Abbas Yazdinejad

TL;DR: This article proposes a secure and energy-efficient blockchain-enabled architecture of SDN controllers for IoT networks using a cluster structure with a new routing protocol, which indicates that the routing protocol has higher throughput, lower delay, and lower energy consumption than EESCFD, SMSN, AODV, AOMDV, and DSDV routing protocols.

TL;DR: It is shown that the proposed architecture's decentralized authentication among a distributed affiliated hospital network does not require re-authentication, which will have a considerable impact on increasing throughput, reducing overhead, improving response time, and decreasing energy consumption in the network.

TL;DR: This work introduces a secure authentication model with low latency for drones in smart cities that looks to leverage blockchain technology, and uses a customized decentralized consensus, known as drone-based delegated proof of stake (DDPOS), for drones among zones in a smart city that does not require reauthentication.

TL;DR: This paper proposes a novel deep Recurrent Neural Network ( RNN) learning model that utilizes the RNN to analyze Windows applications’ operation codes (Opcodes) as a case study and applies traditional machine learning classifiers to show the applicability of deep learners ( LSTM ) versus traditional models in dealing with cryptocurrency malware.

TL;DR: A new authentication approach that utilizes blockchain and software defined networking (SDN) techniques to remove the unnecessary re-authentication in repeated handover among heterogeneous cells using their public and private keys provided by the devised blockchain component while protecting their privacy is proposed.