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Due to rising cyber threats, IoT devices’ security vulnerabilities are expanding. However, these devices cannot run complicated security algorithms locally due to hardware restrictions. Data must be transferred to cloud nodes for processing, giving attackers an entry point. This research investigates distributed computing on the edge, using AI-enabled IoT devices and container orchestration tools to process data in real time at the network edge. The purpose is to identify and mitigate DDoS assaults while minimizing CPU usage to improve security. It compares typical IoT devices with and without AI-enabled chips, container orchestration, and assesses their performance in running machine learning models with different cluster settings. The proposed architecture aims to empower IoT devices to process data locally, minimizing the reliance on cloud transmission and bolstering security in IoT environments. The results correlate with the update in the architecture. With the addition of AI-enabled IoT device and container orchestration, there is a difference of 60% between the new architecture and traditional architecture where only Raspberry Pi were being used.

The amalgamation of heterogeneous generations of mobile cellular networks around the globe has resulted in diverse data speed experiences for end users. At present, there are no defined mechanisms in place for subscribers of a mobile network operator (MNO) to use the services of third-party WiFi providers. MNOs also have no standardized procedures to securely interact with each other, and allow their subscribers to use third-party services on a pay-as-you-go basis. This paper proposes a blockchain-enabled offloading framework that allows a subscriber of a mobile operator to temporarily use another MNO or WiFi provider’s higher-speed network. A smart contract is employed to allow diverse entities, such as MNOs, brokers and WiFi providers, to automatically execute mutual agreements, to enable the utilization of third-party infrastructure in a secure and controlled manner. The proposed framework is tested using Ethereum’s testnet on the Goerli network using Alchemy and Hardhat. The analysis of the results obtained shows that the proposed technique helps mobile operators to offer improved user experience in the form of average speed and latency. The experiments show that the average time taken to deliver a 500 MB file is reduced from 10.23 s to 0.91 s for the global average scenario, from 6.09 s to 0.50 s for 5G, from 13.50 s to 0.50 s for 4G-LTE, from 41.11 s to 0.49 s for 4G, and from 339.11 s to 0.49 s for the 3G scenario. The results also show that, with WiFi offloading, users from all cellular generations can enjoy a similar quality of services, because delivery time ranges from 0.49 s to 0.91 s for offloaded experiments whereas for the non-offloaded scenario it ranges from 6.09 s to 339.11 s.

All anonymous identity-based encryption (IBE) schemes that are group homomorphic (to the best of our knowledge) require knowledge of the identity to compute the homomorphic operation. This paper is motivated by this open problem, namely to construct an anonymous group-homomorphic IBE scheme that does not sacrifice anonymity to perform homomorphic operations. Note that even when strong assumptions, such as indistinguishability obfuscation (iO), are permitted, no schemes are known. We succeed in solving this open problem by assuming iO and the hardness of the DBDH problem over rings (specifically, ZN2 for RSA modulus N). We then use the existence of such a scheme to construct an IBE scheme with re-randomizable anonymous encryption keys, which we prove to be IND-ID-RCCA secure. Finally, we use our results to construct identity-based anonymous aggregation protocols.

The utilization of Internet of Things (IoT) devices in various smart city and industrial applications is growing rapidly. Within a trusted authority (TA), such as an industry or smart city, all IoT devices are closely monitored in a controlled infrastructure. However, in cases where an IoT device from one TA needs to communicate with another IoT device from a different TA, the trust establishment between these devices becomes extremely important. Obtaining a digital certificate from a certificate authority for each IoT device can be expensive. To solve this issue, a group authentication framework is proposed that can establish trust between group IoT devices owned by different entities. The Chebyshev polynomial has many important properties, semigroup is one of the most important. These properties make the Chebyshev polynomial a good candidate for the proposed group authentication mechanism. The secure exchange of information between trusted authorities is supported by Blockchain technology. The proposed framework was implemented and tested using Python and deployed on Blockchain using Ethereum’s Goerli’s testnet. The results show that the proposed framework can reasonably use Chebyshev polynomials with degrees up to four digits in length. The values of various parameters related to Blockchain are also discussed to understand the usability of the proposed framework.

The evolution of smart contracts in recent years inspired a crucial question: do smart contract evaluation protocols provide the required level of privacy when executing contracts on the blockchain? The Hawk (IEEE S&P ’16) paper introduces a way to solve the problem of privacy in smart contracts by evaluating the contracts off-chain, albeit with the trust assumption of a manager. To avoid the partially trusted manager altogether, a novel approach named zkHawk (IEEE BRAINS ’21) explains how we can evaluate the contracts privately off-chain using a multi-party computation (MPC) protocol instead of trusting said manager. This paper dives deeper into the detailed construction of a variant of the zkHawk protocol titled V-zkHawk using formal proofs to construct the said protocol and model its security in the universal composability (UC) framework (FOCS ’01). The V-zkHawk protocol discussed here does not support immediate closure, i.e., all the parties (n) have to send a message to inform the blockchain that the contract has been executed with corruption allowed for up to t parties, where t