Security has always been the main concern for the internet of things (IoT)-based systems. Blockchain, with its decentralized and distributed design, prevents the risks of the existing centralized methodologies. Conventional security and privacy architectures are inapplicable in the spectrum of IoT due to its resource constraints. To overcome this problem, this paper presents a Blockchain-based security mechanism that enables secure authorized access to smart city resources. The presented mechanism comprises the ACE (Authentication and Authorization for Constrained Environments) framework-based authorization Blockchain and the OSCAR (Object Security Architecture for the Internet of Things) object security model. The Blockchain lays out a flexible and trustless authorization mechanism, while OSCAR makes use of a public ledger to structure multicast groups for authorized clients. Moreover, a meteor-based application is developed to provide a user-friendly interface for heterogeneous technologies belonging to the smart city. The users would be able to interact with and control their smart city resources such as traffic lights, smart electric meters, surveillance cameras, etc., through this application. To evaluate the performance and feasibility of the proposed mechanism, the authorization Blockchain is implemented on top of the Ethereum network. The authentication mechanism is developed in the node.js server and a smart city is simulated with the help of Raspberry Pi B+. Furthermore, mocha and chai frameworks are used to assess the performance of the system. Experimental results reveal that the authentication response time is less than 100 ms even if the average hand-shaking time increases with the number of clients.

Secure Patterns provides a solution for the security requirement of the software. There are a large number of secure patterns and it is quite difficult to choose an appropriate pattern. Moreover, selection of these patterns needs security knowledge, commonly developers are not specialized in the domain of security knowledge. This research can help in the selection of secure pattern on the basis of tradeoffs of the secure pattern using text categorization. A repository of secure design patterns is used as a dataset and a repository of requirements artifacts in the form of software requirements specification (SRS) are used for this research. A text categorization scheme which begins with preprocessing, indexing of secure patterns ends up by querying SRS features for retrieving secure design pattern using document retrieval model. For the evaluation of the proposed model, we have used three different domains SRS. These three SRS documents represent three different domains i.e. e-commerce, social media, and desktop utility program. A traditional precision and recall method along with F-measure used for evaluation of information/document retrieval model is used to evaluate the results. F-measure for 17 different design problems shows around 81% accuracy with recall up to 0.69%.

Energy efficiency in mobile computing is really an important issue these days. Owing to the popularity and prevalence of Android operating system among the people, a great number of Android smartphone applications have been developed and proliferated by the software developers. While developing these applications, developers have to keep energy consumption factor in mind, as the efficiency of an application is largely affected by it. Thus, designers and programmers endeavour to choose the best designing approaches to develop energy-efficient applications. It is imperative to assist the programmers in choosing appropriate techniques and strategies to manage power consumption. In the present research, we have investigated the effect of Android application design on its energy utilisation. For this purpose, we have practically implemented design patterns on two Android applications and evaluated their energy consumption before and after implementing these patterns. We have modelled the high-level design of these two Android applications by using software design patterns in such a way as to abate their energy requirement. We have also checked how the quality, maintainability, and efficiency of code are affected by these design patterns. The outcomes of the research can facilitate programmers to utilise these details while developing energy efficient solutions.

Human activity recognition (HAR) plays a pivotal role in applications such as healthcare monitoring, fitness tracking, and smart homes. Multi-modal sensor data from wearable devices offers diverse perspectives on human motion, enhancing recognition accuracy and robustness. However, integrating these modalities poses challenges due to sensor heterogeneity and variability in placement. This study examines the role of multi-modalities in HAR using a hybrid convolutional multi-modal attention network (HCMMA-Net), designed to exploit spatial and temporal dependencies in sensor data. We evaluate the model on two benchmark datasets Cogage, achieving an accuracy of 93.94%, and WISDM, with an accuracy of 99.29%, demonstrating its strong generalizability across varied sensor configurations. Additionally, we present a newly collected multi-modal dataset, HumcareV1.0, comprising different activities in smart-homelike scenarios. On this real-world dataset, HCMMA-Net attains an accuracy of 97.56%, highlighting its effectiveness in capturing subtle behavioral nuances in practical environments. The model exhibits robust generalization across complex activity patterns and sensor configurations, underscoring the significance of multi-modal integration in advancing HAR systems. These findings highlight the potential of our approach for deployment in real-time, context-aware smart environments.

The foundational features of multi-agent systems are communication and interaction with other agents. To achieve these features, agents have to transfer messages in the predefined format and semantics. The communication among these agents takes place with the help of ACL (Agent Communication Language). ACL is a predefined language for communication among agents that has been standardised by the FIPA (Foundation for Intelligent Physical Agent). FIPA-ACL defines different performatives for communication among the agents. These performatives are generic, and it becomes computationally expensive to use them for a specific domain like e-commerce. These performatives do not define the exact meaning of communication for any specific domain like e-commerce. In the present research, we introduced new performatives specifically for e-commerce domain. Our designed performatives are based on FIPA-ACL so that they can still support communication within diverse agent platforms. The proposed performatives are helpful in modelling e-commerce negotiation protocol applications using the paradigm of multi-agent systems for efficient communication. For exact semantic interpretation of the proposed performatives, we also performed formal modelling of these performatives using BNF. The primary objective of our research was to provide the negotiation facility to agents, working in an e-commerce domain, in a succinct way to reduce the number of negotiation messages, time consumption and network overhead on the platform. We used an e-commerce based bidding case study among agents to demonstrate the efficiency of our approach. The results showed that there was a lot of reduction in total time required for the bidding process.