum is worth investing in, what are the basic building steps in the development of an loT forensics curriculum?". To answer those questions, the authors conducted a comprehensive literature review spanning academia, the private sector, and non-profit organizations. The authors also performed semi-structured interviews with two experts from academia and the private sector. The results showed that because of the proliferation of IoT technology and the increasing number of …
Privacy-Preserving Attribute-Based Keyword Search In Shared Multi-Owner Setting, Yibin Miao, Ximeng Liu, Robert H. Deng, Robert H. Deng, Jjguo Li, Hongwei Li, Jianfeng Ma
Privacy-Preserving Attribute-Based Keyword Search In Shared Multi-Owner Setting, Yibin Miao, Ximeng Liu, Robert H. Deng, Robert H. Deng, Jjguo Li, Hongwei Li, Jianfeng Ma
Research Collection Yong Pung How School Of Law
Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) facilitates search queries and supports fine-grained access control over encrypted data in the cloud. However, prior CP-ABKS schemes were designed to support unshared multi-owner setting, and cannot be directly applied in the shared multi-owner setting (where each record is accredited by a fixed number of data owners), without incurring high computational and storage costs. In addition, due to privacy concerns on access policies, most existing schemes are vulnerable to off-line keyword-guessing attacks if the keyword space is of polynomial size. Furthermore, it is difficult to identify malicious users who leak the secret keys when more …
Intelligent Malware Detection Using File-To-File Relations And Enhancing Its Security Against Adversarial Attacks, Lingwei Chen
Intelligent Malware Detection Using File-To-File Relations And Enhancing Its Security Against Adversarial Attacks, Lingwei Chen
Graduate Theses, Dissertations, and Problem Reports (ETD)
With computing devices and the Internet being indispensable in people's everyday life, malware has posed serious threats to their security, making its detection of utmost concern. To protect legitimate users from the evolving malware attacks, machine learning-based systems have been successfully deployed and offer unparalleled flexibility in automatic malware detection. In most of these systems, resting on the analysis of different content-based features either statically or dynamically extracted from the file samples, various kinds of classifiers are constructed to detect malware. However, besides content-based features, file-to-file relations, such as file co-existence, can provide valuable information in malware detection and make …
Proof-Of-Familiarity: A Privacy-Preserved Blockchain Scheme For Collaborative Medical Decision-Making, Jinhong Yang, Md Mehedi Hassan Hasan Onik, Nam-Yong Lee, Mohiuddin Ahmed, Chul-Soo Kim
Proof-Of-Familiarity: A Privacy-Preserved Blockchain Scheme For Collaborative Medical Decision-Making, Jinhong Yang, Md Mehedi Hassan Hasan Onik, Nam-Yong Lee, Mohiuddin Ahmed, Chul-Soo Kim
Research outputs 2014 to 2021
The current healthcare sector is facing difficulty in satisfying the growing issues, expenses, and heavy regulation of quality treatment. Surely, electronic medical records (EMRs) and protected health information (PHI) are highly sensitive, personally identifiable information (PII). However, the sharing of EMRs, enhances overall treatment quality. A distributed ledger (blockchain) technology, embedded with privacy and security by architecture, provides a transparent application developing platform. Privacy, security, and lack of confidence among stakeholders are the main downsides of extensive medical collaboration. This study, therefore, utilizes the transparency, security, and efficiency of blockchain technology to establish a collaborative medical decision-making scheme. This study …
Security And Accuracy Of Fingerprint-Based Biometrics: A Review, Wencheng Yang, Song Wang, Jiankun Hu, Guanglou Zhang, Craig Valli
Security And Accuracy Of Fingerprint-Based Biometrics: A Review, Wencheng Yang, Song Wang, Jiankun Hu, Guanglou Zhang, Craig Valli
Research outputs 2014 to 2021
Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two …
Inception: Virtual Space In Memory Space In Real Space, Peter Casey, Rebecca Lindsay-Decusati, Ibrahim Baggili, Frank Breitinger
Inception: Virtual Space In Memory Space In Real Space, Peter Casey, Rebecca Lindsay-Decusati, Ibrahim Baggili, Frank Breitinger
Electrical & Computer Engineering and Computer Science Faculty Publications
Virtual Reality (VR) has become a reality. With the technology's increased use cases, comes its misuse. Malware affecting the Virtual Environment (VE) may prevent an investigator from ascertaining virtual information from a physical scene, or from traditional “dead” analysis. Following the trend of antiforensics, evidence of an attack may only be found in memory, along with many other volatile data points. Our work provides the primary account for the memory forensics of Immersive VR systems, and in specific the HTC Vive. Our approach is capable of reconstituting artifacts from memory that are relevant to the VE, and is also capable …
Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles
Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework, Nir Nissim, Aviad Cohen, Jian Wu, Andrea Lanzi, Lior Rokach, Yuval Elovici, Lee Giles
Computer Science Faculty Publications
Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library …
Managing Cyber Risks & Business Exposure In The Surface Transportation Ecosystem, Jacques R. Francoeur
Managing Cyber Risks & Business Exposure In The Surface Transportation Ecosystem, Jacques R. Francoeur
Mineta Transportation Institute
This report focuses on Surface Transportation (ST), both fixed and route-based, and the growing threats to their information technology (IT) infrastructures. As an industry, ST seeks to optimize the movement of people and goods, while ensuring safety and resiliency and minimizing environmental impact. Cyber threats are a powerful medium for those with the political, social, and economic motivations and wherewithal to disrupt and destroy existing ST systems. The ultimate objective is to develop a new paradigm to define, describe, design, and deploy the most effective protection, at the lowest cost, in the shortest time within the limits of available resources. …
When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li
When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li
Research Collection School Of Computing and Information Systems
This paper proposes the first user-independent inter-keystroke timing attacks on PINs. Our attack method is based on an inter-keystroke timing dictionary built from a human cognitive model whose parameters can be determined by a small amount of training data on any users (not necessarily the target victims). Our attacks can thus be potentially launched on a large scale in real-world settings. We investigate inter-keystroke timing attacks in different online attack settings and evaluate their performance on PINs at different strength levels. Our experimental results show that the proposed attack performs significantly better than random guessing attacks. We further demonstrate that …
Informed Trading And Cybersecurity Breaches, Joshua Mitts, Eric L. Talley
Informed Trading And Cybersecurity Breaches, Joshua Mitts, Eric L. Talley
Faculty Scholarship
Cybersecurity has become a significant concern in corporate and commercial settings, and for good reason: a threatened or realized cybersecurity breach can materially affect firm value for capital investors. This paper explores whether market arbitrageurs appear systematically to exploit advance knowledge of such vulnerabilities. We make use of a novel data set tracking cybersecurity breach announcements among public companies to study trading patterns in the derivatives market preceding the announcement of a breach. Using a matched sample of unaffected control firms, we find significant trading abnormalities for hacked targets, measured in terms of both open interest and volume. Our results …
Towards Secure And Fair Iiot-Enabled Supply Chain Management Via Blockchain-Based Smart Contracts, Amal Eid Alahmadi
Towards Secure And Fair Iiot-Enabled Supply Chain Management Via Blockchain-Based Smart Contracts, Amal Eid Alahmadi
Theses and Dissertations (Comprehensive)
Integrating the Industrial Internet of Things (IIoT) into supply chain management enables flexible and efficient on-demand exchange of goods between merchants and suppliers. However, realizing a fair and transparent supply chain system remains a very challenging issue due to the lack of mutual trust among the suppliers and merchants. Furthermore, the current system often lacks the ability to transmit trade information to all participants in a timely manner, which is the most important element in supply chain management for the effective supply of goods between suppliers and the merchants. This thesis presents a blockchain-based supply chain management system in the …
Exploring Applicability Of Blockchain To Enhance Single Sign-On (Sso) Systems, Samuel Matloob
Exploring Applicability Of Blockchain To Enhance Single Sign-On (Sso) Systems, Samuel Matloob
UNF Graduate Theses and Dissertations
Single-Sign-On (SSO) systems usage has been on the rise exponentially. One of the major benefits of having an SSO system is to have a central authentication service, which other applications can use. However, SSO services are also prone to failure. If an SSO service becomes unavailable due to failure, every application that uses the SSO service become simultaneously inaccessible to users. The goal of this research is to explore a technique to mitigate the availability issue of the SSO by customizing its functionality, and distributing its data using blockchain technology over the network. The Blockchain data structure possesses inherent properties …