Many Internet of Things applications, such as smart cities and intelligent transportation, require accessible data to users (i.e., data consumers). To address users' timely data access needs, Information-Centric Wireless Sensor Networks (ICWSNs) were proposed that allow users to access data directly from cache nodes. Particularly, ICWSNs are clustered, and Cluster Heads (CHs) are selected to collect data from basic sensing nodes and act as cache nodes. Nevertheless, clustering and ensuring data security in ICWSNs is challenging. This is because sensor nodes are often resource-constrained, heterogeneous (i.e., perform different sensing tasks), and/or mobile. Driven by users' security and timely data access needs, in this thesis, cluster-based ICWSNs' management for enhanced user security satisfaction is investigated. First, a security-aware CHs selection algorithm is proposed to optimize network coverage that is subject to security and energy constraints. Then, cluster-based ICWSNs with heterogeneous communities are modeled analytically and compared to conventional cluster-based ICWSNs with heterogeneous sensor nodes. To overcome the identified energy-latency and security trade-off, a Security Level Aware algorithm for Cluster-based ICWSNs with Heterogeneous communities (SLAC-H) is proposed. In SLAC-H, community leaders collect and forward application-domain-speciffic data to CHs. Next, Node Embedding with Security Resource Allocation (NESRA) clustering algorithm for mobile ICWSNs is proposed. To improve user security satisfaction, NESRA allocates security resources to sensor nodes based on their location, mobility, and energy resources. Still, when security is set as a priority, many times, more energy is spent on security than is actually required. Therefore, along with the mobility-aware NESRA, User-aware clustering with Security Resource Allocation (USRA) algorithm is proposed. In USRA, a sink node determines which security resource each sensor node will be using for the next round to avoid over-utilization of network resources while satisfying user security needs. A summary of the proposed algorithms and some highlights for future work conclude this thesis.