Computer networks are increasingly complex environments and equipped with new services, users and infrastructure. The information safety and privacy become fundamental to the evolution of these environments. The anonymity, the weakness and other factors often encourage people to create malicious tools and techniques of attacks to information and computer systems. It can generate small inconveniences or even moral and financial damage. Thus, the detection of intrusion combined with other security tools can protect and prevent malicious attacks and anomalies in computer systems. Yet, considering the complexity and robustness of these systems, the security services are not always able to examine and audit the entire information flow, creating points of security failures that can be discovered and explored. Therefore, this PhD thesis proposes, designs, implements and analyzes the performance of an Integrated Security Services Layer (ISSL). So several security services were implemented and integrated to the ISSL such as Firewall, IDS, Antivirus, authentication tools, proprietary tools and cryptography services. Furthermore, the main feature of our ISSL is the creation of a common structure for storing information about incidents in a computer system. This information is considered to be the source of knowledge so that the system of anomaly detection, inserted in the ISSL, can act effectively in the prevention and protection of computer systems by detecting and classifying early anomalous situations. In this sense, behavioral models were created based on the concepts of the Hidden Markov Model (MHMM) and models for analysis of anomalous sequences. The ISSL was implemented in three versions: (i) System-on-Chip (SoC), (ii) JCISS software in Java and (iii) one simulator. Results such as the time performance, occupancy rates, the impact on the detection of anomalies and details of implementation are presented, compared and analyzed in this thesis. The ISSL obtained significant results regarding the detection rates of anomalies using the model MHMM, which are: for known attacks, rates of over 96% were obtained; for partial attacks by a time, rates above 80%, for partial attacks by a sequence, rates were over 96% and for unknown attacks, rates were over 54%. The main contributions of ISSL are the creation of a structure for the security services integration and the relationship and analysis of anomalous occurrences to reduce false positives, early detection and classification of abnormalities and prevention of computer systems. Furthermore, solutions were figured out in order to improve the detection as the sequential model, and features such as subMHMM for learning at real time. Finally, the SoC and Java implementations allowed the evaluation and use of the ISSL in real environments.