With the increasing use of smart technologies like the Internet of Things, home automation has become the hottest trend these days. It provides all the modern features and convenience that a homeowner can expect. Home appliances can be automated via wireless connectivity and they can be accessible on the go. However, there are so many security concerns with the significant rise of smart home appliances like light bulbs, power switches, door locks, home security, etc., especially because of limited processing power and storage. They are highly vulnerable to security threats. Hence, security has become the primary concern and matter of discussion among researchers in this area. This way, a decentralized database blockchain is gaining a lot of popularity to assure security in this field. This article is aimed to explore the security of smart homes and investigate the adoption of blockchain. This research paper is aimed to explore security measures that manufacturers should consider for IoT systems and the way Blockchain can help solve this problem.

With the increasing demand to efficiently deploy DNNs on mobile edge devices, it becomes much more important to reduce unnecessary computation and increase the execution speed. Prior methods towards this goal, including model compression and network architecture search (NAS), are largely performed independently and do not fully consider compiler-level optimization which is a must-do for mobile acceleration. In this work, we propose NPAS, a compiler-aware unified network pruning and architecture search and the corresponding comprehensive compiler optimizations supporting different DNNs and different pruning schemes, which bridge the gap of weight pruning and NAS. Our framework achieves 6.7 ms, 5.9 ms, and 3.9 ms ImageNet inference times with 78%, 75% (MobileNet-V3 level), and 71% (MobileNet-V2 level) Top-1 accuracy respectively on an off-the-shelf mobile phone, consistently outperforming prior work.

In recent days most of the industrial firms have been searching for ways to keep their data as secured and protected as possible. They have indulged in research works to find a mechanism that can be simple, convenient and guarantees high level security to large amount of data that is being manipulated every now and then. Among such mechanisms, one mechanism that satisfies all these requirements is Homomorphic Encryption (HE). Homomorphic Encryption schemes facilitate computation on the encrypted data, yielding different output every time is considered as an edge over traditional encryption algorithms. HE schemes ensures integrity and security of data, against threats and violations. Researchers expanded the dimensionality of the homomorphic encryption to another level through Carmichael’s Theorem-Based Homomorphic Encryption (CTHE) scheme and Modified Enhanced Homomorphic Encryption (MEHE) scheme. CTHE and MEHE schemes are reviewed in this article to show its robustness against invasive attacks.