Cyber Supply Chain (CSC) system is complex which involves different sub-systems performing various tasks. Security in supply chain is challenging due to the inherent vulnerabilities and threats from any part of the system which can be exploited at any point within the supply chain. This can cause a severe disruption on the overall business continuity. Therefore, it is paramount important to understand and predicate the threats so that organization can undertake necessary control measures for the supply chain security. Cyber Threat Intelligence (CTI) provides an intelligence analysis to discover unknown to known threats using various properties including threat actor skill and motivation, Tactics, Techniques, and Procedure (TT and P), and Indicator of Compromise (IoC). This paper aims to analyse and predicate threats to improve cyber supply chain security. We have applied Cyber Threat Intelligence (CTI) with Machine Learning (ML) techniques to analyse and predict the threats based on the CTI properties. That allows to identify the inherent CSC vulnerabilities so that appropriate control actions can be undertaken for the overall cybersecurity improvement. To demonstrate the applicability of our approach, CTI data is gathered and a number of ML algorithms, i.e., Logistic Regression (LG), Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (DT), are used to develop predictive analytics using the Microsoft Malware Prediction dataset. The experiment considers attack and TTP as input parameters and vulnerabilities and Indicators of compromise (IoC) as output parameters. The results relating to the prediction reveal that Spyware/Ransomware and spear phishing are the most predictable threats in CSC. We have also recommended relevant controls to tackle these threats. We advocate using CTI data for the ML predicate model for the overall CSC cyber security improvement.

Recent advancements in the Internet of Things (IoT) and the Web of Things (WoT) accompany a smart life where real world objects, including sensing devices, are interconnected with each other. The Web representation of smart objects empowers innovative applications and services for various domains. To accelerate this approach, Web of Objects (WoO) focuses on the implementation aspects of bringing the assorted real world objects to the Web applications. In this paper; we propose an emergency fire management system in the WoO infrastructure. Consequently, we integrate the formation and management of Virtual Objects (ViO) which are derived from real world physical objects and are virtually connected with each other into the semantic ontology model. The charm of using the semantic ontology is that it allows information reusability, extensibility and interoperability, which enable ViOs to uphold orchestration, federation, collaboration and harmonization. Our system is context aware, as it receives contextual environmental information from distributed sensors and detects emergency situations. To handle a fire emergency, we present a decision support tool for the emergency fire management team. The previous fire incident log is the basis of the decision support system. A log repository collects all the emergency fire incident logs from ViOs and stores them in a repository.

The general goal of the Web-of-Objects (WoO) is to simplify object and application deployment, maintenance, and operation of IoT infrastructures. WoO also aim to provide user-centric IoT service by enabling object virtualization and semantic ontology based service composition. In WoO, semantic modeling of objects plays a distinguished role in achieving interoperability of device and service through semantic ontology model. In this paper, we propose a semantic functional module for user centric service composition in WoO platform. We design an ontology model for virtual object (ViO); it is the physical representation of real world objects. Consequently, we present a user-demand based service composition by showing an use case of WoO. In the proposed semantic based service composition approach, virtual object and composite virtual object are the key entity; this class of objects allows composing services from heterogeneous objects by following a service composition algorithm. This algorithm creates composite service along with the semantic description of that service. The proposed approach of service composition enhances the collaboration of objects as well as services. In the proposed system, user can search a service using natural language through the user interface; on the other hand, the service composition module creates the service by selecting the required objects dynamically.

The admiration of social networks (SNs) and the advent of the Internet of Things (IoT) direct to a new research paradigm called Social IoT (SIoT), where real-world physical objects can form their own SN like the human SN. This effort leads to an immense possibility of unique applications for a smart cognitive society. However, it is still a challenge to explore these applications due to a lack of an adequate SIoT framework, where SIoT nodes can be controlled, managed, and monitored in realtime under a cognitive framework. Hence, in this paper, we propose a framework to create, manage, control, and monitor the SIoT objects intelligently and cognitively in real-time. In our proposed framework, we enable virtual representation of realworld objects known as virtual objects (VOs) and ensure their relationship semantically to compose new services by combining VOs and called composite VOs. Additionally, we identify special skills (e.g., expertise, and/or willingness to help others, etc.) as abstract objects. We also enable real-time interaction by using stream processing techniques. We also evaluated the performance of VO selection to understand the resource consumption and latency during the process.

In this paper we aim to propose a Web-Of-Objects (WoO) based Energy Management System (WEMS) for providing a solution to efficiently manage energy consumption in smart home environment. The general goal of the WoO is to simplify object and application deployment, maintenance and operation in Internet of Things infrastructures. WoO also intends to propose service architecture system to support an intelligent features through an objectification and virtualization of the physical things. Object virtualization ensures harmonization, federation and combination of objects as well as services in the WEMS. Semantic ontology plays a vital role in WoO for ensuring the information reusability, extensibility and interoperability among virtual objects. It enables WEMS to be easily deployable in the real environment. This system can be applicable to building, home and factory, particularly we consider a home environment in this paper.