Biblio

In today's power market, it's vital to keep electrical energy affordable to the vast majority of people while maintaining the highest degree of dependability. Due to which, the transmission network must operate beyond transfer limitations, generating congestion on transmission lines. These transmission line difficulties can be alleviated with the use of reactive power adjustment based on FACTS devices. Using a fuzzy tuned Static Synchronous Series Compensator [SSSC], this research proposes a novel method for calculating the effective damping oscillation control signals. The performance of the SSSC is compared to that of fuzzy logic-based controllers using PI controllers. According to the simulation results, the SSSC with fuzzy logic control effectively improves power flow under disrupted conditions

This paper uses Endsley's situational awareness model as a starting point for creating a new cyber-security awareness model for risk maturity. This is used to model the relationship between risk management-based situational awareness and levels of maturity in making decisions to deal with potential cyber-attacks. The risk maturity related to cyber situational awareness using the fuzzy failure mode effect analysis (FMEA) method is needed as a basis for effective risk-based decision making and to measure the level of maturity in decision making using the Software Engineering Institute Capability Maturity Model Integration (SEI CMMI) approach. The novelty of this research is that it builds a model of the relationship between the level of maturity and the level of risk in cyber-situational awareness. Based on the data during the COVID-19 pandemic, there was a decrease in the number of incidents, including the following decreases: from 15-29 cases of malware attacks to 8-12 incidents, from 20-35 phishing cases to 12-15 cases and from 5-10 ransomware cases to 5-6 cases.

Cipher Text Policy Attribute Based Encryption which is a form of Public Key Encryption has become a renowned approach as a Data access control scheme for data security and confidentiality. It not only provides the flexibility and scalability in the access control mechanisms but also enhances security by fuzzy fined-grained access control. However, schemes are there which for more security increases the key size which ultimately leads to high encryption and decryption time. Also, there is no provision for handling the middle man attacks during data transfer. In this paper, a light-weight and more scalable encryption mechanism is provided which not only uses fewer resources for encoding and decoding but also improves the security along with faster encryption and decryption time. Moreover, this scheme provides an efficient key sharing mechanism for providing secure transfer to avoid any man-in-the-middle attacks. Also, due to fuzzy policies inclusion, chances are there to get approximation of user attributes available which makes the process fast and reliable and improves the performance of legitimate users.

In internet based communication, various types of attacks have been evolved. Hence, attacker easily breaches the securities. Traditional intrusion detection techniques to observe these attacks have failed and thus hefty systems are required to remove these attacks before they expose entire network. With the ability of artificial intelligence systems to adapt high computational speed, boost fault tolerance, and error resilience against noisy information, a hybrid particle swarm optimization(PSO) fuzzy rule based inference engine has been designed in this paper. The fuzzy logic based on degree of truth while the PSO algorithm based on population stochastic technique helps in learning from the scenario, thus their combination will increase the toughness of intrusion detection system. The proposed network intrusion detection system will be able to classify normal as well as anomalism behaviour in the network. DARPA-KDD99 dataset examined on this system to address the behaviour of each connection on network and compared with existing system. This approach improves the result on the basis of precision, recall and F1-score.

In the open network environment, the strange entities can establish the mutual trust through Automated Trust Negotiation (ATN) that is based on exchanging digital credentials. In traditional ATN, the attribute certificate required to either satisfied or not, and in the strategy, the importance of the certificate is same, it may cause some unnecessary negotiation failure. And in the actual situation, the properties is not just 0 or 1, it is likely to between 0 and 1, so the satisfaction degree is different, and the negotiation strategy need to be quantified. This paper analyzes the fuzzy negotiation process, in order to improve the trust establishment in high efficiency and accuracy further.

In this paper, an optimization model of automobile supply chain network with risks under fuzzy price is put forward. The supply chain network is composed of component suppliers, plants, and distribution centers. The total costs of automobile supply chain consist of variable costs, fixed costs, and transportation costs. The objective of this study is to minimize the risks of total profits. In order to deal with this model, this paper puts forward an approximation method to transform a continuous fuzzy problem into discrete fuzzy problem. The model is solved using Cplex 12.6. The results show that Cplex 12.6 can perfectly solve this model, the expected value and lower semi-variance of total profits converge with the increasing number of discretization points, the structure of automobile supply chain network keeps unchanged with the increasing number of discretization points.

Cloud Computing has emerged as a paradigm to deliver on demand resources to facilitate the customers with access to their infrastructure and applications as per their requirements on a subscription basis. An exponential increase in the number of cloud services in the past few years provides more options for customers to choose from. To assist customers in selecting a most trustworthy cloud provider, a unified trust evaluation framework is needed. Trust helps in the estimation of competency of a resource provider in completing a task thus enabling users to select the best resources in the heterogeneous cloud infrastructure. Trust estimates obtained using the AHP process exhibit a deviation for parameters that are not in direct proportion to the contributing attributes. Such deviation can be removed using the Fuzzy AHP model. In this paper, a Fuzzy AHP based hierarchical trust model has been proposed to rate the service providers and their various plans for infrastructure as a service.