IoT smart energy management is to maximize energy efficiency through energy information collection, energy DR management and energy sharing/trading by developing IoT-based smart energy platform technology. IoT smart energy management services provide energy efficiency enhancement, energy sharing and trading services through interconnection and integration of energy supply-transfer-utilization energy systems using the Internet of things. For this, this paper shows IoT energy management platform with energy big data system.

The performance of a polling system is modeled by stochastic Petri nets and its analysis is done by numerically solving the underlying Markov chain. One key problem in using stochastic Petri nets for real applications is that the size of underlying Markov chain tends to be large, and thus to be computationally intractable. In order to carry out the performance analysis of a large complex system in practice, the authors develop approximation methods at the Petri net level for the finite population, asymmetric polling systems and analyze the error due to the approximation. The mean cycle time and the mean response time of the system are approximated by the folding method and by the fixed-point iteration method. The effect of an increasing number of customers on the polling systems is studied using these approximations. The approximation methods are shown to save more than 95% of computation cost without a concomitant loss in accuracy. The methods perform very well at low offered loads.<>

We propose a novel dynamic host mutation (DHM) architecture based on moving target defense (MTD) that can actively cope with cyberattacks. The goal of the DHM is to break the cyber kill chain, expand the attack surface to increase the attacker’s target analysis cost, and disrupt the attacker’s fingerprinting to disable the server trace. We define the participating entities that share the MTD policy within the enterprise network or the critical infrastructure, and define functional modules of each entity for DHM enforcement. The threat model of this study is an insider threat of a type not considered in previous studies. We define an attack model considering an insider threat and propose a decoy injection mechanism to confuse the attacker. In addition, we analyze the security of the proposed structure and mechanism based on the security requirements and propose a trade-off considering security and availability.