The majority of collaborative learning and knowledge sharing (CLKS) platforms are built with numerous communication mediums, team and task management in mind. However, with the CLKS, the Question-Answering (QAs), User profile evaluation based on the quality of answers provided, and feeding of subject or project relevant data are all available. QAs are required for online or offline cooperation between team members or users. To that purpose, this paper presents a web application called CodeUP with features like QA system, Question similarity testing, and user profile rating for boosting communication and cooperation efficiency in CLKS for academic groups and small development teams. CodeUP is intended to be quickly established and step for academic or development groups to collaborate. As the CodeUP application supports the CLKS, it is also an ideal tool for academia and development teams to perform computer supported QA system and knowledge sharing in the sphere of work or study.

In this paper, we present the design and development of a collaborative knowledge-sharing platform with Blockchain based smart contracts (CodeBlockS) to help increase the trust and efficiency of how developers find the solution to their problems or try to learn new things. The popularity of Question-and-Answer websites such as StackOverflow, Ask, and Yahoo, as well as online course websites like as Udemy, is gradually expanding. Given this increased popularity, the quality and efficiency of user interaction must be improved such that users can try to connect with each other, ask questions about technical problems they are experiencing, or if they want to learn a topic in exchange for a fee and potentially collaborate on a project, or simply share their thoughts on a topic and improve their knowledge and network at the same time. Because these contracts will contain money, CodeBlockS has employed Ethereum Blockchain-based smart contracts to manage the data and money, as blockchain-based smart contracts are immutable and handle payments very securely. In general, social networking websites there are very few people sharing valuable knowledge and many people sharing worthless, time-consuming content that creates distraction. With the CodeBlockS system, developers find the solution to their problems or try to learn new things, and users can share their thoughts and learning on the platform. The platform also provides inbuilt smart contracts functionality using which two users can create a contract where one user will teach or solve doubt of the other user and receive fees towards service rendered.

The presence of malicious nodes in the ad hoc and sensor networks poses serious security attacks during routing which affects the network performance. To address such attacks, numerous researchers have proposed defense techniques using a human behavior pattern called trust. Among existing solutions, direct observations based trust models have gained significant attention in the research community. In this paper, the authors propose a Self Adaptive Trust Model (SATM) of secure geographic routing in wireless sensor networks (WSNs). Unlike conventional weight based trust models, SATM intelligently assigns the weights associated with the network activities. These weights are applied to compute the final trust value. SATM considers direct observations to restrict the reputation based attacks. Due to the flexible and intelligent weight computation, SATM dynamically detects the malicious nodes and direct the traffic towards trustworthy nodes. SATM has been incorporated into Greedy Perimeter Stateless Routing (GPSR) protocol. Simulation results using the network simulator NS-2 have shown that GPSR with SATM is robust against detecting malicious nodes.

In this paper, an improvement over Trusted Greedy Perimeter Stateless Routing (T-GPSR) is presented. T-GPSR employs heuristic weight values to evaluate total trust value of neighboring nodes. However, heuristic assignment of weights provide flexibility but it is not suitable in presence of several security attacks such as Grey hole, selfish behavior, on-off attack etc., are launched in the network in different proportions. To overcome this limitation, an improvement is suggested with an emphasis on trust update, lightweight trust computation and storage to reduce communication and storage overhead. The simulation study indicates that the packet delivery ratio of the improved T-GPSR has improved by 10% over T-GPSR in the presence of 50% of malicious nodes in the network.