Cyber-attacks are becoming more sophisticated and thereby presenting increasing challenges in accurately detecting intrusions. Failure to prevent the intrusions could degrade credibility of security services, e.g. data confidentiality, integrity, availability. Numerous intrusion detection methods have been proposed literature tackle computer threats, which can be broadly classified into Signature-based Intrusion Detection Systems (SIDS) Anomaly-based (AIDS). This survey paper presents a...

Conventional Internet of Things (IoT) ecosystems involve data streaming from sensors, through Fog devices to a centralized Cloud server. Issues that arise include privacy concerns due third party management servers, single points failure, bottleneck in flows and difficulties regularly updating firmware for millions smart point security maintenance perspective. Blockchain technologies avoid trusted parties safeguard against failure other issues. This has inspired researchers investigate...

The Internet of Things (IoT) has facilitated services without human intervention for a wide range applications, including continuous remote patient monitoring (RPM). However, the complexity RPM architectures, size data sets generated and limited power capacity devices make challenging. In this paper, we propose tier-based End to architecture that centric agent (PCA) as its center piece. PCA manages blockchain component preserve privacy when streaming from body area sensors needs be stored...

Incipient fault detection in low signal-to-noise ratio (SNR) conditions requires robust features for accurate condition-based machine health monitoring. Accurate classification is positively linked to the quality of faults. Therefore, there a need enhance before classification. This paper presents novel vibration spectrum imaging (VSI) feature enhancement procedure SNR conditions. An artificial neural network (ANN) has been used as classifier using these enhanced The normalized amplitudes...

The Internet of Things (IoT) has been rapidly evolving towards making a greater impact on everyday life to large industrial systems. Unfortunately, this attracted the attention cybercriminals who made IoT target malicious activities, opening door possible attack end nodes. Due number and diverse types devices, it is challenging task protect infrastructure using traditional intrusion detection system. To novel ensemble Hybrid Intrusion Detection System (HIDS) proposed by combining C5...

Cyberttacks are becoming increasingly sophisticated, necessitating the efficient intrusion detection mechanisms to monitor computer resources and generate reports on anomalous or suspicious activities. Many Intrusion Detection Systems (IDSs) use a single classifier for identifying intrusions. Single IDSs unable achieve high accuracy low false alarm rates due polymorphic, metamorphic, zero-day behaviors of malware. In this paper, Hybrid IDS (HIDS) is proposed by combining C5 decision tree One...

The Internet of Things (IoT) has become increasingly prevalent in various aspects our lives, enabling billions devices to connect and communicate seamlessly. However, the intricate nature IoT connections device vulnerabilities exposes security threats. To address challenges, we propose a proactive defense framework that leverages model-based approach for analysis facilitates strategies. Our proposed incorporates mechanisms combine Moving Target Defense techniques with cyber deception....

Next generation heterogeneous wireless networks offer the end users with assurance of QoS inside each access network as well during vertical handoff between them.For guaranteed QoS, algorithm must be aware, which cannot achieved use traditional RSS criteria.In this paper, we propose a novel uses received SINR from various criteria.This consider combined effects different value one being converted to equivalent target network, so can have knowledge achievable bandwidths both make decisions...

Abstract The Australian healthcare sector is a complex mix of government departments, associations, providers, professionals, and consumers. Cybersecurity attacks, which have recently increased, challenge the in many ways; however, best approaches for to manage threat are unclear. This study will report on semi-structured focus group conducted with five representatives from computer security sectors. An analysis this transcript yielded four themes: 1) securing landscape; 2) financial...

The Internet of Things (IoT) has facilitated services without human intervention for a wide range applications, including underwater monitoring, where sensors are located at various depths, and data must be transmitted to surface base stations storage processing. Ensuring that across hierarchical sensor networks kept secure private high computational cost remains challenge. In this paper, we propose multilevel monitoring architecture. Our proposal includes layer-based architecture consisting...

Microarray data are used in a range of application areas biology, although often it contains considerable numbers missing values. These values can significantly affect subsequent statistical analysis and machine learning algorithms so there is strong motivation to estimate these as accurately possible before using algorithms. While many imputation have been proposed, more robust techniques need be developed that further biological undertaken. In this paper, an innovative value algorithm...

Inchoate fault detection for machine health monitoring (MHM) demands high level of classification accuracy under poor signal-to-noise ratio (SNR) which persists in most industrial environment. Vibration signals are extensively used signature matching abnormality and diagnosis. In order to guarantee improved performance SNR, feature extraction based on statistical parameters immune Gaussian noise becomes inevitable. This paper proposes a novel framework adaptive higher cumulants (HOCs)...

Industrial Internet of Things (IIoT) deploys edge devices to act as intermediaries between sensors and actuators application servers or cloud services. Machine learning models have been widely used thwart malware attacks in such devices. However, these are vulnerable adversarial where attackers craft samples by introducing small perturbations fool a classifier misclassify them benign applications. Literature on deep networks proposes retraining defense mechanism combined with legitimate...

Fake news has become a significant challenge on online social platforms, increasing uncertainty and unwanted tension in society. The negative impact of fake political processes, public health, harmony underscores the urgency developing more effective detection systems. Existing methods for often focus solely one platform, potentially missing important clues that arise from multiple platforms. Another consideration is domain changes rapidly, making cross-domain analysis difficult than...