An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things,
2021
Singapore Management University
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,
2021
Minnesota State University, Mankato
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,
2021
Old Dominion University
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,
2021
Edith Cowan University
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,
2021
Institute for High Performance Computing
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,
2021
Xi'an Jiaotong University
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,
2021
Singapore Management University
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,
2021
Singapore Management University
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,
2021
Eastern Washington University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2021
Edith Cowan University
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,
2020
San Jose State University
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 …
