# SASC: Secure and Authentication-Based Sensor Cloud Architecture for Intelligent Internet of Things
## 2 Related Work  
Recently, smart devices called sensor nodes provided an opportunity to design and maintain the network architecture for information gathering and forwarding. Sensor nodes are mostly dispersed randomly in a self-configured mode for various applications such as fire detection, smart cities, smart home, healthcare, and agriculture [33; 34; 35]. Since sensor nodes have limited constraints in terms of processing, storage, battery, and transmission capabilities, they might be compromised in unreliable and complex IoT systems. Moreover, the field of artificial intelligence (AI) grown by developments in machine learning (ML) more explicitly in constraint networks showing significance in an area of IoT systems [36; 37]. Thus, developing an energy-efficient and intelligent network infrastructure with effective data security is the main research challenge for IoT devices [38; 39; 40]. In cloud computing [41; 42; 43], end-users get infrastructure from service providers for storing and processing of data. Due to huge data collection and limited resources of sensor nodes, the cloud infrastructure is integrated into WSNs for strengthening network performance, i.e., computational processing and data storage. In the sensor-cloud architecture, sensor nodes capture required data from the monitoring area and store it on the cloud for processing and analyzing purposes, which is then sent towards the requested end-users or clients. The sensor-cloud infrastructure reduces the overheads on low power sensing nodes and improves network management [44; 45; 46; 47]. The storage of big data and their processing is one of the demanding applications for any cloud infrastructure. However, most of the proposed solutions overlook the security and authentication aspects of the network among cluster heads, BS, and cloud servers. This may disclose the data privacy to malicious nodes and may compromise the network performance [48; 49; 50]. Clustering solutions [51; 52; 53] provide improvements in energy efficiency, network scalability, and data delivery performances. However, most of these solutions do not consider secure data forwarding with node-level authentication in the presence of malicious nodes. In the cluster formation phase, the cluster head performs a significant role in data collection and transmission. Under unreliable environments, the cluster head verification with secure data transmission is a major research challenge that can compromise the capabilities of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) is the standard and first dynamic protocol [54], which aims to divide the sensor field into various clusters. However, the formulated clusters are non-uniformly distributed concerning load balancing and lack of secure data transmission. Furthermore, the role of cluster heads is shifted based on a fixed epoch that rapidly executes the process of the re-clustering phase. Authors in [55] proposed LEACH based security routing protocol for WSNs using Exclusion Basis Systems (EBS) and \(\upmu\)TESLA. The proposed solution generates and distributes keys based on EBS and guarantees the security of keys by using \(\upmu\)TESLA. However, the cluster formation phase is still based on a random manner and leads to uneven energy consumption among sensor nodes. In addition, the security key is frequently updated in each data transmission round. In [56], the authors proposed an energy-efficient and QoS-aware routing protocol for wireless sensor networks based on a smart grid to achieve reliable data transmission. Furthermore, the proposed solution consists of a BMO-based routing algorithm for uniformly sized energy consumption between the nodes. However, the proposed solution overlooked the data security in terms of data confidentiality, authenticity, and integrity under the presence of network threats. As a result, the transmitting information may be compromised. Authors in [57] proposed SecLEACH that aims to improve the performance of cluster-based solutions by incorporating some functionalities of the data level security.