This paper addresses an NP-hard problem, referred to as Network Topology Design with minimum Cost subject to a Reliability constraint (NTD-CR), to design a minimal-cost communication network topology that satisfies a pre-defined reliability constraint. The paper describes a dynamic programming (DP) scheme to solve the NTD-CR problem, and proposes a DP approach, called Dynamic Programming Algorithm to solve NTD-CR (DPCR-ST), to generate the topology using a selected sequence of spanning trees of the network, STX _min . The paper shows that our DPCR-ST approach always provides a feasible solution, and produces an optimal topology given an optimal order of spanning trees. The paper proves that the problem of optimally ordering the spanning trees is NP-complete, and proposes three greedy heuristics to generate and order only k spanning trees of the network. Each heuristic allows the DPCR-ST approach to generate STX _min using only k spanning trees, which improves the time complexity while producing a near optimal topology. Simulations based on fully connected networks that contain up to 2.3×10 ⁹ spanning trees show the merits of using the ordering methods and the effectiveness of our algorithm vis-à-vis to four existing state-of-the-art techniques. Our DPCR-ST approach is able to generate 81.5% optimal results, while using only 0.77% of the spanning trees contained in networks. Further, for a typical 2 × 100 grid network that contains up to 1.899 ¹⁰² spanning trees, DPCR-ST approach requires only k=1214 spanning trees to generate a topology with a reliability no larger than 5.05% off from optimal.

The domain name system (DNS) plays a vital role in network services for name resolution. By default, this service is seldom blocked by security solutions. Thus, it has been exploited for security breaches using the DNS covert channel (tunnel). One of the greatest current data leakage techniques is DNS tunneling, which uses DNS packets to exfiltrate sensitive and confidential data. Data protection against stealthy exfiltration attacks is critical for human beings and organizations. As a result, many security techniques have been proposed to address exfiltration attacks starting with building security policies and ending with designing security solutions, such as firewalls, intrusion detection or prevention, and others. In this paper, a hybrid DNS tunneling detection system has been proposed based on the packet length and selected features for the network traffic. The proposed system takes advantage of the outcome results conducted using the testbed and Tabu-PIO feature selection algorithm. The evolution of the proposed system has already been completed using three distinct datasets. The experimental outcome results show that the proposed hybrid approach achieved 98.3% accuracy and a 97.6% F-score in the DNS tunneling datasets, which outperforms the other related works’ techniques using the same datasets. Moreover, when the packet length was added into the hybrid approach, the run-time shows better results than when Tabu-PIO was used when the size of the data increases.

Over the last few years, the arena of mobile application development has expanded considerably beyond the demand of the world's software markets. With the growing number of mobile software companies and the increasing sophistication of smartphone technology, developers have been establishing several categories of applications on dissimilar platforms. However, developers confront several challenges when undertaking mobile application projects. In particular, there is a lack of consolidated systems that can competently, promptly and efficiently provide developers with personalised services. Hence, it is essential to develop tailored systems that can recommend appropriate tools, IDEs, platforms, software components and other correlated artifacts to mobile application developers. This paper proposes a new recommender system framework comprising a robust set of techniques that are designed to provide mobile app developers with a specific platform where they can browse and search for personalised artifacts. In particular, the new recommender system framework comprises the following functions: (i) domain knowledge inference module: including various semantic web technologies and lightweight ontologies; (ii) profiling and preferencing: a new proposed time- aware multidimensional user modelling; (iii) query expansion: to improve and enhance the retrieved results by semantically augmenting users’ query; and (iv) recommendation and information filtration: to make use of the aforementioned components to provide personalised services to the designated users and to answer a user’s query with the minimum mismatches.

This paper addresses an NP-hard problem to design a network topology with maximum all-terminal reliability subject to a cost constraint, given the locations of the various computer centers (nodes), their connecting links, each link's reliability and cost, and the maximum budget cost to install the links. Because cost is always a major focus in network design, this problem is practical for critical applications requiring maximized reliability. This paper first formulates a Dynamic Programming (DP) scheme to solve the problem. A DP approach, called DPA-1, generates the topology using all spanning trees of the network (ST _G ). The paper shows that DPA-1 is optimal if the spanning trees are optimally ordered. Further, the paper describes an alternative DP algorithm, called DPA-2, that uses only k spanning trees ( k ≤ n, where n=|ST _G |) sorted in increasing weight and lexicographic order to improve the time efficiency of DPA-1 while producing similar results. Extensive simulations using hundreds of benchmark networks that contain up to 1.899 ¹⁰² spanning trees show the merits of using the sorting method, and the effectiveness of our algorithms. DPA-2 is able to generate 85% optimal results, while using only a small number of k spanning trees, and up to 16.83 CPU seconds. Furthermore, the non-optimal results are only up to 3.4% off from optimal for the simulated examples.

Due to the unique features and characteristics of blockchain technology, its applications have expanded across various sectors, including finance, banking, supply chains, and smart grids (SGs). Blockchain ensures security and trust in transactions without requiring a third party, making it particularly valuable in decentralized systems. This paper explores the integration of blockchain technology into SG systems. It begins with a comprehensive review of conventional and smart power grids, identifying the key challenges modern SGs face, particularly issues related to trust and fraud. An in-depth analysis of blockchain technology follows, highlighting its potential, advantages, and defining characteristics. The study then examines several blockchain-based SG applications and provides a comparative analysis of prior research. The findings of this review illuminate the critical role of blockchain in enhancing SG performance by addressing trust and fraud prevention challenges. Furthermore, this research has significant implications for the energy sector, as it underscores the potential of blockchain to revolutionize SGs through increased security, transparency, and efficiency. By providing a foundation for future studies, this paper aims to guide the development of unified blockchain frameworks that address scalability, privacy, and energy management, paving the way for a more secure and efficient decentralized energy system

Traditional systems in real life lack transparency and ease of use due to their reliance on centralization and large infrastructure. Furthermore, many sectors that rely on information technology face major challenges related to data integrity, trust, and counterfeiting, limiting scalability and acceptance in the community. With the decentralization and digitization of energy transactions in smart grids, security, integrity, and fraud prevention concerns have increased. The main problem addressed in this study is the lack of a secure, tamper-resistant, and decentralized mechanism to facilitate direct consumer-to-prosumer energy transactions. Thus, this is a major challenge in the smart grid. In the blockchain, current consensus algorithms may limit the scalability of smart grids, especially when depending on popular algorithms such as Proof of Work, due to their high energy consumption, which is incompatible with the characteristics of the smart grid. Meanwhile, Proof of Stake algorithms rely on energy or cryptocurrency stake ownership, which may make the smart grid environment in blockchain technology vulnerable to control by the many owning nodes, which is incompatible with the purpose and objective of this study. This study addresses these issues by proposing and implementing a hybrid framework that combines the features of private and public blockchains across three integrated layers: user interface, application, and blockchain. A key contribution of the system is the design of a novel consensus algorithm, Proof of Energy, which selects validators based on node roles and randomized assignment, rather than computational power or stake ownership. This makes it more suitable for smart grid environments. The entire framework was developed without relying on existing decentralized platforms such as Ethereum. The system was evaluated through comprehensive experiments on performance and security. Performance results show a throughput of up to 60.86 transactions per second and an average latency of 3.40 s under a load of 10,000 transactions. Security validation confirmed resistance against digital signature forgery, invalid smart contracts, race conditions, and double-spending attacks. Despite the promising performance, several limitations remain. The current system was developed and tested on a single machine as a simulation-based study using transaction logs without integration of real smart meters or actual energy tokenization in real-time scenarios. In future work, we will focus on integrating real-time smart meters and implementing full energy tokenization to achieve a complete and autonomous smart grid platform. Overall, the proposed system significantly enhances data integrity, trust, and resistance to counterfeiting in smart grids.