92,773 research outputs found
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
The biological immune system (BIS) is characterized by networks of cells, tissues, and
organs communicating and working in synchronization. It also has the ability to learn,
recognize, and remember, thus providing the solid foundation for the development
of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself
as an area of computational intelligence. Real-Valued Negative Selection Algorithm
with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated
its potentials in the field of anomaly detection. The V-Detectors algorithm depends
greatly on the random detectors generated in monitoring the status of a system.
These randomly generated detectors suffer from not been able to adequately cover
the non-self space, which diminishes the detection performance of the V-Detectors
algorithm. This research therefore proposed CSDE-V-Detectors which entail the
use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in
optimizing the random detectors of the V-Detectors. The DE is integrated with CS
at the population initialization by distributing the population linearly. This linear
distribution gives the population a unique, stable, and progressive distribution process.
Thus, each individual detector is characteristically different from the other detectors.
CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness
of the detector set in the search space. In comparison with V-Detectors, cuckoo search,
differential evolution, support vector machine, artificial neural network, na¨ıve bayes,
and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms
other algorithms with an average detection rate of 95:30% on all the datasets. This
signifies that CSDE-V-Detectors can efficiently attain highest detection rates and
lowest false alarm rates for anomaly detection. Thus, the optimization of the randomly
detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly
detection tasks
Reconsidering online reputation systems
Social and socioeconomic interactions and transactions often require trust. In digital spaces, the main approach to facilitating trust has effectively been to try to reduce or even remove the need for it through the implementation of reputation systems. These generate metrics based on digital data such as ratings and reviews submitted by users, interaction histories, and so on, that are intended to label individuals as more or less reliable or trustworthy in a particular interaction context. We suggest that conventional approaches to the design of such systems are rooted in a capitalist, competitive paradigm, relying on methodological individualism, and that the reputation technologies themselves thus embody and enact this paradigm in whatever space they operate in. We question whether the politics, ethics and philosophy that contribute to this paradigm align with those of some of the contexts in which reputation systems are now being used, and suggest that alternative approaches to the establishment of trust and reputation in digital spaces need to be considered for alternative contexts
The State of e-Banking Implementation in Nigeria: A Post-Consolidation Review
The most widely used e-Banking instrument in �igeria is e-Payment, particularly the automatic teller machine
(ATM) card. However, with the adoption of e-Banking by all the banks in �igeria, the volume of cash in circulation
has continued to increase pre-and-post bank recapitalization/consolidation exercise. Furthermore, some of the 25 banks that survived the exercise were found lately to have depleted their capital base and have lost credibility before the consumers, e-Banking implementation notwithstanding.
Therefore, in this paper, we review the state of e-Banking implementation in �igeria and evaluate the influence of
trust on the adoption of e-Payment using an extended technology acceptance model (TAM). Similarly, we
investigate organizational reputation, perceived risk and perceived trust in the management of banks as a factor for
enhancing customer loyalty.
The findings in this work reveal that perceived ease of use and perceived usefulness are not only antecedent to ebanking
acceptance, they are also factors to retain customers to the use of e-banking system such as organizational
reputation, perceived risk and trust
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