Malbot-Drl: Malware Botnet Detection Using Deep Reinforcement Learning In Iot Networks,
2023
Edith Cowan University
Malbot-Drl: Malware Botnet Detection Using Deep Reinforcement Learning In Iot Networks, Mohammad Al-Fawa'reh, Jumana Abu-Khalaf, Patryk Szewczyk, James J. Kang
Research outputs 2022 to 2026
In the dynamic landscape of cyber threats, multi-stage malware botnets have surfaced as significant threats of concern. These sophisticated threats can exploit Internet of Things (IoT) devices to undertake an array of cyberattacks, ranging from basic infections to complex operations such as phishing, cryptojacking, and distributed denial of service (DDoS) attacks. Existing machine learning solutions are often constrained by their limited generalizability across various datasets and their inability to adapt to the mutable patterns of malware attacks in real world environments, a challenge known as model drift. This limitation highlights the pressing need for adaptive Intrusion Detection Systems (IDS), capable …
Identity-Based Edge Computing Anonymous Authentication Protocol,
2023
Edith Cowan University
Identity-Based Edge Computing Anonymous Authentication Protocol, Naixin Kang, Zhenhu Ning, Shiqiang Zhang, Sadaqat Ur Rehman, Muhammad Waqas
Research outputs 2022 to 2026
With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore, this paper proposes an identity-based …
Intrusion Detection Based On Bidirectional Long Short-Term Memory With Attention Mechanism,
2023
Edith Cowan University
Intrusion Detection Based On Bidirectional Long Short-Term Memory With Attention Mechanism, Yongjie Yang, Shanshan Tu, Raja Hashim Ali, Hisham Alasmary, Muhammad Waqas, Muhammad Nouman Amjad
Research outputs 2022 to 2026
With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. …
Predictive Taxonomy Analytics (Lasso): Predicting Outcome Types Of Cyber Breach,
2023
Singapore Management University
Predictive Taxonomy Analytics (Lasso): Predicting Outcome Types Of Cyber Breach, Jing Rong Goh, Shaun S. Wang, Yaniv Harel, Gabriel Toh
Research Collection School Of Economics
Cyber breaches are costly for the global economy and extensive efforts have gone into improving the cybersecurity infrastructure. There are numerous types of cyber breaches that vary greatly in terms of cause and impact, resulting in an extensive literature for individual cyber breach type. Our paper seeks to provide a general framework that can be easily applied to analyze different types of cyber breaches. Our framework is inspired by the taxonomy approach in the cybersecurity literature, where it was proposed that an effective set of taxonomy can provide a direction on supporting improved decision-making in cyber risk management and selecting …
Robustembed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training,
2023
Georgia State University
Robustembed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training, Javad Asl, Eduardo Blanco, Daniel Takabi
School of Cybersecurity Faculty Publications
Pre-trained language models (PLMs) have demonstrated their exceptional performance across a wide range of natural language processing tasks. The utilization of PLM-based sentence embeddings enables the generation of contextual representations that capture rich semantic information. However, despite their success with unseen samples, current PLM-based representations suffer from poor robustness in adversarial scenarios. In this paper, we propose RobustEmbed, a self-supervised sentence embedding framework that enhances both generalization and robustness in various text representation tasks and against diverse adversarial attacks. By generating high-risk adversarial perturbations to promote higher invariance in the embedding space and leveraging the perturbation within a novel contrastive …
An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot,
2023
Zhengzhou University
An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot, Zhaocheng Wang, Xueying Liu, Xinming Shao, Abdullah Alghamdi, Md. Shirajum Munir, Sujit Biswas
School of Cybersecurity Faculty Publications
Consumer Internet of Things (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem, like a smart home. Due to security and privacy concerns, blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their machine learning (ML) models using end-user data. Federated learning (FL) uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralized aggregator to safeguard the ecosystem. However, blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research introduces a novel architecture, emphasizing …
Ranked Keyword Search Over Encrypted Cloud Data Through Machine Learning Method,
2023
City University of Hong Kong
Ranked Keyword Search Over Encrypted Cloud Data Through Machine Learning Method, Yinbin Miao, Wei Zheng, Xiaohua Jia, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng
Research Collection School Of Computing and Information Systems
Ranked keyword search over encrypted data has been extensively studied in cloud computing as it enables data users to find the most relevant results quickly. However, existing ranked multi-keyword search solutions cannot achieve efficient ciphertext search and dynamic updates with forward security simultaneously. To solve the above problems, we first present a basic Machine Learning-based Ranked Keyword Search (ML-RKS) scheme in the static setting by using the k-means clustering algorithm and a balanced binary tree. ML-RKS reduces the search complexity without sacrificing the search accuracy, but is still vulnerable to forward security threats when applied in the dynamic setting. Then, …
Dial "N" For Nxdomain: The Scale, Origin, And Security Implications Of Dns Queries To Non-Existent Domains,
2023
Colorado School of Mines
Dial "N" For Nxdomain: The Scale, Origin, And Security Implications Of Dns Queries To Non-Existent Domains, Gunnan Liu, Lin Jin, Shuai Hao, Yubao Zhang, Daiping Liu, Angelos Stavrou, Haining Wang
Computer Science Faculty Publications
Non-Existent Domain (NXDomain) is one type of the Domain Name System (DNS) error responses, indicating that the queried domain name does not exist and cannot be resolved. Unfortunately, little research has focused on understanding why and how NXDomain responses are generated, utilized, and exploited. In this paper, we conduct the first comprehensive and systematic study on NXDomain by investigating its scale, origin, and security implications. Utilizing a large-scale passive DNS database, we identify 146,363,745,785 NXDomains queried by DNS users between 2014 and 2022. Within these 146 billion NXDomains, 91 million of them hold historic WHOIS records, of which 5.3 million …
Blockchain Securities Issues: Decentralized Identity System With Key Management Perspective,
2023
Georgia Southern University
Blockchain Securities Issues: Decentralized Identity System With Key Management Perspective, Olalekan O. Adaramola
College of Graduate Studies: Theses & Dissertations
Blockchain was created many years ago to solve the problems of data transfer Integrity, several years later the issues persist. Blockchain securities are one of the most important considerations to be investigated, and data integrity is about ensuring the accuracy and validity of messages such that when they are read, they are the same as when they were first written. It is of the opinion that passing information across from one person to another cannot be the same as it was first said at the onset. Our work investigated Blockchain security issues, studying Integrity emanating from transactions across the blocks …
A Longitudinal Study Of Factors That Affect User Interactions With Social Media And Email Spam,
2023
WVU
A Longitudinal Study Of Factors That Affect User Interactions With Social Media And Email Spam, Wojciech M. Mazurek
Graduate Theses, Dissertations, and Problem Reports (ETD)
Given the rapid growth of social media and the increasing prevalence of spam, it is crucial to understand users’ interactions with unsolicited content to develop effective countermeasures against spam. This thesis focuses on exploring the factors that influence users’ decisions to interact with spam on social media and email. It builds upon prior work, which serves as a foundation for further research and conducting a longitudinal analysis. Our results are based on the analysis of 221 responses collected through an online survey. The survey not only gathered demographic information such as age, gender, and race but also collected data on …
Security Of Internet Of Things (Iot) Using Federated Learning And Deep Learning — Recent Advancements, Issues And Prospects,
2023
University of the Cumberlands
Security Of Internet Of Things (Iot) Using Federated Learning And Deep Learning — Recent Advancements, Issues And Prospects, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty
Electrical & Computer Engineering Faculty Publications
There is a great demand for an efficient security framework which can secure IoT systems from potential adversarial attacks. However, it is challenging to design a suitable security model for IoT considering the dynamic and distributed nature of IoT. This motivates the researchers to focus more on investigating the role of machine learning (ML) in the designing of security models. A brief analysis of different ML algorithms for IoT security is discussed along with the advantages and limitations of ML algorithms. Existing studies state that ML algorithms suffer from the problem of high computational overhead and risk of privacy leakage. …
A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers,
2023
Old Dominion University
A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen
Electrical & Computer Engineering Faculty Publications
The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …
A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques,
2023
University of the Cumberlands
A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, Danda Rawat
Electrical & Computer Engineering Faculty Publications
IoT security is one of the prominent issues that has gained significant attention among the researchers in recent times. The recent advancements in IoT introduces various critical security issues and increases the risk of privacy leakage of IoT data. Implementation of Blockchain can be a potential solution for the security issues in IoT. This review deeply investigates the security threats and issues in IoT which deteriorates the effectiveness of IoT systems. This paper presents a perceptible description of the security threats, Blockchain based solutions, security characteristics and challenges introduced during the integration of Blockchain with IoT. An analysis of different …
Implications Of Cyberbiosecurity In Advanced Agriculture,
2023
Old Dominion University
Implications Of Cyberbiosecurity In Advanced Agriculture, Simone Stephen, Keitavius Alexander, Lucas Potter, Xavier-Lewis Palmer
Electrical & Computer Engineering Faculty Publications
The world is currently undergoing a rapid digital transformation sometimes referred to as the fourth industrial revolution. During this transformation, it is increasingly clear that many scientific fields are not prepared for this change. One specific area is agriculture. As the sector which creates global food supply, this critical infrastructure requires detailed assessment and research via newly developed technologies (Millett et al, 2019; Peccoud et al, 2018) . Despite its fundamental significance to modern civilization, many aspects of industrial agriculture have not yet adapted to the digital world. This is evident in the many vulnerabilities currently present within agricultural systems, …
A Reflection Of Typology And Verification Flaws In Consideration Of Biocybersecurity/Cyberbiosecurity: Just Another Gap In The Wall,
2023
BiosView Labs
A Reflection Of Typology And Verification Flaws In Consideration Of Biocybersecurity/Cyberbiosecurity: Just Another Gap In The Wall, Luke Potter, Kim Mossberg, Xavier Palmer
Electrical & Computer Engineering Faculty Publications
Verification is central to any process in a functional and enduring cyber-secure organization. This verification is how the validity or accuracy of a state of being is assessed (Schlick, 1936; Balci, 1998). Conversely, breakdown in verification procedures is core to the interruption of normal operations for an organization. A key problem for organizations that utilize biology as an interlock within their systems is that personnel lack sufficient ability to verify all practically relevant biological information for procedures such as a nurse logging a blood draw, or a molecular biology technician preparing agar to culture microbes for study. This has several …
S-400s, Disinformation, And Anti-American Sentiment In Turkey,
2023
Old Dominion University
S-400s, Disinformation, And Anti-American Sentiment In Turkey, Russell "Alex" Korb, Saltuk Karahan, Gowri Prathap, Ekrem Kaya, Luke Palmieri, Hamdi Kavak, Richard L. Wilson (Ed.), Major Brendan Curran (Ed.)
Political Science & Geography Faculty Publications
As social and political discourse in most countries becomes more polarized, anti-Americanism has risen not only in the Middle East and Latin America but also among the U.S. allies in Europe. Social media is one platform used to disseminate anti-American views in NATO countries, and its effectiveness can be magnified when mass media, public officials, and popular figures adopt these views. Disinformation, in particular, has gained recognition as a cybersecurity issue from 2016 onward, but disinformation can be manufactured domestically in addition to being part of a foreign influence campaign. In this paper, we analyze Turkish tweets using sentiment analysis …
A Cross-Domain Trust Model Of Smart City Iot Based On Self-Certification,
2023
Edith Cowan University
A Cross-Domain Trust Model Of Smart City Iot Based On Self-Certification, Yao Wang, Yubo Wang, Zhenhu Ning, Sadaqat Ur Rehman, Muhammad Waqas
Research outputs 2022 to 2026
Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced …
Crowdfa: A Privacy-Preserving Mobile Crowdsensing Paradigm Via Federated Analytics,
2023
Singapore Management University
Crowdfa: A Privacy-Preserving Mobile Crowdsensing Paradigm Via Federated Analytics, Bowen Zhao, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Mobile crowdsensing (MCS) systems typically struggle to address the challenge of data aggregation, incentive design, and privacy protection, simultaneously. However, existing solutions usually focus on one or, at most, two of these issues. To this end, this paper presents CROWD FA, a novel paradigm for privacy-preserving MCS through federated analytics (FA), which aims to achieve a well-rounded solution encompassing data aggregation, incentive design, and privacy protection. Specifically, inspired by FA, CROWD FA initiates an MCS computing paradigm that enables data aggregation and incentive design. Participants can perform aggregation operations on their local data, facilitated by CROWD FA, which supports various …
Seqadver: Automatic Payload Construction And Injection In Sequence-Based Android Adversarial Attack,
2023
Singapore Management University
Seqadver: Automatic Payload Construction And Injection In Sequence-Based Android Adversarial Attack, Fei Zhang, Ruitao Feng, Xiaofei Xie, Xiaohong Li, Lianshuan Shi
Research Collection School Of Computing and Information Systems
Machine learning has achieved a great success in the field of Android malware detection. In order to avoid being caught by these ML-based Android malware detection, malware authors are inclined to initiate adversarial sample attacks by tampering with mobile applications. Although machine learning has high capability, it lacks robustness against adversarial attacks. Currently, many of the adversarial attacking tools not only inject dead code into target applications, which can never be executed, but also require the injection of many benign features into a malicious APK. This can be easily noticeable by program analysis techniques. In this paper, we propose SeqAdver, …
Hybrid Warfare And Disinformation: A Ukraine War Perspective,
2023
Edith Cowan University
Hybrid Warfare And Disinformation: A Ukraine War Perspective, Sascha-Dominik Dov Bachmann, Dries Putter, Guy Duczynski
Research outputs 2022 to 2026
Misinformation, disinformation and mal information are part of the information disorder construct, dominating the information warfare domain. These are key enablers associated with grey zone operations, and an integral part of current adversaries' and competitors' hybrid warfare tool kit. Disinformation, in combination with influence operations, also plays an important role within the concept of hybrid warfare; both from a threat–and own resilience perspective. This article reflects on these information warfare tools and their application by Russia in the current Russo-Ukraine war, offering potentially considerable force multipliers in the information domain for the Russian aggressor. Hybrid warfare and associated threats, specifically …
