The k-means clustering algorithm is considered one of the most powerful and popular data mining algorithms in research community. However, despite its popularity, has certain limitations, including problems associated with random initialization centroids which leads to unexpected convergence. Additionally, such a requires number clusters be defined beforehand, responsible for different cluster shapes outlier effects. A fundamental problem inability handle various types. This paper provides...

With the rapid growth of cyber attacks, sharing threat intelligence (CTI) becomes essential to identify and respond attack in timely cost-effective manner. However, with lack standard languages automated analytics information, analyzing complex unstructured text CTI reports is extremely time- labor-consuming. Without addressing this challenge, will be highly impractical, uncertainty time-to-defend continue increase.

Abstract The concept of false data injection attack (FDIA) was introduced originally in the smart grid domain. While term sounds common, it specifically means case when an attacker compromises sensor readings such tricky way that undetected errors are into calculations state variables and values. Due to rapid growth Internet associated complex adaptive systems, cyber attackers interested exploiting similar attacks other application domains as healthcare, finance, defense, governance, etc. In...

Cybersecurity issues constitute a key concern of today’s technology-based economies. has become core need for providing sustainable and safe society to online users in cyberspace. Considering the rapid increase technological implementations, it turned into global necessity attempt adapt security countermeasures, whether direct or indirect, prevent systems from cyberthreats. Identifying, characterizing, classifying such threats their sources is required cyber-ecosystem. This paper focuses on...

The current healthcare sector is facing difficulty in satisfying the growing issues, expenses, and heavy regulation of quality treatment. Surely, electronic medical records (EMRs) protected health information (PHI) are highly sensitive, personally identifiable (PII). However, sharing EMRs, enhances overall treatment quality. A distributed ledger (blockchain) technology, embedded with privacy security by architecture, provides a transparent application developing platform. Privacy, security,...

The lack of explainability a decision from an Artificial Intelligence (AI) based "black box" system/model, despite its superiority in many real-world applications, is key stumbling block for adopting AI high stakes applications different domain or industry. While popular Explainable (XAI) methods approaches are available to facilitate human-friendly explanation the decision, each has own merits and demerits, with plethora open challenges. We demonstrate XAI mutual case study/task (i.e.,...

With technological advances, the generation of deepfake material is now within reach those operating consumer-grade hardware. As a result, much research has been undertaken on detection techniques. This work analysed and measured performance various techniques using multiple metrics discussed effectiveness these by examining analysing current state Unlike other existing surveys, this produced Systematic Literature Review (SLR) conducted from beginning 2021 to August 2022. SLR includes...

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 privacy preserving authentication mechanism. To this end, we propose a multi-level blockchain-based privacy-preserving protocol. The paper thoroughly explains the formation of centers, vehicles registration, key generation processes. In proposed architecture, global center (GAC) is responsible...

Anomaly detection from Big Cybersecurity Datasets is very important; however, this a challenging and computationally expensive task. Feature selection (FS) an approach to remove irrelevant redundant features select subset of features, which can improve the machine learning algorithms’ performance. In fact, FS effective preprocessing step anomaly techniques. This article’s main objective quantify accuracy scalability both supervised unsupervised effort, novel using FS, called Detection Using...

Outlier detection is used to detect abnormalities in various application domains including clustering based disease onset identification, gene expression analysis, computer network intrusion, financial fraud and human behaviour analysis. Existing methods outliers are inadequate due poor accuracy lack of any general technique. Most techniques consider either small clusters as or provide a score for being outlier each data object. These approaches have limitations high computational complexity...

Anomaly detection is an important aspect of data mining, where the main objective to identify anomalous or unusual from a given dataset. However, there no formal categorization application-specific anomaly techniques for big and this ignites confusion mi

With the widespread of Artificial Intelligence (AI)-enabled security applications, there is a need for collecting heterogeneous and scalable data sources effectively evaluating performances applications. This paper presents description new datasets, named ToN_IoT datasets that include distributed collected from Telemetry Internet Things (IoT) services, Operating systems Windows Linux, Network traffic. The aims to describe testbed architecture used collect Linux audit traces hard disk, memory...

The efficiency of cooperative communication protocols to increase the reliability and range transmission for Vehicular Ad hoc Network (VANET) is proven, but identity verification security are required be ensured. Though it difficult maintain strong network connections between vehicles because there high mobility, with help communication, possible efficiency, minimise delay, packet loss, Packet Dropping Rate (PDR). However, cooperating unknown or unauthorized could result in information...

The Industrial Internet of Things (IIoT) is creating a massive impact in wide range applications. In addition, with the forthcoming 5G and 6G technologies, vehicular ad-hoc networks will have pioneer advancements. However, security concerns are not well addressed, as should be deployed at large scale. To address concerns, especially to ensure secure emergency message transmission, blockchain-based protocol proposed this paper, where one blockchains store authentication information vehicle,...

In the modern financial market, market participants use big data analytics to gain valuable insight on historical for better decision making. Complying with three vs (i.e., velocity, volume and variety) of data, is considered as a complex system comprised many interacting high-frequency traders those make decisions based relative strengths these interactions. Researchers have put substantial scholarly input deal anomalies. From perspective, anomaly detection in has widely been ignored...