Academic literature on the topic 'Black-hole attack Tree'

Thick bark has been shown to protect trees from wildfires, but can it protect trees from an ambrosia beetle attack? We addressed this question by examining the distribution of holes of the invasive Kuroshio Shot Hole Borer (KSHB, Euwallacea kuroshio; Coleoptera: Scolytinae) in the bark of Goodding’s black willow (Salix gooddingii), one of the KSHB’s most-preferred hosts. The study was conducted in the Tijuana River Valley, California, in 2016–17, during the peak of the KSHB infestation there. Using detailed measurements of bark samples cut from 27 infested trees, we tested and found support for two related hypotheses: (1) bark thickness influences KSHB attack densities and attack locations, i.e., the KSHB bores abundantly through thin bark and avoids boring through thick bark; and (2) bark thickness influences KSHB impacts, i.e., the KSHB causes more damage to thinner-barked trees than to thicker-barked trees. Our results indicate that thick bark protects trees because it limits the density of KSHB entry points and thereby limits internal structural damage to low, survivable levels. This is the first study to identify bark thickness as a factor that influences the density of KSHB—or any ambrosia beetle—in its host tree, and the first to link bark thickness to rates of host tree mortality.

The polyphagous shot hole borer (PSHB) is an invasive ambrosia beetle that forms a symbiosis with a new, as-yet-undescribed Fusarium sp., together causing Fusarium dieback on avocado and other host plants in California and Israel. In California, PSHB was first reported on black locust in 2003 but there were no records of fungal damage until 2012, when a Fusarium sp. was recovered from the tissues of several backyard avocado trees infested with PSHB in Los Angeles County. The aim of this study was to determine the plant host range of the beetle–fungus complex in two heavily infested botanical gardens in Los Angeles County. Of the 335 tree species observed, 207 (62%), representing 58 plant families, showed signs and symptoms consistent with attack by PSHB. The Fusarium sp. was recovered from 54% of the plant species attacked by PSHB, indicated by the presence of the Fusarium sp. at least at the site of the entry hole. Trees attacked by PSHB included 11 species of California natives, 13 agriculturally important species, and many common street trees. Survey results also revealed 19 tree species that function as reproductive hosts for PSHB. Additionally, approximately a quarter of all tree individuals planted along the streets of southern California belong to a species classified as a reproductive host. These data suggest the beetle–disease complex potentially may establish in a variety of plant communities locally and worldwide.

The paper presents a new security aspect for a Mobile Ad-Hoc Network (MANET)-based IoT model using the concept of artificial intelligence. The Black Hole Attack (BHA) is considered one of the most affecting threats in the MANET in which the attacker node drops the entire data traffic and hence degrades the network performance. Therefore, it necessitates the designing of an algorithm that can protect the network from the BHA node. This article introduces Ad-hoc On-Demand Distance Vector (AODV), a new updated routing protocol that combines the advantages of the Artificial Bee Colony (ABC), Artificial Neural Network (ANN), and Support Vector Machine (SVM) techniques. The combination of the SVM with ANN is the novelty of the proposed model that helps to identify the attackers within the discovered route using the AODV routing mechanism. Here, the model is trained using ANN but the selection of training data is performed using the ABC fitness function followed by SVM. The role of ABC is to provide a better route for data transmission between the source and the destination node. The optimized route, suggested by ABC, is then passed to the SVM model along with the node’s properties. Based on those properties ANN decides whether the node is a normal or an attacker node. The simulation analysis performed in MATLAB shows that the proposed work exhibits an improvement in terms of Packet Delivery Ratio (PDR), throughput, and delay. To validate the system efficiency, a comparative analysis is performed against the existing approaches such as Decision Tree and Random Forest that indicate that the utilization of the SVM with ANN is a beneficial step regarding the detection of BHA attackers in the MANET-based IoT networks.

Along with the expansion of Internet of Things (IoT), the importance of security and intrusion detection in this network also increases, and the need for new and architecture-specific intrusion detection systems (IDS) is felt. In this article, a distributed intrusion detection system based on a software defined networking (SDN) is presented. In this method, the network structure is divided into a set of sub-networks using the SDN architecture, and intrusion detection is performed in each sub-network using a controller node. In order to detect intrusion in each sub-network, a decision tree optimized by black hole optimization (BHO) algorithm is used. Thus, the decision tree deployed in each sub-network is pruned by BHO, and the split points in its decision nodes are also determined in such a way that the accuracy of each tree in detecting sub-network attacks is maximized. The performance of the proposed method is evaluated in a simulated environment and its performance in detecting attacks using the NSLKDD and NSW-NB15 databases is examined. The results show that the proposed method can identify attacks in the NSLKDD and NSW-NB15 databases with an accuracy of 99.2% and 97.2%, respectively, which indicates an increase compared to previous methods.

Purpose of the study: development of a distributed routing algorithm to ensure security in wireless self-organizing networks from intruder attacks on the network. Methods: application of algorithms, graph theory, discrete optimization and heuristic approaches based on the results of numerical experiments. Results: the paper proposes a modified distributed routing algorithm for self-organizing networks. The algorithm, presented in this paper, is based on a distributed version of Dijkstra’s algorithm, designed to detect the shortest paths without loops on a graph under conditions of changing the weight of its edges. The loop freedom in this case is achieved by storing at each node an additional table containing the penultimate nodes on the shortest routes to all nodes, which allows the node to build a tree of shortest routes with itself as a root. In the modification of the algorithm, these tables are used by the nodes to check the correspondence of the declared route and the return route, which makes it possible to recognize and exclude from the network an intruder who carries out attacks to disrupt the correct routing mechanism. The effectiveness of the proposed algorithm for protection against routing attacks, in particular, black hole attacks, is confirmed by the results of testing on a program model.

Notes on the reproduction, breeding biology and ethology of the Eurasian pygmy owl (Glaucidium passerinum) in Slovakia Accessible data on 78 breeding occurrences of the Eurasian pygmy owl (Glaucidium passerinum) in Slovakia are evaluated. Data from the oldest known breeding in 1846 up to 2010 were used. The breeding of this species has been proved in 24 orographic units, at altitudes from 450 (400) to 1450 m. Distribution of the species in Slovakia closely follows the distribution of fir (Abies alba) and spruce (Picea abies) and breeding has also been recorded in forest habitats with an abundance of scots pine (Pinus silvestris) and black pine (Pinus nigra). From the point of view of natural and secondary origin of these forest habitats, the species breeds in both ‘natural’ habitats such as montane spruce forests and Euro-Siberian coniferous forests, forests with beech and fir, oak-hornbeam forests with lime and fir, as well as in secondary forest spruce plantations. From 22 evaluated Slovakian nests as many as 17 (70.8%) were situated no farther than 200 m from water. A high number of nests (72.5%) were situated at altitudes between 600-1100 m, with 13% above this range and 14.5% below. As many as 25 nest holes were located in spruce, both living and dead, and in snags, ten in fir (with a significant number of dead stumps), six in beech, four in oak and four in aspen. Nests were also found on one occasion each in larch, maple and black pine. On one occasion breeding took place in a nest-box. On several occasions the same nest hole was used repeatedly, with the highest number of such occasions being four times in the same tree in an eight year period. On three occasions a shift of nest location of ca. 200-350 m within the same territory occurred and two neighbouring pairs, and nests, were once found at the same time just 400 m from each other. Nest holes excavated by the Dendrocopos major and Picoides tridactylus are often used. On four occasions breeding took place in natural cavities (2x beech, 1x larch, 1x maple). The lowest situated nest was placed lower than one m above ground level and the highest 13 m above the ground. From 44 evaluated nest holes the highest number (26) were situated between 4-7 m. The production of young was evaluated in 57 cases, 34 of which were successful (69.7%). Young were found on 27 occasions, from which 80 fledged: an average of 2.96 per nest. This average is slightly lower than that calculated in Austria and Germany. In the colder than usual years of 2009 and 2010, which were poorer in food availability and characterized by high precipitation, the numbers of fledglings was even lower: on average only 2.3 and 2.0 fledglings per nest respectively. The average number of fledglings per nest from 8 Slovakian nests in three consecutive years (1989 to 1991) was 3.75 fledglings per nest but the same parameter from nine Slovakian nests in six years (2005 to 2010) dropped to 2.88. This indicates a diminishing trend in nest productivity. On one occasion the movements of fledglings in the territory after their fledging were observed for 27 days. On other occasions disturbance due to human activity (tree felling) was recorded as the reason for an abandoned breeding attempt. Such disturbance can be extreme, for example, in the Kysuce Region in the Javorníky Mts and Turzovská vrchovina Mts, two breeding sites with nests in 1999 and 2003 were later destroyed because of complete removal of those forest tracts attacked by bark-beetles. In 2009 in the Strážovské vrchy Mts, a curious case was observed where, during the period of parent care of nestlings, the male disappeared but the female continued to feed her two nestlings alone until they fledged. Just after fledging these fledglings were predated, probably by a Pernis apivorus or an Accipiter nisus, both of which bred nearby. The authors made several remarkable ethological observations in the life of Eurasian pygmy owls. In the Strážovské vrchy Mts the ‘nest-showing’ of more than one cavity in its territory by the male to the female was observed. Copulation was observed a total of eleven times during the months February - May in the years 1989-2010, with the following frequency: February 1x, March 3x, first half of April 5x, second half of April 1x, beginning of May 1x. Interactions of the Eurasian pygmy owls with diurnal raptors, other owl species and other cavity-breeders were also documented. In the Strážovské vrchy Mts the breeding of an Eurasian pygmy owl pair at a relatively close distance to the nests of various diurnal raptors were as follows (species/distance from nest of the raptor from nest of the Eurasian pygmy owl): Pernis apivorus 7 m, Accipiter nisus 230 m, Buteo buteo 250 m, Aquila pomarina 500 m, Accipiter gentilis 700 m. In the Volovské vrchy Mts a pair of Eurasian pygmy owls successfully bred at a distance of 600 m from two nests of Strix uralensis, and another pair bred at a distance of 500 m from a nest of Strix aluco. The breeding of another pair of Strix aluco just 30 m from a cavity used by a pair of Eurasian pygmy owl led to unsuccessful breeding/abandoned nest by this pair. Competitive behaviour was observed between the Eurasian pygmy owl and other cavity-breeders such as Sitta europaea and Dendrocopos major, and an occasion of the predatory killing of an owl fledgling by Strix uralensis was suspected. An attack by Aegolius funereus on a Eurasian pygmy owl was also observed.

Vehicular ad hoc networks (VANETs) are used for vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications. They are a special type of mobile ad hoc networks (MANETs) that can share useful information to improve road traffic and safety. In VANETs, vehicles are interconnected through a wireless medium, making the network susceptible to various attacks, such as Denial of Service (DoS), Distributed Denial of Service (DDoS), or even black hole attacks that exploit the wireless medium to disrupt the network. These attacks degrade the network performance of VANETs and prevent legitimate users from accessing resources. VANETs face unique challenges due to the fast mobility of vehicles and dynamic changes in network topology. The high-speed movement of vehicles results in frequent alterations in the network structure, posing difficulties in establishing and maintaining stable communication. Moreover, the dynamic nature of VANETs, with vehicles joining and leaving the network regularly, adds complexity to implementing effective security measures. These inherent constraints necessitate the development of robust and efficient solutions tailored to VANETs, ensuring secure and reliable communication in dynamic and rapidly evolving environments. Therefore, securing communication in VANETs is a crucial requirement. Traditional security countermeasures are not pertinent to autonomous vehicles. However, many machine learning (ML) technologies are being utilized to classify malicious packet information and a variety of solutions have been suggested to improve security in VANETs. In this paper, we propose an enhanced intrusion detection framework for VANETs that leverages mutual information to select the most relevant features for building an effective model and synthetic minority oversampling (SMOTE) to deal with the class imbalance problem. Random Forest (RF) is applied as our classifier, and the proposed method is compared with different ML techniques such as logistic regression (LR), K-Nearest Neighbor (KNN), decision tree (DT), and Support Vector Machine (SVM). The model is tested on three datasets, namely ToN-IoT, NSL-KDD, and CICIDS2017, addressing challenges such as missing values, unbalanced data, and categorical values. Our model demonstrated great performance in comparison to other models. It achieved high accuracy, precision, recall, and f1 score, with a 100% accuracy rate on the ToN-IoT dataset and 99.9% on both NSL-KDD and CICIDS2017 datasets. Furthermore, the ROC curve analysis demonstrated our model’s exceptional performance, achieving a 100% AUC score.

The Tijuana River Valley is the first natural habitat in California to be substantially invaded by the Kuroshio Shot Hole Borer (KSHB,Euwallaceasp.), an ambrosia beetle native to Southeast Asia. This paper documents the distribution of the KSHB in the riparian vegetation in the valley and assesses the damage done to the vegetation as of early 2016, approximately six months after the beetle was first observed in the valley. I divided the riparian habitats into 29 survey units so that the vegetation within each unit was relatively homogenous in terms of plant species composition, age and density. From a random point within each unit, I examined approximately 60 individuals of the dominant plant species for evidence of KSHB infestation and evidence of major damage such as limb breakage. In the 22 forested units,I examined the dominant arroyo and black willows (Salix lasiolepisBenth. andS. gooddingiiC.R. Ball), and in the seven scrub units, I examined mule fat (Baccharis salicifolia(Ruiz & Pav.) Pers.). Evidence of KSHB infestation was found in 25 of the 29 units. In the forest units, infestation rates ranged from 0 to 100% and were high (>60%) in 16 of the units. In the scrub units, infestation rates ranged from 0 to 33%. Infestation rates were significantly correlated with the wetness of a unit; wetter units had higher infestation rates. Evidence of major physical damage was found in 24 units, and dense stands of willows were reduced to broken trunks in several areas. Overall, I estimated that more than 280,000 (70%) of the willows in the valley were infested, and more than 140,000 had suffered major limb damage. In addition, I recorded evidence of KSHB infestation in the other common plant species in the valley; of the 23 species examined, 14 showed evidence of beetle attack. The four species with the highest rates of infestation were native trees in the Salicaceae family. The three species considered to be the worst invasive plants in the valley,Ricinus communisL., Tamarix ramosissimaLedeb. andArundo donaxL., had low rates of infestation. Several findings from this study have significance for resource managers: (1) the KSHB attack caused extensive mortality of trees soon after being first discovered so, if managers are to control the spread of the beetle, they will need to develop an effective early detection and rapid response program; (2) infestation rates were highest in units that were wet, so resource managers trying to detect the beetle in other areas should thoroughly search trees near water, particularly nutrient-enriched water; (3) the infestation appears to be a novel form of disturbance, and the affected forests may need special management actions in order to recover; and (4) the infestation has altered the structure of the forest canopy, and this is likely to promote the growth of invasive plant species that were relatively inconspicuous in the forests prior to the beetle attack but will now need more attention.

The purpose of the study of this article is to highlight the history of the discovery of horse harnesses and rig at the end of the nineteenth and early twentieth centuries, and their characteristics. That objects belonged to Chorniyfamily from Kiev and were transferred in 1979 to create an exposition of museums. Presently, the items of horse harnesses and harnesses from the stock collection NHER «Pereyaslav» are exhibited in the museums «Postal Station», «Museum of the National Land Transport of the Middle Dnieper».These museums are located on the territory of the first Museum of Folk Architecture and Life of the Middle Dnieper, established in 1964 in Pereyaslav-Khmelnytskyi city and is the part of the National Historical and Ethnographic Reserve «Pereyaslav». This collection has been gathering for decades. Mikhail Zham (1927–2002) was an ideological inspiration and active collector of horse harness and rigs. Among the large number of horse ruminant, which is in the exposition of museums, there are 25 harnesses and rigsof I. Chorniy. At the beginning of the twentieth century Ivan Chorny, like his father was. I. Chorny, was engaged in camping, had a camping and caravan artillery, a large collection of vehicles, horse harnesses and rigs. Horse rigs – a collection of items for harness, as well as a way to harness them. Rigs should be distinguished from harness, which is a more general term and includes both objects and accessories for harnessing, and for hanging horses and other animals (for horseback riding, or the use of pets). Among the items (harnesses and rigs) belonging to the Black family are: Yoke – a cervical part of a horse's rigs, through which the weight of the transported cargo is transmitted to the horse's neck. There are four in their collection. The arc is a part of a horse's rigs from a bent trunk of a tree, which serves to attach a hawk (one of the two poles, attached to the ends of the front of the car's vehicle) to the yoke. There are three of them. Squares – a long belt, a rope, etc., by which horses are ruled, fixed on both sides to the bridle. The stock collection consists of four units of the box. Bridle («knot») – a piece of harness, which is worn on the animal's head to control it. The collection consists of five pieces of bridles. Breast-bandis a long belt that covers the horse's body and holds the band from slipping around the neck, for example, during descent from the mountain, braking. The collection has four units. Сherezsidelko- a strap that passes through a saddle from one hole to the other, supporting them. Saddle – a part of the rig, in the form of a pillow, which is enclosed under the cherezsidelko. Serves to convey force on the back of a horse. There are 3 of them in collection. Attention is focused on the features of manufacturing, material, technology, and the analysis of harnesses and rigs were made. Also, authors focus on the fact that, depending on the used harness, rigs are divided into: «holobelʹno-postoronkovyy» harness, sidewalk harness; a combined harness. An overview of the declared assembly, analysis of the species, typological, structural features of the horse harness, the comparison of these elements, shows that the samples presented in it are the same type of design, material, technology and characteristic of the entire territory of Ukraine. At the same time, some of them are distinguished by the original artistic decoration, which is a manifestation of the preferences and artistic tastes of the masters who made them. The horse harness and rigs of Chorniy family organically complements the structure and subjects of the exposition of the Museum of National Land Transport and the Museum «Postal Station» of the National Historical and Ethnographic Reserve «Pereyaslav».

Mobile adhoc network, a derivative of the adhoc network is sensitive to heterogeneous forms of attacks in particular passive and active attacks. Black hole attack is one such continually prevailing threat in mobile adhoc networks (MANETs), where specific nodes operate spitefully in the course of data transmission. Throughout this work, we intend to present an effectual approach to detect and intercept this attack taking into account Dynamic MANET on-demand (DYMO) routing protocol. This work presupposes working in three modulesplanting, detection and ultimately the interception against the black hole attack. An IDS is initiated on the notion of machine leaning using MATLAB software. A relative scrutiny of IDS grounded on classifiers like K-Nearest Neighbor, Support Vector Machine, Decision tree and neural network is also conducted to make it certain that the best feasible classifier is settled on for administering the IDS. The analysis of the put forward work is subsequently accomplished taking miscellaneous metrics covering packet drop rate, average transmission delay, Packet Delivery Ratio along with throughput.

The open medium, dynamic topology and distributed operation in Mobile Ad hoc Networks (MANET) leads to high risks. Many solutions are proposed to protect a MANET from attacks, ranging from attack identification to prevention. Although these solutions reduce and avoid the attacks in a MANET, sometimes they identify many false attacks as real ones which may cause huge loss of resources. For example, a sudden route breakdown can cause delay in packet delivery; differentiating such a delay from the delay caused by an attacker is difficult. Further, an intelligent attacker could also cause false negative alarms in the network by manipulating the ADS. The attacker could avoid detection by an ADS by delaying the packets in small incre- ments which lead to large increments in delay over time. Such an attack could be detected by using a strong bound on the threshold of delay parameter. But, this could cause false positive alarms as discussed in the above example. Such false alarms occur more often when an attack is complex and has multiple features. In this thesis we propose solutions to mitigate such false alarms and improve the attack detection probability. In thesis we made an attempt to design a system which identifies and con firms the attacks, to protect the MANET from false attacks and loss of resources due to false alarms. The system designed, enhances the attack detection rate by confirming the occurrence of the attack through analysis of the current attack scenario and the past history of attacks. First, we designed and developed, a Wormhole Attack Confirmation (WAC) System using Honeypots to mitigate false alarms in a MANET and protect its resources during a wormhole attack. We embark on the study by building an attack tree of the wormhole attack. The attack tree is built by identifying all the network conditions which could trigger the wormhole attack. These conditions are called as symptoms of wormhole attack and are analyzed by the honeypot. The Honeypot is centrally located and confirms the wormhole attack in a three step process. It makes an assessment of the current scenario using the attack tree of the wormhole attack, and compares it with the similar scenarios in the past with inputs from Attack History Database (AHD) to provide a verdict on the scenario. For preserving the security of a Mobile Ad hoc Network, we need to determine the origin of the attack, that is, trace the location of the attacker. Determining the physical location of the attacker helps in con nement of the attacker and attack. However, traditional attacker trace- back schemes fail to perform in a MANET which leads to huge degradation of its performance. Hence, we propose a Wormhole Attacker Tracing system to trace the location of a wormhole attacker in a MANET. The system runs on the Honeypot and collects the information about the attack from the victim's neighbors using bloom filters. Honeypot extracts the informa- tion from the bloom filter, and the information about the past attacks from Attack History Database (AHD), to trace the location of the wormhole attacker. The zone of the attacker is determined by the honeypot using the concept of Dominating sets. Further, the exact location of the attacker within the zone is determined by interacting with the attacker and identifying the dominant congested link. To demonstrate the WAC system functioning, we have considered the real time applications like email services. We have simulated the WAC system exclusively with email dumping by the attacker under various network load conditions. The system accurately identifies fake attacks and location of the attacker. We extended the technique for the black-hole attacks in a MANET. The Black-hole Attack Confirmation (BAC) system uses honeypot to intelligently identify and confirm the black-hole attack. Honeypot identifies the actions of a black-hole attacker in the current attack scenario with the help of the Black-hole attack Tree (BAT). BAT is an exhaustive sketch of all possible ways a black-hole attack can launched on a MANET. Further, honeypot analyzes the history of attacks from Attack History Database (AHD),to con firm the black-hole attack. Together with the BAT and AHD, the honeypot adapts itself to the current attack scenario, and efficiently confi rms the black-hole attack in a MANET. To preserve the security of a MANET we designed a Black-hole Attacker Tracing system to locate and quarantine the black-hole attacker. The system works in two phases. In phase one, the Honeypot determines the zone of the black-hole attacker. To identify the zone of the black- hole attacker, the honeypot maintains an open connection with the attacker, while collecting the information about the attacker. The current information is enhanced with the knowledge available in the attack history database. Honeypots analyze the actions of the attacker using Dominating sets. The physical location of the black-hole attacker within the zone is determined by identifying the dominant un-reliable node. Later we integrated both systems: WAC and BAC and deployed in MANET where IoT- Health care is a major application. Health care is one of the rapidly developing system in the context of IoT. The value held by the health care attracts a large number of attackers. These systems inherit the vulnerabilities of its underlying access networks like MANET which hinder its deployment. We have applied our systems to counter the attacks on an IoT-Health care network based on a MANET. The purpose of the experiment is to mitigate multiple attacks in an IoT-Health care network. In summary: (1) We designed a Wormhole Attack Con firmation (WAC) system using Hon- eypot through which we make an attempt to confi rm the attack by analyzing a wormhole attack holistically using a attack tree; (2) We designed a Wormhole Attacker Location Tracing Scheme to trace the location of a wormhole attacker by exploiting the properties of the wormhole attack using the dominating sets; (3) We evaluated the performance of WAC system with real time application of email service in a MANET; (4) We designed a system to protect the MANET from the black-hole attack through the Black-hole Attack Confirmation (BAC) system using Honeypot and the Black-hole Attack Tree (BAT); (5) We then designed a Black-hole Attacker Tracing system using Honeypot, where the system first identifying the zone of the attacker followed by identifying the attacker within the zone by collecting the information about the attack from neighbors of victim, and extracting the information about similar attacks from history; (6) We have applied the attack confirmation systems to an IoT-Health care network to identify and confirm multiple attacks in IoT-Health care network. We have simulated the designed system in several IoT-Health care environments, of varying sizes of nodes and applications. On several occasions the results have demonstrated that the proposed system is efficient in confirming multiple attacks, thereby saving the resources and minimizing the path reestablishment. Thus the systems presented in this thesis are capable of avoiding attacks in a practical network and also save important resources of the network.