Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (988)
- Social and Behavioral Sciences (930)
- Law (808)
- Computer Engineering (742)
- Computer Law (728)
-
- Legal Studies (638)
- Forensic Science and Technology (617)
- Electrical and Computer Engineering (552)
- Business (485)
- Databases and Information Systems (394)
- Management Information Systems (332)
- Artificial Intelligence and Robotics (289)
- Technology and Innovation (279)
- OS and Networks (257)
- Sociology (251)
- Other Computer Sciences (237)
- Public Affairs, Public Policy and Public Administration (227)
- Software Engineering (223)
- Medicine and Health Sciences (159)
- Cybersecurity (143)
- Systems Architecture (139)
- Theory and Algorithms (135)
- Digital Communications and Networking (134)
- Education (124)
- Communication (119)
- Defense and Security Studies (119)
- Social Media (89)
- Institution
-
- Singapore Management University (1102)
- Embry-Riddle Aeronautical University (768)
- Edith Cowan University (532)
- Kennesaw State University (300)
- Old Dominion University (256)
-
- Air Force Institute of Technology (181)
- San Jose State University (117)
- Bridgewater State University (73)
- Clark University (71)
- University of New Haven (65)
- United Arab Emirates University (64)
- University of Arkansas, Fayetteville (59)
- City University of New York (CUNY) (55)
- Dakota State University (49)
- California State University, San Bernardino (34)
- Nova Southeastern University (33)
- Maurer School of Law: Indiana University (32)
- University for Business and Technology in Kosovo (30)
- University of Central Florida (24)
- University of South Alabama (23)
- University of Dayton (22)
- Franklin University (21)
- LSU New Orleans (21)
- University of Nebraska at Omaha (20)
- Wayne State University (20)
- California Polytechnic State University, San Luis Obispo (18)
- University of Kentucky (18)
- Florida Institute of Technology (17)
- Louisiana State University (16)
- Portland State University (16)
- Keyword
-
- Cybersecurity (317)
- Security (246)
- Privacy (163)
- Computer security (101)
- Digital forensics (89)
-
- Information security (89)
- Blockchain (88)
- Machine learning (82)
- Authentication (71)
- Cryptography (71)
- Cloud computing (68)
- Encryption (65)
- Data privacy (62)
- [RSTDPub] (54)
- Cyber security (53)
- Access control (50)
- Data protection (47)
- Network security (45)
- Malware (41)
- Machine Learning (39)
- Android (38)
- Artificial intelligence (38)
- Computer networks--Security measures (38)
- Cybercrime (38)
- Internet of Things (36)
- Deep learning (34)
- Digital Forensics (34)
- Intrusion detection (33)
- MPA (33)
- Forensics (31)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (1051)
- Journal of Digital Forensics, Security and Law (536)
- Australian Information Security Management Conference (224)
- Theses and Dissertations (212)
- Annual ADFSL Conference on Digital Forensics, Security and Law (186)
-
- Journal of Cybersecurity Education, Research and Practice (171)
- Master's Projects (107)
- KSU Proceedings on Cybersecurity Education, Research and Practice (97)
- Cybersecurity Undergraduate Research Showcase (90)
- Research outputs 2022 to 2026 (84)
- International Journal of Cybersecurity Intelligence & Cybercrime (72)
- School of Professional Studies (71)
- Electrical & Computer Engineering and Computer Science Faculty Publications (58)
- Australian Digital Forensics Conference (50)
- Theses (45)
- Australian Information Warfare and Security Conference (44)
- Research outputs 2014 to 2021 (41)
- Computer Science Faculty Publications (40)
- Masters Theses & Doctoral Dissertations (34)
- CCAC Theses and Dissertations (33)
- Graduate Theses and Dissertations (33)
- Articles by Maurer Faculty (31)
- Publications (29)
- Electronic Theses and Dissertations (25)
- UBT International Conference (24)
- VMASC Publications (24)
- Electrical & Computer Engineering Faculty Publications (23)
- Open Educational Resources (23)
- Faculty Publications (22)
- LSU New Orleans Theses and Dissertations (21)
- Publication Type
Articles 1501 - 1530 of 4669
Full-Text Articles in Information Security
A Serious Game For Social Engineering Awareness Creation, Fabian Muhly, Philipp Leo, Stefano Caneppele
A Serious Game For Social Engineering Awareness Creation, Fabian Muhly, Philipp Leo, Stefano Caneppele
Journal of Cybersecurity Education, Research and Practice
Social engineering is a method used by offenders to deceive their targets utilizing rationales of human psychology. Offenders aim to exploit information and use them for intelligence purposes or financial gains. Generating resilience against these malicious methods is still challenging. Literature shows that serious gaming learning approaches are used more frequently to instill lasting retention effects. Serious games are interactive, experiential learning approaches that impart knowledge about rationales and concepts in a way that fosters retention. In three samples and totally 97 participants the study at hand evaluated a social engineering serious game for participants’ involvement and instruction compliance during …
An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things, Jiannan Wei, Tran Viet Xuan Phuong, Guomin Yang
An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things, Jiannan Wei, Tran Viet Xuan Phuong, Guomin Yang
Research Collection School Of Computing and Information Systems
As an essential element of the next generation Internet, Internet of Things (IoT) has been undergoing an extensive development in recent years. In addition to the enhancement of peoples daily lives, IoT devices also generate/gather a massive amount of data that could be utilized by machine learning and big data analytics for different applications. Due to the machine-to-machine communication nature of IoT, data security and privacy are crucial issues that must be addressed to prevent different cyber attacks (e.g., impersonation and data pollution/poisoning attacks). Nevertheless, due to the constrained computation power and the diversity of IoT devices, it is a …
A Methodology For Detecting Credit Card Fraud, Kayode Ayorinde
A Methodology For Detecting Credit Card Fraud, Kayode Ayorinde
All Graduate Theses, Dissertations, and Other Capstone Projects
Fraud detection has appertained to many industries such as banking, retails, financial services, healthcare, etc. As we know, fraud detection is a set of campaigns undertaken to avert the acquisition of illegal means to obtain money or property under false pretense. With an unlimited and growing number of ways fraudsters commit fraud crimes, detecting online fraud was so tricky to achieve. This research work aims to examine feasible ways to identify credit card fraudulent activities that negatively impact financial institutes. In the United States, an average of U.S consumers lost a median of $429 from credit card fraud in 2017, …
Matters Of Biocybersecurity With Consideration To Propaganda Outlets And Biological Agents, Xavier-Lewis Palmer, Ernestine Powell, Lucas Potter, Thaddeus Eze (Ed.), Lee Speakman (Ed.), Cyril Onwubiko (Ed.)
Matters Of Biocybersecurity With Consideration To Propaganda Outlets And Biological Agents, Xavier-Lewis Palmer, Ernestine Powell, Lucas Potter, Thaddeus Eze (Ed.), Lee Speakman (Ed.), Cyril Onwubiko (Ed.)
Electrical & Computer Engineering Faculty Publications
The modern era holds vast modalities in human data utilization. Within Biocybersecurity (BCS), categories of biological information, especially medical information transmitted online, can be viewed as pathways to destabilize organizations. Therefore, analysis of how the public, along with medical providers, process such data, and the methods by which false information, particularly propaganda, can be used to upset the flow of verified information to populations of medical professionals, is important for maintenance of public health. Herein, we discuss some interplay of BCS within the scope of propaganda and considerations for navigating the field.
An Investigation Into The Efficacy Of Url Content Filtering Systems, Brett Ronald Turner
An Investigation Into The Efficacy Of Url Content Filtering Systems, Brett Ronald Turner
Theses: Doctorates and Masters
Content filters are used to restrict to restrict minors from accessing to online content deemed inappropriate. While much research and evaluation has been done on the efficiency of content filters, there is little in the way of empirical research as to their efficacy. The accessing of inappropriate material by minors, and the role content filtering systems can play in preventing the accessing of inappropriate material, is largely assumed with little or no evidence. This thesis investigates if a content filter implemented with the stated aim of restricting specific Internet content from high school students achieved the goal of stopping students …
Privattnet: Predicting Privacy Risks In Images Using Visual Attention, Zhang Chen, Thivya Kandappu, Vigneshwaran Subbaraju
Privattnet: Predicting Privacy Risks In Images Using Visual Attention, Zhang Chen, Thivya Kandappu, Vigneshwaran Subbaraju
Research Collection School Of Computing and Information Systems
Visual privacy concerns associated with image sharing is a critical issue that need to be addressed to enable safe and lawful use of online social platforms. Users of social media platforms often suffer from no guidance in sharing sensitive images in public, and often face with social and legal consequences. Given the recent success of visual attention based deep learning methods in measuring abstract phenomena like image memorability, we are motivated to investigate whether visual attention based methods could be useful in measuring psychophysical phenomena like “privacy sensitivity”. In this paper we propose PrivAttNet – a visual attention based approach, …
Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu
Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu
Research Collection School Of Computing and Information Systems
With the rapid growth of Android malware, many machine learning-based malware analysis approaches are proposed to mitigate the severe phenomenon. However, such classifiers are opaque, non-intuitive, and difficult for analysts to understand the inner decision reason. For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features. Unfortunately, the explanation results obtained in the malware analysis domain cannot achieve a consensus in general, which makes the analysts confused about whether they can trust such results. In this work, we propose principled guidelines to assess the quality of five explanation approaches by designing three critical …
Privacy-Preserving Outsourced Clinical Decision Support System In The Cloud, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang
Privacy-Preserving Outsourced Clinical Decision Support System In The Cloud, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang
Research Collection School Of Computing and Information Systems
In this paper, we propose a privacy-preserving clinical decision support system using Naïve Bayesian (NB) classifier, hereafter referred to as Peneus, designed for the outsourced cloud computing environment. Peneus allows one to use patient health information to train the NB classifier privately, which can then be used to predict a patient's (undiagnosed) disease based on his/her symptoms in a single communication round. Specifically, we design secure Single Instruction Multiple Data (SIMD) integer circuits using the fully homomorphic encryption scheme, which can greatly increase the performance compared with the original secure integer circuit. Then, we present a privacy-preserving historical Personal Health …
Enabling Efficient Spatial Keyword Queries On Encrypted Data With Strong Security Guarantees, Xiangyu Wang, Jianfeng Ma, Feng Li, Ximeng Liu, Yinbin Miao, Robert H. Deng
Enabling Efficient Spatial Keyword Queries On Encrypted Data With Strong Security Guarantees, Xiangyu Wang, Jianfeng Ma, Feng Li, Ximeng Liu, Yinbin Miao, Robert H. Deng
Research Collection School Of Computing and Information Systems
Structured Encryption (STE), which allows a server to provide secure search services on encrypted data structures, has been widely investigated in recent years. To meet expressive search requirements in practical applications, a large number of STE constructions have been proposed either on textual keywords or spatial data. However, STE on spatio-textual data, which are widely used in location-based services, has not been fully investigated. In this paper, we formally define the notion of Spatial Keyword Structured Encryption (SKSE) and propose several concrete SKSE constructions with various efficiencysecurity trade-offs. Firstly, we propose a basic construction with linear search complexity, which only …
Password-Less Two-Factor Authentication Using Scannable Barcodes On A Mobile Device, Grant M. Callant Ii
Password-Less Two-Factor Authentication Using Scannable Barcodes On A Mobile Device, Grant M. Callant Ii
EWU Masters Thesis Collection
Currently, passwords are the default method used to authenticate users. As hardware continues to advance in speed, breaking these passwords becomes easier. The traditional solution to this problem is ever increasing password complexity and two-factor authentication. However, users become strained under overly complex login systems and often circumvent them. Two-factor authentication also adds to this complexity and many forms of two-factor authentication are inherently insecure. In answer to these problems, this project proposes a password-less multi-factor authentication system, which leverages the tried-and-proven existing technologies, asymmetric cryptography, digital signatures, and biometric authentication. Simulated user testing shows promising results, suggesting that registration …
Real-Time Monitoring As A Supplementary Security Component Of Vigilantism In Modern Network Environments, Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan
Real-Time Monitoring As A Supplementary Security Component Of Vigilantism In Modern Network Environments, Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan
Research outputs 2014 to 2021
© 2020, The Author(s). The phenomenon of network vigilantism is autonomously attributed to how anomalies and obscure activities from adversaries can be tracked in real-time. Needless to say, in today’s dynamic, virtualized, and complex network environments, it has become undeniably necessary for network administrators, analysts as well as engineers to practice network vigilantism, on traffic as well as other network events in real-time. The reason is to understand the exact security posture of an organization’s network environment at any given time. This is driven by the fact that modern network environments do, not only present new opportunities to organizations but …
An Energy-Efficient And Secure Data Inference Framework For Internet Of Health Things: A Pilot Study, James Jin Kang, Mahdi Dibaei, Gang Luo, Wencheng Yang, Paul Haskell-Dowland, Xi Zheng
An Energy-Efficient And Secure Data Inference Framework For Internet Of Health Things: A Pilot Study, James Jin Kang, Mahdi Dibaei, Gang Luo, Wencheng Yang, Paul Haskell-Dowland, Xi Zheng
Research outputs 2014 to 2021
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Privacy protection in electronic healthcare applications is an important consideration, due to the sensitive nature of personal health data. Internet of Health Things (IoHT) networks that are used within a healthcare setting have unique challenges and security requirements (integrity, authentication, privacy, and availability) that must also be balanced with the need to maintain efficiency in order to conserve battery power, which can be a significant limitation in IoHT devices and networks. Data are usually transferred without undergoing filtering or optimization, and this traffic can overload sensors and cause rapid battery consumption …
A Secured Privacy-Preserving Multi-Level Blockchain Framework For Cluster Based Vanet, A. F.M.Suaib Akhter, Mohiuddin Ahmed, A. F.M.Shahen Shah, Adnan Anwar, Ahmet Zengin
A Secured Privacy-Preserving Multi-Level Blockchain Framework For Cluster Based Vanet, A. F.M.Suaib Akhter, Mohiuddin Ahmed, A. F.M.Shahen Shah, Adnan Anwar, Ahmet Zengin
Research outputs 2014 to 2021
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Existing research shows that Cluster-based Medium Access Control (CB-MAC) protocols perform well in controlling and managing Vehicular Ad hoc Network (VANET), but requires ensuring improved security and privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving authentication protocol. The paper thoroughly explains the formation of the authentication centers, vehicles registration, and key generation processes. In the proposed architecture, a global authentication center (GAC) is responsible for storing all vehicle information, while Local Authentication Center (LAC) maintains a blockchain to enable quick handover between internal clusters of vehicle. …
A Blockchain-Based Authentication Protocol For Cooperative Vehicular Ad Hoc Network, A. F. M. S. Akhter, Mohiuddin Ahmed, A. F. M. S. Shah, Adnan Anwar, A. S. M. Kayes, Ahmet Zengin
A Blockchain-Based Authentication Protocol For Cooperative Vehicular Ad Hoc Network, A. F. M. S. Akhter, Mohiuddin Ahmed, A. F. M. S. Shah, Adnan Anwar, A. S. M. Kayes, Ahmet Zengin
Research outputs 2014 to 2021
The efficiency of cooperative communication protocols to increase the reliability and range of transmission for Vehicular Ad hoc Network (VANET) is proven, but identity verification and communication security are required to be ensured. Though it is difficult to maintain strong network connections between vehicles because of there high mobility, with the help of cooperative communication, it is possible to increase the communication efficiency, minimise delay, packet loss, and Packet Dropping Rate (PDR). However, cooperating with unknown or unauthorized vehicles could result in information theft, privacy leakage, vulnerable to different security attacks, etc. In this paper, a blockchain based secure and …
A Secured Message Transmission Protocol For Vehicular Ad Hoc Networks, A. F. M. Suaib Akhter, A. F. M. Shahen Shah, Mohiuddin Ahmed, Nour Moustafa, Unal Çavuşoğlu, Ahmet Zengin
A Secured Message Transmission Protocol For Vehicular Ad Hoc Networks, A. F. M. Suaib Akhter, A. F. M. Shahen Shah, Mohiuddin Ahmed, Nour Moustafa, Unal Çavuşoğlu, Ahmet Zengin
Research outputs 2014 to 2021
Vehicular Ad hoc Networks (VANETs) become a very crucial addition in the Intelligent Transportation System (ITS). It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources. To overcome these challenges, we propose a blockchain-based Secured Cluster-based MAC (SCB-MAC) protocol. The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages. The message which contains emergency information and requires Strict Delay Requirement (SDR) for transmission are called safety messages (SM). Cluster Members (CMs) sign SMs …
A Review Of Security Standards And Frameworks For Iot-Based Smart Environments, Nickson M. Karie, Nor Masri Sahri, Wencheng Yang, Craig Valli, Victor R. Kebande
A Review Of Security Standards And Frameworks For Iot-Based Smart Environments, Nickson M. Karie, Nor Masri Sahri, Wencheng Yang, Craig Valli, Victor R. Kebande
Research outputs 2014 to 2021
Assessing the security of IoT-based smart environments such as smart homes and smart cities is becoming fundamentally essential to implementing the correct control measures and effectively reducing security threats and risks brought about by deploying IoT-based smart technologies. The problem, however, is in finding security standards and assessment frameworks that best meets the security requirements as well as comprehensively assesses and exposes the security posture of IoT-based smart environments. To explore this gap, this paper presents a review of existing security standards and assessment frameworks which also includes several NIST special publications on security techniques highlighting their primary areas of …
Federated Deep Learning For Cyber Security In The Internet Of Things: Concepts, Applications, And Experimental Analysis, Mohamed Amine Ferrag, Othmane Friha, Leandros Maglaras, Helge Janicke, Lei Shu
Federated Deep Learning For Cyber Security In The Internet Of Things: Concepts, Applications, And Experimental Analysis, Mohamed Amine Ferrag, Othmane Friha, Leandros Maglaras, Helge Janicke, Lei Shu
Research outputs 2014 to 2021
In this article, we present a comprehensive study with an experimental analysis of federated deep learning approaches for cyber security in the Internet of Things (IoT) applications. Specifically, we first provide a review of the federated learning-based security and privacy systems for several types of IoT applications, including, Industrial IoT, Edge Computing, Internet of Drones, Internet of Healthcare Things, Internet of Vehicles, etc. Second, the use of federated learning with blockchain and malware/intrusion detection systems for IoT applications is discussed. Then, we review the vulnerabilities in federated learning-based security and privacy systems. Finally, we provide an experimental analysis of federated …
Biometrics For Internet‐Of‐Things Security: A Review, Wencheng Yang, Song Wang, Nor Masri Sahri, Nickson M. Karie, Mohiuddin Ahmed, Craig Valli
Biometrics For Internet‐Of‐Things Security: A Review, Wencheng Yang, Song Wang, Nor Masri Sahri, Nickson M. Karie, Mohiuddin Ahmed, Craig Valli
Research outputs 2014 to 2021
The large number of Internet‐of‐Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric‐based authentication systems for IoT are discussed and classified based on different biometric …
Digital Forensic Readiness In Operational Cloud Leveraging Iso/Iec 27043 Guidelines On Security Monitoring, Sheunesu Makura, H. S. Venter, Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan, Sadi Alawadi
Digital Forensic Readiness In Operational Cloud Leveraging Iso/Iec 27043 Guidelines On Security Monitoring, Sheunesu Makura, H. S. Venter, Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan, Sadi Alawadi
Research outputs 2014 to 2021
An increase in the use of cloud computing technologies by organizations has led to cybercriminals targeting cloud environments to orchestrate malicious attacks. Conversely, this has led to the need for proactive approaches through the use of digital forensic readiness (DFR). Existing studies have attempted to develop proactive prototypes using diverse agent-based solutions that are capable of extracting a forensically sound potential digital evidence. As a way to address this limitation and further evaluate the degree of PDE relevance in an operational platform, this study sought to develop a prototype in an operational cloud environment to achieve DFR in the cloud. …
Digital Forensic Readiness Intelligence Crime Repository, Victor R. Kebande, Nickson M. Karie, Kim-Kwang R. Choo, Sadi Alawadi
Digital Forensic Readiness Intelligence Crime Repository, Victor R. Kebande, Nickson M. Karie, Kim-Kwang R. Choo, Sadi Alawadi
Research outputs 2014 to 2021
It may not always be possible to conduct a digital (forensic) investigation post-event if there is no process in place to preserve potential digital evidence. This study posits the importance of digital forensic readiness, or forensic-by-design, and presents an approach that can be used to construct a Digital Forensic Readiness Intelligence Repository (DFRIR). Based on the concept of knowledge sharing, the authors leverage this premise to suggest an intelligence repository. Such a repository can be used to cross-reference potential digital evidence (PDE) sources that may help digital investigators during the process. This approach employs a technique of capturing PDE from …
A Neat Approach To Malware Classification, Jason Do
A Neat Approach To Malware Classification, Jason Do
Master's Projects
Current malware detection software often relies on machine learning, which is seen as an improvement over signature-based techniques. Problems with a machine learning based approach can arise when malware writers modify their code with the intent to evade detection. This leads to a cat and mouse situation where new models must constantly be trained to detect new malware variants. In this research, we experiment with genetic algorithms as a means of evolving machine learning models to detect malware. Genetic algorithms, which simulate natural selection, provide a way for models to adapt to continuous changes in a malware families, and thereby …
Signature Identification And Verification Systems: A Comparative Study On The Online And Offline Techniques, Nehal Hamdy Al-Banhawy, Heba Mohsen, Neveen I. Ghali Prof.
Signature Identification And Verification Systems: A Comparative Study On The Online And Offline Techniques, Nehal Hamdy Al-Banhawy, Heba Mohsen, Neveen I. Ghali Prof.
Future Computing and Informatics Journal
Handwritten signature identification and verification has become an active area of research in recent years. Handwritten signature identification systems are used for identifying the user among all users enrolled in the system while handwritten signature verification systems are used for authenticating a user by comparing a specific signature with his signature that is stored in the system. This paper presents a review for commonly used methods for preprocessing, feature extraction and classification techniques in signature identification and verification systems, in addition to a comparison between the systems implemented in the literature for identification techniques and verification techniques in online and …
Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao
Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao
Articles
It is often the case with new technologies that it is very hard to predict their long-term impacts and as a result, although new technology may be beneficial in the short term, it can still cause problems in the longer term. This is what happened with oil by-products in different areas: the use of plastic as a disposable material did not take into account the hundreds of years necessary for its decomposition and its related long-term environmental damage. Data is said to be the new oil. The message to be conveyed is associated with its intrinsic value. But as in …
Malware Classification With Gaussian Mixture Model-Hidden Markov Models, Jing Zhao
Malware Classification With Gaussian Mixture Model-Hidden Markov Models, Jing Zhao
Master's Projects
Discrete hidden Markov models (HMM) are often applied to the malware detection and classification problems. However, the continuous analog of discrete HMMs, that is, Gaussian mixture model-HMMs (GMM-HMM), are rarely considered in the field of cybersecurity. In this study, we apply GMM-HMMs to the malware classification problem and we compare our results to those obtained using discrete HMMs. As features, we consider opcode sequences and entropy-based sequences. For our opcode features, GMM-HMMs produce results that are comparable to those obtained using discrete HMMs, whereas for our entropy-based features, GMM-HMMs generally improve on the classification results that we can attain with …
Improving A Wireless Localization System Via Machine Learning Techniques And Security Protocols, Zachary Yorio
Improving A Wireless Localization System Via Machine Learning Techniques And Security Protocols, Zachary Yorio
Masters Theses, 2020-current
The recent advancements made in Internet of Things (IoT) devices have brought forth new opportunities for technologies and systems to be integrated into our everyday life. In this work, we investigate how edge nodes can effectively utilize 802.11 wireless beacon frames being broadcast from pre-existing access points in a building to achieve room-level localization. We explain the needed hardware and software for this system and demonstrate a proof of concept with experimental data analysis. Improvements to localization accuracy are shown via machine learning by implementing the random forest algorithm. Using this algorithm, historical data can train the model and make …
Malware Classification Using Lstms, Dennis Dang
Malware Classification Using Lstms, Dennis Dang
Master's Projects
Signature and anomaly based detection have long been quintessential techniques used in malware detection. However, these techniques have become increasingly ineffective as malware becomes more complex. Researchers have therefore turned to deep learning to construct better performing models. In this project, we create four different long-short term memory (LSTM) models and train each model to classify malware by family type. Our data consists of opcodes extracted from malware executables. We employ techniques used in natural language processing (NLP) such as word embedding and bidirection LSTMs (biLSTM). We also use convolutional neural networks (CNN). We found that our model consisting of …
Using Eye-Gaze To Evaluate Neural Attention, Shahansha Salim
Using Eye-Gaze To Evaluate Neural Attention, Shahansha Salim
Master’s Dissertations
The ability to selectively concentrate on areas of interest while ignoring the rest is termed as attention in human beings. This ability has played a key role in survival as well as information processing. Neural Attention is said to be an effort to bring similar action of selectively concentrating areas of relevance in deep neural networks. This simple yet powerful concept has attracted a lot of research in recent years, yielding breakthrough results in Natural Language Processing (NLP) problems and main stream Computer Vision problems such as Image Caption Generation, Neural Machine Translation (NMT), Visual Question Answering (VQA), Action Recognition, …
Thaw Publications, Carl Landwehr, David Kotz
Thaw Publications, Carl Landwehr, David Kotz
Computer Science Technical Reports
In 2013, the National Science Foundation's Secure and Trustworthy Cyberspace program awarded a Frontier grant to a consortium of four institutions, led by Dartmouth College, to enable trustworthy cybersystems for health and wellness. As of this writing, the Trustworthy Health and Wellness (THaW) project's bibliography includes more than 130 significant publications produced with support from the THaW grant; these publications document the progress made on many fronts by the THaW research team. The collection includes dissertations, theses, journal papers, conference papers, workshop contributions and more. The bibliography is organized as a Zotero library, which provides ready access to citation materials …
On Improving The Memorability Of System-Assigned Recognition-Based Passwords, Mahdi Nasrullah Al-Ameen, Sonali T. Marne, Kanis Fatema, Matthew Wright, Shannon Scielzo
On Improving The Memorability Of System-Assigned Recognition-Based Passwords, Mahdi Nasrullah Al-Ameen, Sonali T. Marne, Kanis Fatema, Matthew Wright, Shannon Scielzo
Computer Science Faculty and Staff Publications
User-chosen passwords reflecting common strategies and patterns ease memorization but offer uncertain and often weak security, while system-assigned passwords provide higher security guarantee but suffer from poor memorability. We thus examine the technique to enhance password memorability that incorporates a scientific understanding of long-term memory. In particular, we examine the efficacy of providing users with verbal cues—real-life facts corresponding to system-assigned keywords. We also explore the usability gain of including images related to the keywords along with verbal cues. In our multi-session lab study with 52 participants, textual recognition-based scheme offering verbal cues had a significantly higher login success …
Narrowing The Wealth And Income Gap In Poland, China, And The United States, Cyndy Carboo, Zhiling Song, Jiawei Feng, Xudong Zhu
Narrowing The Wealth And Income Gap In Poland, China, And The United States, Cyndy Carboo, Zhiling Song, Jiawei Feng, Xudong Zhu
School of Professional Studies
With the widespread of globalization, the wealth gap continues to widen globally. Due to the enormous differences in national conditions and political systems of various countries, this article selects China, the United States, and Poland as the research objects, and uses a specific time unit as the benchmark, and mainly focuses on the four directions of medical care, education, job opportunities, and pensions. A reader could understand the correlation between the wealth gap and multiple factors deeply in this article. This article analyzes the impact of income disparity on these three countries and proposes solutions to help narrow the gap …