Integrating Innate and Adaptive Immunity for Intrusion Detection

Network Intrusion Detection Systems (NIDS) monitor a net- work with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDS’s rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to an intrusion detection problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Introducting Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reactive and for generating tolerance. We have derived an algorithm based on the functionality of these cells, and have used the signals and differentiation pathways to build a control mechanism for an artificial immune system. We present our algorithmic details in addition to some preliminary results, where the algorithm was applied for the purpose of anomaly detection. We hope that this algorithm will eventually become the key component within a large, distributed immune system, based on sound imnological concepts.

An Immune Network Intrusion Detection System Utilising Correlation Context

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Experimenting with Innate Immunity

libtissue is a software system for implementing and testing AIS algorithms on real-world computer security problems. AIS algorithms are implemented as a collection of cells, antigen and signals interacting within a tissue compartment. Input data to the tissue comes in the form of realtime events generated by sensors monitoring a system under surveillance, and cells are actively able to affect the monitored system through response mechanisms. libtissue is being used by researchers on a project at the University of Nottingham to explore the application of a range of immune-inspired algorithms to problems in intrusion detection. This talk describes the architecture and design of libtissue, along with the implementation of a simple algorithm and its application to a computer security problem.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

'Towards a Conceptual Framework for Innate Immunity'

Innate immunity now occupies a central role in immunology. However, artificial immune system models have largely been inspired by adaptive not innate immunity. This paper reviews the biological principles and properties of innate immunity and, adopting a conceptual framework, asks how these can be incorporated into artificial models. The aim is to outline a meta-framework for models of innate immunity.

A Recommender System based on the Immune Network

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

'Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection'

Abstract. Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reactive and for generating tolerance. We have derived an algorithm based on the functionality of these cells, and have used the signals and differentiation pathways to build a control mechanism for an artificial immune system. We present our algorithmic details in addition to some preliminary results, where the algorithm was applied for the purpose of anomaly detection. We hope that this algorithm will eventually become the key component within a large, distributed immune system, based on sound immunological concepts.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

Modulation of immune cells and Th1/Th2 cytokines in insulin-treated type 2 diabetes mellitus.

Background: The role of the immune system in insulin resistance associated with type 2 diabetes has been suggested. Objectives: We assessed the profile of Th1/Th2 cytokines along with the frequencies of immune cells in insulin-treated type 2 diabetic patients (T2DP). Methods: 45 T2D patients and 43 age-matched healthy subjects were selected. Serum concentrations of T-helper type 1 (Th1) and Th2 cytokines and the frequencies of innate and adaptive immunity cells were assessed. Results: T2DP were hyperglycemic and showed high level of insulin, normal levels of triglycerides and total-cholesterol and without any change in HDL-cholesterol.Compared to healthy subjects, T2DP exhibited significant decreased frequencies of neutrophils, without any change in monocytes, eosinophils and natural killer cells. The percentages of total lymphocytes (CD3+) and CD8+-T-cells decreased whereas those of regulatory T-cells increased without any change in CD4+ T-cells in T2DP. Interestingly, the frequencies of effector CD4+-T and B-cells increased in T2DP. Serum concentrations of IL-2, IFN-γ and IL-4 decreased while IL-10 significantly enhanced in T2DP, suggesting a differentiation of CD4+T helper cells towards IL-10-producing- Teff-cells in these patients. Conclusion: Insulin-treated type 2 diabetes is associated with anti-inflammatory profile consistent with differentiation of CD4+-Th-cells towards IL-10-producing-Teff-cells, concomitant with increased frequencies of Treg and B-cells, and this may probably offer prevention against certain infections or autoimmune/inflammatory diseases.

An immune inspired Network Intrusion Detection System utilising correlation

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Oral vaccination with heat inactivated Mycobacterium bovis activates the complement system to protect against tuberculosis

Tuberculosis (TB) remains a pandemic affecting billions of people worldwide, thus stressing the need for new vaccines. Defining the correlates of vaccine protection is essential to achieve this goal. In this study, we used the wild boar model for mycobacterial infection and TB to characterize the protective mechanisms elicited by a new heat inactivated Mycobacterium bovis vaccine (IV). Oral vaccination with the IV resulted in significantly lower culture and lesion scores, particularly in the thorax, suggesting that the IV might provide a novel vaccine for TB control with special impact on the prevention of pulmonary disease, which is one of the limitations of current vaccines. Oral vaccination with the IV induced an adaptive antibody response and activation of the innate immune response including the complement component C3 and inflammasome. Mycobacterial DNA/RNA was not involved in inflammasome activation but increased C3 production by a still unknown mechanism. The results also suggested a protective mechanism mediated by the activation of IFN-γ producing CD8+ T cells by MHC I antigen presenting dendritic cells (DCs) in response to vaccination with the IV, without a clear role for Th1 CD4+ T cells. These results support a role for DCs in triggering the immune response to the IV through a mechanism similar to the phagocyte response to PAMPs with a central role for C3 in protection against mycobacterial infection. Higher C3 levels may allow increased opsonophagocytosis and effective bacterial clearance, while interfering with CR3-mediated opsonic and nonopsonic phagocytosis of mycobacteria, a process that could be enhanced by specific antibodies against mycobacterial proteins induced by vaccination with the IV. These results suggest that the IV acts through novel mechanisms to protect against TB in wild boar.

The Role Of The Inflammatory Microenvironment In Thyroid Carcinogenesis.

Immune responses against thyroid carcinomas have long been demonstrated and associations between inflammatory microenvironment and thyroid carcinomas repeatedly reported. This scenario has prompted scientists throughout the world to unveil how the inflammatory microenvironment is established in thyroid tumors and what is its influence on the outcome of patients with thyroid carcinoma. Many studies have reported the role of evasion from the immune system in tumor progression and reinforced the weakness of the innate immune response toward thyroid cancer spread in advanced stages. Translational studies have provided evidence that an increased density of tumor-associated macrophages in poorly differentiated thyroid carcinoma (DTC) is associated with an aggressive phenotype at diagnosis and decreased cancer-related survival, whereas well-DTC microenvironment enriched with macrophages is correlated with improved disease-free survival. It is possible that these different results are related to different microenvironments. Several studies have provided evidence that patients whose tumors are not infiltrated by lymphocytes present a high recurrence rate, suggesting that the presence of lymphocytes in the tumor microenvironment may favor the prognosis of patients with thyroid carcinoma. However, the effect of lymphocytes and other immune cells on patient outcome seems to result from complex interactions between the tumor and immune system, and the molecular pattern of cytokines and chemokines helps to explain the involvement of the immune system in thyroid tumor progression. The inflammatory microenvironment may help to characterize aggressive tumors and to identify patients who would benefit from a more invasive approach, probably sparing the vast majority of patients with an indolent disease from unnecessary procedures.

Immune cells and oxidative stress in the endotoxin tolerance mouse model

Sepsis is a systemic inflammatory response that can lead to tissue damage and death. In order to increase our understanding of sepsis, experimental models are needed that produce relevant immune and inflammatory responses during a septic event. We describe a lipopolysaccharide tolerance mouse model to characterize the cellular and molecular alterations of immune cells during sepsis. The model presents a typical lipopolysaccharide tolerance pattern in which tolerance is related to decreased production and secretion of cytokines after a subsequent exposure to a lethal dose of lipopolysaccharide. The initial lipopolysaccharide exposure also altered the expression patterns of cytokines and was followed by an 8- and a 1.5-fold increase in the T helper 1 and 2 cell subpopulations. Behavioral data indicate a decrease in spontaneous activity and an increase in body temperature following exposure to lipopolysaccharide. In contrast, tolerant animals maintained production of reactive oxygen species and nitric oxide when terminally challenged by cecal ligation and puncture (CLP). Survival study after CLP showed protection in tolerant compared to naive animals. Spleen mass increased in tolerant animals followed by increases of B lymphocytes and subpopulation Th1 cells. An increase in the number of stem cells was found in spleen and bone marrow. We also showed that administration of spleen or bone marrow cells from tolerant to naive animals transfers the acquired resistance status. In conclusion, lipopolysaccharide tolerance is a natural reprogramming of the immune system that increases the number of immune cells, particularly T helper 1 cells, and does not reduce oxidative stress.

The effects of nitric oxide on the immune response during giardiasis

Nitric oxide (NO) is a free radical synthesized from L-arginine by different isoforms NO-synthases. NO possesses multiple and complex biological functions. NO is an important mediator of homeostasis, and changes in its generation or actions can contribute or not to pathological states. The knowledge of effects of NO has been not only important to our understanding of immune response, but also to new tools for research and treatment of various diseases. Knowing the importance of NO as inflammatory mediator in diverse infectious diseases, we decided to develop a revision that shows the participation/effect of this mediator in immune response induced against Giardia spp. Several studies already demonstrated the participation of NO with microbicidal and microbiostatic activity in giardiasis. On the other hand, some works report that Giardia spp. inhibit NO production by consuming the intermediate metabolite arginine. In fact, studies in vitro showed that G. lamblia infection of human intestinal epithelial cells had reduced NO production. This occurs due to limited offer of the crucial substrate arginine (essential aminoacid for NO production), consequently reducing NO production. Therefore, the balance between giardial arginine consumption and epithelial NO production could contribute to the variability of the duration and severity of infections by this ubiquitous parasite.