The inherent complexities of Industrial Internet of Things (IIoT) architecture make its security and privacy issues becoming critically challenging. Numerous surveys have been published to review IoT security issues and challenges. The studies gave a general overview of IIoT security threats or a detailed analysis that explicitly focuses on specific technologies. However, recent studies fail to analyze the gap between security requirements of these technologies and their deployed countermeasure in the industry recently. Whether recent industry countermeasure is still adequate to address the security challenges of IIoT environment are questionable. This article presents a comprehensive survey of IIoT security and provides insight into today’s industry countermeasure, current research proposals and ongoing challenges. We classify IIoT technologies into the four-layer security architecture, examine the deployed countermeasure based on CIA+ security requirements, report the deficiencies of today’s countermeasure, and highlight the remaining open issues and challenges. As no single solution can fix the entire IIoT ecosystem, IIoT security architecture with a higher abstraction level using the bottom-up approach is needed. Moving towards a data-centric approach that assures data protection whenever and wherever it goes could potentially solve the challenges of industry deployment.

Due to its wide accessibility, cloud services are susceptible to attacks. Data manipulation is a serious threat to data integrity which can occur in cloud computing - a relatively new offering under the umbrella of cloud services. Data can be tampered with, and malicious actors could use this to their advantage. Cloud computing clients in various application domains want to be assured that their data is accurate and trustworthy. On another spectrum, blockchain is a tamper-proof digital ledger that can be used alongside cloud technology to provide a tamper-proof cloud computing environment. This paper proposes a scheme that combines cloud computing with blockchain that assures data integrity for all homomorphic encryption schemes. To overcome the cloud service provider's (CSP) ultimate authority over the data, the proposed scheme relies on the Byzantine Fault Tolerance consensus to build a distributed network of processing CSPs based on the client requirements. After certain computations performed by all CSPs, they produce a master hash value for their database. To ensure immutable data is produced, master hash values are preserved in Bitcoin or Ethereum blockchain networks. The master hash values can be obtained by tracking the block header address for verification purposes. A theoretical analysis of the overhead costs associated with creating master hash values for each of the cryptocurrencies is presented. We found that Ethereum leads to lower client financial costs and better online performance than Bitcoin. We also specify the data security requirements the proposed scheme provides, the ground-level implementation, and future work. The proposed verification scheme is based on public cryptocurrency as a back-end service and does not require additional setup actions by the client other than a wallet for the chosen cryptocurrency.

Despite having many similar characteristics with cryptography, existing chaotic systems have many security issues that negatively affect the chaos-based cryptographic algorithms that utilize them. This paper proposes a new chaotification method that enhances the chaotic complexity of existing chaotic maps to surmount these issues. The proposed method uses a cosine function alongside a chaotic map in a cascade system. To depict its advantages, we apply it to enhance logistic and Henon maps before analyzing their chaotic properties. Results and comparisons indicate that the new chaotic maps have a wider chaotic range, elevated sensitivity, complex characteristics, high nonlinearity, and an extended cycle length as compared to the original (seed) maps as well as other chaotic maps. We then utilize the modified maps (and their corresponding seed maps) to design simple pseudorandom number generators to study their feasibility when used in cryptographic algorithms. We perform comparisons between the generators derived from both the original and seed maps. Results show that generators based on the new maps outperform their seed counterparts in nearly every aspect. This finding demonstrates the capability of the proposed method in improving the performance of chaos-based cryptographic algorithms.