Performance Modeling and Analysis of Network Firewalls

The Internet of Things (IoT) represents a new reality, as smart devices spread quickly and a higher number of applications arises. This attracts the attention of not only legitimate users but also attackers aiming to jeopardize the entire IoT infrastructure. Intrusion detection mechanisms are paramount in this networking environment as its first line of defense. Hence, this work proposes a Network Intrusion Detection System (NIDS) that deals with the Distributed Denial of Service (DDoS) attack, one of the most critical attacks that occur through IoT. The proposed NIDS uses stream learning to detect DDoS attacks in the IoT network and is designed to be deployed in a fog infrastructure. The detection model, built on Hoeffding Anytime Tree (HATT) algorithm, achieved a 99% accuracy and a 99% recall.

In this paper we identify a potential Denial of Service (DoS) attack that targets the last‐matching rules of the security policy of a firewall. The last‐matching rules are those rules that are located at the bottom of the ruleset of a firewall's security policy, and would require the most processing time by the firewall. If these rules are discovered, an attacker can potentially launch an effective low‐rate DoS attack to trigger worst‐case or near worst‐case processing, thereby overwhelming the firewall and bringing it to its knees. In this paper, we present a probing technique to remotely discover the last‐matching rules of a firewall. We study experimentally the effectiveness of this probing technique taking into account important factors such as the firewall's motherboard architecture and load conditions at network links and hosts. In addition we examine the impact of launching a low‐rate DoS attack on a firewall's performance. The performance is studied in terms of the firewall's CPU utilization and throughput, packet loss, and latency. Copyright © 2009 John Wiley & Sons, Ltd.

Wireless sensor networks (WSNs) have been widely applied in many areas for real‐time event detection. They are designed using both mobile and static sensor nodes (SNs) for different applications such as smart parking, environmental monitoring, health care systems, automotive industries, sports, open space surveillance, and so on. WSNs communicate through wireless mediums and are accessible to anyone, which make SNs susceptible to different types of attacks. Distributed denial of service (DDoS) is one such attack. It wastes the limited energy of SNs and causes loss of data packets within a network. A DDoS attack launches a coordinated attack by flooding the target nodes with bogus requests, thus exhausting their resources, and forcing them to deny service to legitimate member nodes. In this study, the authors propose a message analyser scheme for WSNs. The method is capable of detecting compromised SNs vulnerable to a DDoS attack. In addition, it is able to detect all compromised messages transmitted by the attackers to the base station through the sender nodes. The proposed method is compared with other related protocols. The results show that their method can effectively detect and defend against DDoS attacks in WSNs.

Software-Defined Networking (SDN) is now a well-established approach in 5G, Internet of Things (IoT) and Cloud Computing. The primary idea behind its immense popularity is the separation of its underlying intelligence from the data-carrying components like routers and switches. The intelligence of the SDN-based networks lies in the central point, popularly known as the SDN controller. It is the central control hub of the SDN-based network, which has full privileges and a global view over the entire network. Providing security to SDN controllers is one such important task. Whenever one wishes to implement SDN into their data center or network, they are required to provide the website to SDN controllers. Several attacks are becoming a hurdle in the exponential growth of SDN, and among all one such attack is a Distributed Denial of Service (DDoS) attack. In a couple of years, several new SDN controllers will be available. Among many, Open Networking Operating System (ONOS) and OpenDayLight (ODL) are two popular SDN controllers laying the foundation for many other controllers. These SDN controllers are now being used by numerous businesses, including Cisco, Juniper, IBM, Google, etc. In this paper, vulnerability analysis is carried out against DDoS attacks on the latest released versions of both ODL and ONOS SDN controllers in real-time cloud data centers. For this, we have considered distributed SDN controllers (located at different locations) on two different clouds (AWS and Azure). These controllers are connected through the Internet and work on different networks. DDoS attacks are bombarded on the distributed SDN controllers, and vulnerability is analyzed. It was observed with experimentation that, under five different scenarios (malicious traffic generated), ODL-3 node cluster controller had performed better than ONOS. In these five different scenarios, the amount of malicious traffic was incregradually increased. It also observed that, in terms of disk utilization, memory utilization, and CPU utilization, the ODL 3-node cluster was way ahead of the SDN controller.

There are many factors in mucosal secretions that contribute to innate immunity and the 'first line of defence' at mucosal surfaces. Few studies, however, have investigated the effects of exercise on many of these 'defence' factors. The aim of the present study was to determine the acute effects of prolonged exercise on salivary levels of selected antimicrobial peptides (AMP) that have not yet been studied in response to exercise (HNP1-3 and LL-37) in addition to immunoglobulin A (IgA). A secondary objective was to assess the effects of exercise on saliva antibacterial capacity. Twelve active men exercised on a cycle ergometer for 2.5 h at approximately 60% of maximal oxygen uptake. Unstimulated whole saliva samples were obtained before and after exercise. There was a significant decrease (P < 0.05) in salivary IgA:osmolality ratio, following exercise, but IgA concentration and secretion rate were unaltered. Salivary HNP1-3 and LL-37 concentrations (P < 0.01 and P < 0.05, respectively), concentration:osmolality ratios (P < 0.01) and secretion rates (P < 0.01) all increased following exercise. Salivary antibacterial capacity (against E. coli) did not change. The increased concentration of AMPs in saliva may confer some benefit to the 'first line of defence' and could result from synergistic compensation within the mucosal immune system and/or airway inflammation and epithelial damage. Further study is required to determine the significance of such changes on the overall 'defence' capacity of saliva and how this influences the overall risk for infection.

Today, the proportion of elderly and senile people is steadily growing throughout the world. The most important factors in the first line of immune defense of the mucous membranes of the upper respiratory tract are β-defensins, which are a group of secretory proteins with antimicrobial activity. The aim of this study was to study the expression of genes for antimicrobial peptides β-defensins and the composition of the microbiome of the mucous membranes of the upper respiratory tract in elderly people and long-livers with various aging phenotypes.The main study group included 67 centenarians and 49 elderly people, who were further divided into two subgroups depending on the course of aging (pathological and successful aging). Nucleic acids were isolated from nasopharyngeal scrapings and the expression levels of the DEFB1 and DEFB4 genes were determined using real-time polymerase chain reaction. The composition of the microbiota in nasopharyngeal swabs was determined by MALDI-TOF mass spectrometry.In analyzing the expression of the DEFB1 gene in elderly people and centenarians with successful and pathological aging phenotypes, no difference was revealed between the groups. Expression of the DEFB4 gene was increased in centenarians with pathological aging compared to centenarians with successful aging and in the elderly group. Excessive production of antimicrobial peptides is dual in nature; on the one hand, they provide the first line of defense against microorganisms, and on the other, they are cytotoxic to their own cells. An increase in the expression of the DEFB4 gene during aging may be due to an increase in the number of pathogen-associated molecular patterns, which can be one’s own microbiota and/or components of microbial metabolism. Analysis of the microbiota composition showed an increase in biodiversity in individuals with a successful aging phenotype compared to a pathological phenotype. Particular attention is paid to Staphylococcus spp., the species composition of which depends on the aging phenotype. In the pathological aging group, the frequency of St. aureus colonization is significantly higher than in the successful aging group.Thus, overexpression of the DEFB4 gene and changes in the composition of the microbiota of the mucous membranes of the upper respiratory tract may be one of the mechanisms explaining the increased susceptibility to infections in various aging phenotypes.

By comparing natural immunity to Aspergillus fumigatus (AF) in vivo with the action of human or mouse phagocytes against AF in vitro, we delineated two sequential lines of defense against AF. The first line of defense was formed by macrophages and directed against spores. Macrophages prevented germination and killed spores in vitro and rapidly eradicated conidia in vivo, even in neutropenic and athymic mice. The second was the neutrophilic granulocyte (PMN), which protected against the hyphal form of AF. Human and mouse PMN killed mycelia in vitro. Normal, but not neutropenic mice, stopped hyphal growth, and eradicated mycelia. Either line of defense acting alone protected mice from high challenge doses. Natural immunity collapsed only when both the reticuloendothelial system and PMN were impaired. These findings are in keeping with the clinical observation that high doses of cortisone and neutropenia are the main risk factors for invasive aspergillosis. Cortisone inhibited the conidiacidal activity of mouse macrophages in vivo and of human or mouse mononuclear phagocytes in vitro. Cortisone damaged this first line of defense directly and not through the influence of T lymphocytes or other systems modifying macrophage function as shown in athymic mice and in vitro. In addition, daily high doses of cortisone in mice reduced the mobilization of PMN so that the second line of defense was also impaired. Thus, cortisone can break down natural resistance on its own. Myelosuppression rendered mice susceptible only when the first line of defense was overpowered by high challenge doses, by activated spores that cannot be killed by macrophages, or by cortisone suppression of the conidiacidal activity of macrophages. The host, thus, can call upon two independent phagocytic cell lines that form graded defense systems against aspergillus. These lines of defense function in the absence of a specific immune response, which seems superfluous in the control and elimination of this fungus.

Dealing with network security has always been a challenging task, particularly in the prevention and detection of distributed denial of service (DDoS) attacks. Attacks such as DDoS pose hazards to the system by compromising its accessibility to individuals who need to use a specific server. This type of cyberattack occurs when a system is overloaded with a massive amount of traffic, causing the network to become unavailable. This attack type focuses on engaging the service with correct operators without breaching safety parameters. Responsible artificial intelligence (AI) refers to the ethical development and deployment of AI systems that prioritise fairness, transparency, privacy, and accountability. Currently, the deep learning method is very effective in distinguishing DDoS traffic from harmless traffic by removing the representation of higher-level features from lower-level traffic. The study presented in this paper proposes a responsible artificial intelligence-based hybridisation framework for attack detection using recursive feature elimination (RAIHFAD-RFE) for cybersecurity systems. The study aimed to analyse and propose efficient cybersecurity tactics for preventing, mitigating and detecting DDoS attacks using advanced methods. As a primary step, the RAIHFAD-RFE technique utilises the Z-score standardisation method for the data pre-processing phase to clean, transform and organise raw data into a structured format. Furthermore, the recursive feature elimination (RFE) model is employed for feature selection (FS) to identify and retain the most essential features, thereby improving model performance and reducing model complexity. Moreover, the hybridisation of long short-term memory and bidirectional gated recurrent unit (LSTM-BiGRU) models was employed for classification. To optimise model performance, the improved orca predation algorithm (IOPA) is utilised for hyperparameter tuning to select the optimal parameters for enhanced accuracy. A comprehensive experimental analysis of the RAIHFAD-RFE approach was performed under the CIC-IDS-2017 and Edge-industrial internet of things (IIoT) datasets. A comparison study of the RAIHFAD-RFE approach provided superior accuracy values of 99.35% and 99.39%, respectively, compared to existing models on the dual dataset.

Citation: 'first line of defence' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.13151 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Experimental modulation of cellular glutathione levels has been used to explore the role of glutathione in cadmium toxicity. Mice treated with buthionine sulfoximine [an effective irreversible inhibitor of gamma-glutamylcysteine synthetase (EC 6.3.2.2) that decreases cellular levels of glutathione markedly] were sensitized to the toxic effects of CdCl2. Mice pretreated with a sublethal dose of Cd2+ to induce metallothionein synthesis were not sensitized to Cd2+ by buthionine sulfoximine. Mice sensitized to Cd2+ by buthionine sulfoximine were protected against a lethal dose of Cd2+ by glutathione mono isopropyl ester (L-gamma-glutamyl-L-cysteinylglycylisopropyl ester), but not by glutathione. These results are in accord with studies that showed that glutathione mono esters (in contrast to glutathione) are efficiently transported into cells and converted intracellularly to glutathione. The findings indicate that intracellular glutathione functions in protection against Cd2+ toxicity, and that this tripeptide provides a first line of defense against Cd2+ before induction of metallothionein synthesis occurs. The experimental approach used here in which cellular levels of glutathione are decreased or increased seems applicable to investigation of other types of metal toxicity and of other glutathione-dependent biological phenomena.

Most interactions between plants and fungi or Oomycetes do not result in a successful infection but are thwarted by the host (Thordal-Christensen, 2003; Lipka et al., 2008). In many cases, the obvious visible first line of defence is the papilla, a cell wall apposition (CWA) laid down by the host at the site of attempted penetration by the fungus or Oomycete on the inside of the host cell wall. CWA are observed in many plant species but are best studied in the cereal–powdery mildew interactions where the CWA comprises the inner papilla surrounded by an outer halo. Histological and chemical analyses demonstrate the complexity of the papillae, which comprise callose, protein, and various phenolic compounds and inorganic compounds, especially opal silica and, at least transiently, reactive oxygen species (see Zeyen et al., 2002, for a review). It is clear that papillae play a significant role, since penetration is often arrested by papillae, but as to which components of papillae are important for successful defence against a particular species pathogen is unclear. In other words, the demonstration of the complexity of papillae is not a demonstration of their role in disease resistance and presents the question as to why they are so complex. What is the role of the individual components of the papilla? There are two approaches which use the tools of forward and reverse genetics to determine the role of individual components of papillae which will answer this question, at least in part. The regulation of the formation of papillae has been studied genetically in both barley and Arabidopsis. Mutants have been obtained in barley exhibiting resistance, and indeed the mlo mutant confers race-non-specific resistance in both species (Consonni et al., 2006). Other Arabidopsis mutations contribute to the assembly of papillae (Collins et al., 2003, 2007). The physiological role of the Arabidopsis gene products is uncertain in some cases (Lipka et al., 2008). Thus the forward genetics approach has favoured the identification of regulatory, like mlo, and mechanistic components, like Pen1, but has not yielded mutations in the phenolic biosynthetic pathways associated with papilla formation. The nature of the first line of defence in cereals is still something of a mystery despite many years of study. We know much but there is still much to learn. Wei and colleagues have previously developed Triticum monococcum L. (Einkorn, a diploid wheat) as an excellent model system to use as an alternative to barley. In this issue, the study by Bhuiyan et al. (2009) uses a forward genetic approach to study the role of papilla components in Einkorn wheat infected with the powdery mildew fungus Blumeria graminis. The result is compelling evidence that lignification of papillae plays an important role in defence against penetration by this fungus. Lignification is, in essence, the generation of wood. The process can be considered to comprise two phases, firstly, the biosynthesis of monolignols, the building bricks, and, secondly, the assembly and polymerization of these bricks in the papilla. This paper represents an in-depth study of the first phase, which is illustrated in Fig. 1 of Bhuiyan et al. (2009). The approach taken has been to screen an expression sequence tag (EST) library prepared from the epidermis of T. monococcum infected with B. graminis f. sp. tritici (Bgt) (Liu et al., 2005; Bhuiyan et al., 2007) which is predicted to be enriched for first line defences against Blumeria graminis (Wei et al., 1998; Collinge et al., 2002). This yielded 13 cDNAs representing eight genes encoding enzymes involved in monolignol biosynthesis, according to their bioinformatical analysis. That six of these transcripts exhibit nearly synchronized accumulation patterns, as revealed by Northern blotting of entire leaves and epidermal expression, as revealed by RT PCR, is an excellent indication of their role in papilla formation. Proof of the importance of monolignol biosynthesis comes from the reverse genetics of transient gene silencing of four of the biosynthetic genes and an additive effect was obtained by combining three of the genes pair-wise. Thus, silencing gave a statistically significant increase in the efficiency of penetration. In the control, roughly 40% of penetration attempts were successful by the host powdery mildew fungus Bgt and increased 4-fold in the non-host powdery mildew fungus, Bg. f.sp. hordei, which infects barley. The double silenced constructs gave over 70% successful penetration rates. The genes included TmPAL, which encodes the first enzyme in the phenylpropanoid pathway, and can be predicted to have other roles in defence in grasses. For example, flavonoid biosynthesis has been seen to be induced in barley in response to B. graminis (Christensen et al., 1998a, b). The combination of TmPAL with genes encoding the two final biosynthetic enzymes of

Firewall is a core element of a network security system which takes care of the availability, privacy, and integrity of network resources. However, managing a system with large scale, heterogeneous policies is complex and error prone. In multi-firewall systems, it is very important to configure the policy rules in the relevant firewall to prevent malicious flow into the network. Any modification to a firewall rule or insertion of a new rule needs intra and inter firewall conflict resolution to find correct mapping of rule to firewall. In SDN, the controller generates flow rules for different switches depending on application requirements and network topologies. Firewall can be used as a first line of defense against different attacks to the data plane and the control plane of SDN. The state-of-art work on firewall implementation in SDN shows various anomalies that may introduce functional failures and security violations. In this paper, we have proposed a novel approach for distributed anomaly-free firewall implementation on SDN controller. Here, the controller receives the firewall policies of different domains through north bound API and resolves the intra and inter firewall conflicts and derives a single anomaly-free firewall policy at the controller level. When the controller receives a packet_in message from a switch at run time, it selects a conflict free rule from global policy and sends it to appropriate switches. We have evaluated our proposed distributed firewall system for different network topologies under different attacking scenarios, e.g., DDoS attacks and experimental results are reported. The results show the efficacy of our solution in terms of reduced malicious traffic flows, improvements in CPU utilization of controller, packet loss and response time of legitimate packets.

The rapid growth of the internet and the increasing reliance on digital infrastructures have posed significant challenges to cybersecurity. Among the other variants of attacks, Distributed Denial of Service (DDoS) attacks have emerged as one of the most destructive and common threats. These attacks disrupt or slow down network services by overwhelming the network infrastructure with a massive volume of malicious traffic. To effectively identify and mitigate DDoS attacks, machine learning techniques have been extensively employed in intrusion detection systems. Machine learning approaches offer the advantage of automating the detection process by learning patterns and characteristics of DDoS attacks from historical data. Researchers have explored various machine learning algorithms such as K-Nearest Neighbours (KNN), Support Vector Machine (SVM), Random Forest (RF), and Naïve Bayes to classify and detect DDoS attacks. These algorithms leverage features extracted from network traffic data, including packet size, packet delay patterns, and traffic behaviour, to differentiate between normal and malicious traffic.

Cloud Data Center (CDC) security remains a major challenge for business organizations and takes an important concern with research works. The attacker purpose is to guarantee the service unavailability and maximize the financial loss costs. As a result, Distributed Denial of Service (DDoS) attacks have appeared as the most popular attack. The main aim of such attacks is to saturate and overload the system network through a massive data packets size flooding toward a victim server and to block the service to users. This paper provides a defending system in order to mitigate the Denial of Service (DoS) attack in CDC environment. Basically it outlines the different techniques of DoS attacks and its countermeasures by combining the filtering and detection mechanisms. We presented an analytical model based on queueing model to evaluate the impact of flooding attack on cloud environment regarding service availability and QoS performance. Consequently, we have plotted the response time, throughput, drop rate and resource computing utilization varying the attack arrival rate. We have used JMT (Java Modeling Tool) simulator to validate the analytical model. Our approach was appeared powerful for attacks mitigation in the cloud environment.

Mucosal surfaces are important physical barriers whose main function is to protect the systemic environment of the body against microbial invasion. It is the first line of defense to protect the animal and also functioning as an active immune tissue. Four mucosal-associated lymphoid tissues (MALTs), which start the immune responses are skin, gills, gut, and nose, have been reported in fish. Humoral and cellular immunity, their regulation and the factors that influence the response in these MALTs are still not well known in most fish species. These are principle doorway for microbial invasion and as such developing protective vaccines against these pathogens can serve as first line of defense against infections. In this review we have summarized the role of fish mucosal immunity to provide the first line of defense mechanism against microbial invasion. Increased knowledge of fish mucosal immune system will facilitate the development of novel vaccination strategies in fish. Keywords: Mucus, mucosal immunity, MALT, B cells, T cells Cite this Article Supriya Dash, Jayashree Nanda, Soumyashree Barik et al. Mucosal Defense Mechanism in Fish: An Overview. Research & Reviews: A Journal of Immunology . 2017; 7(3): 1–5p.