Cloud and IoT Systems Security

Subject: Tech & Engineering
Pages: 5
Words: 1225
Reading time:
5 min
Study level: College


Cloud-based services and IoT systems are the future of computing and technological innovation. These technologies are currently being developed and implemented on the mass organizational scale, creating various challenges which includes integration security. This report will investigate the fundamental basics of cloud-based and IoT technologies and solutions to various organizational challenges to their adoption.

Cloud-Based Technologies and Services

Cloud computing is the delivery of computing services over the Internet, otherwise known as “the cloud” in this context. It is a model which promotes universal, on-demand, and convenient network access to a shared pool of computing resources. These can be created, supplied, and managed with little effort and does not require service provider interaction (Stallings & Brown, 2018). Cloud computing can include networks, storage, servers, applications, and other services over the Internet.

Cloud-based technologies offer significant benefits such as faster innovation and upgrades, the flexibility of resources and usage, and economies of scale which lower operating or infrastructure costs. The global reach, performance, and cost-efficiency have led to businesses rapidly adopting this technology and its subbranches such as mobile cloud computing (Stergiou, Psannis, Kim, & Gupta, 2016).

The cloud computing model consists of five fundamental characteristics. Broad network access consists of capabilities and access possibilities available through standard mechanisms. Rapid elasticity provides the ability to modify resources based on service requirements. Measured service helps to control and optimize resource use through metering and tracking levels of usage for various services. On-demand self-service implies that a customer should be able to provision computing capabilities without human interaction.

Finally, resource pooling is the pooling of a provider’s computing resources to focus on multiple CSCs through a multi-tenant model that may have dynamic physical and virtual resources (Stallings & Brown, 2018). Cloud service models include software, platformer, and infrastructure as a service. These distinctly identify the primary purpose that a customer may require to use or access the cloud for and management or control of resources underlying the infrastructure.

IoT Technologies and Services

The Internet of Things (IoT) is a relatively new and innovative principle in technology which describes an advanced automation and analytics system through the interconnection of smart devices. It utilizes a wide range of data points from sources such as networking, sensors, AI technology, and big data to deliver systems for a product. The unique flexibility of IoT technologies makes them applicable to any industry where they contribute to transparency, enhanced performance, and greater control.

The potential for IoT is significant as it can have an extensive impact on daily life and behavior of users. The effects would become visible in various contexts such as a private domicile adopting the “smart home” technology. In society and technology, IoT could be used in robotics, e-health, assisted living, and learning processes. Meanwhile, businesses which adopt IoT can experience improvements in areas such as logistics, intelligent transportation, process management, automation and industrial production (Stergiou et al., 2016).

The interconnection of smart devices in IoT can range from appliances to tiny sensors. Currently, the technological process is to embed mobile transceivers into various devices and gadgets, thus allows for communication to be established among them as well as with human users. Progress and development of IoT are driven primarily be deeply embedded devices and sensors The IoT system is what allows to create a universal and interconnected space amongst billions of personal gadgets, household appliances, and industrial objects, all using cloud technology.

Sensor information is delivered from objects allowing them to learn, act depending on commands and environment, and eventually modify functions or behavior accordingly. Large IoT systems can eventually manage complex networks such as factories or cities (Stallings & Brown, 2018). However, the most challenging and underdeveloped aspect of IoT remains network security.


Despite numerous benefits of the cloud computing model, integrational and organizational implementation challenges remain. Such aspects as multi-tenancy and isolation, vendor lock-in, and data management are amongst of many. However highly concerning security issues leave cloud consumers vulnerable. Security management of the cloud is commonly outsourced to a third party, often the one that hosts all of an organization’s IT assets.

However, this results in the critical loss of control. Furthermore, there may a co-existence of different organizations’ clouds on the same server, but neither is aware of the strength of security protocols. There are commonly no security guarantees between cloud providers and consumers, which leads to a significant risk of storing sensitive information on public infrastructure. All types of cloud-based services are vulnerable to data security threats due to the nature of cloud computing systems that imply storage, management, and access methods which are easily accessed through various resources while only having a small layer of protection such as CML (Ali, Khan, & Vasilakos, 2015).

The main challenge to IoT implementation is security. Due to the newness of the IoT principles and technology, security is not currently paramount in product design. Encryption algorithms are also a problem as public key cryptosystems are used for authorization systems but there is a lack of global root certificate authority (Stergiou et al., 2016). Furthermore, public key cryptosystems suffer from increased computational overhead.

Object identification is a challenge since it is vital to ensure the integrity of records in naming architecture. The most commonly used Domain Name System (DNS) is vulnerable to attacks through a DNS cache poisoning. Finally, privacy is of utmost concern since IoT collects significant amounts of data, both personally and business-sensitive. The difficulties continue with data collection policy which guides the types and amount of information gathered as well as how it is stored. Meanwhile, data anonymization ensures there is cryptographic protection for data relations. Often guidelines and proper security for these aspects are overlooked (Zhang et al., 2014).


For cloud computing, securing the communication patterns and networks can be achieved through a combination of virtual LANs, IDS, IPS, and firewalls which would allow protecting data while in transit. These tools in combination with strict access management can achieve protect by ensuring visibility and monitoring of traffic. Furthermore, recently developed Advanced cloud protect systems (ACPS) can neutralize attacks by diving into multiple modules throughout the host platform and detecting suspicious activity.

Finally, complex identity and access management systems allow providing a monitored gateway for any cloud-computing stakeholders. A robust identity management system covers all data with corresponding identity context parameters. It may be viable to consider a tradeoff of performance for security optimization. Adaptative security controls based on expected threat level can help manage performance drops. Finally, a federation of security protocols amongst the clouds or integrated cloud resources is vital. The security requirements must be enforced on all included clouds (Ali et al., 2015).

In IoT, object identification can be managed by employing security extensions to the DNS framework such as DNSSEEC that would ensure the authenticity of resource records and serve as a tool for distribution cryptographic keys. The issue of vulnerable cryptosystems can be potentially resolved through delegated authorization as well as methods to eliminate backdoor through dynamic analysis technique.

This would ensure interface and the intermediate layer are dependent on different systems. Privacy can be potentially mitigated by creating a system that would assign various levels of cryptographic protection depending on a devices’ resource constraints and one that would attempt to remove the direct connect between data and its owner through encryption and scrambling (Zhang et al., 2014).


Ali, M., Khan, S. U., & Vasilakos, A. V. (2015). Security in cloud computing: Opportunities and challenges. Information Sciences, 305, 357-383. Web.

Stallings, W., & Brown, L. (2018). Computer security: Principles and practice (4th ed.). Upper Saddle River, NJ: Pearson Education.

Stergiou, C., Psannis, K. E., Kim, B.-G., & Gupta, B. (2016). Secure integration of IoT and cloud computing. Future Generation Computer Systems, 78(3), 964-975. Web.

Zhang, Z., Cho, M. C., Wang, C., Hsu, C., Chen., C., & Shieh, S. (2016). IoT security: Ongoing challenges and research opportunities. In 2014 IEEE 7th international conference on service-oriented computing and applications (pp. 230-234). Matsue, Japan: Institute of Electrical and Electronic Engineers.