One way to reduce the computational load of the agents is the distribution of their services. To achieve this goal, the functionality of a MAS (multiagent system) should not reside in the agents themselves, but ubiquitously be distributed so that allows the system to perform tasks in parallel avoiding an additional computational cost. The distribution of services that offers SCODA (Distributed and Specialized Agent Communities) allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA.

Currently, web services‐based applications have an important presence in public and private organizations. The vulnerabilities that these types of applications may have pose an inherent potential risk to the business model of these organizations. These applications have the inherent risk of being used by organizations in such a way that their activity is affected and they become the main entry point for attackers who want to breach their security. The main barrier to this type of attack are web application firewalls (WAF), which are responsible for processing Hypertext Transfer Protocol requests between clients and web servers, classifying them and rejecting malicious requests. This type of (WAF) applications, for the most part, have regular expressions that correspond to general rules and allow detecting malicious requests that follow a pattern contained in them. However, due to the knowledge of these rules by attackers, it is easy to circumvent security and to impersonate a malicious request by an innocuous request. Therefore, in this article, we present a study of different models based on artificial intelligence techniques as Naïve Bayes, k‐nearest neighbors, support vector machines, and linear regression to test their effectiveness in detecting malicious requests from a synthetic dataset containing more than 100,000 requests. The results obtained show that the implementation of these methods optimize the detection of malicious requests obtaining results between 92% and 99% of success in their classification.

The specialization exists in biological systems and in human organizations, as a methodology to improve processes and optimize their aims. This specialization in artificial intelligent systems such as multi-agent systems, can improve their aims, depending on the type of specialization and the goals which they need to achieve. The enterprise networks are a collaboration model between companies which we can apply over these intelligent systems, so that, these systems can achieve more complex aims. Therefore, in this collaboration type, is necessary to consider their specialization type, and how they could collaborate to achieve aims, that by themselves would not be possible.