Intruder Recognition Research Articles

A new deep-learning with swarm based feature selection for intelligent intrusion detection for the Internet of things

Humanity can benefit from the Internet of Things (IoT) paradigm in many different ways. IoT devices are nonetheless susceptible to different cyber-attacks launched by the attacker owing to their constrained resources. Using MLTs (Machine Learning Techniques) in IDSs (Intrusion Detection Systems) network data is classified as either benign or harmful depending on its characteristics. However, the growth in IoT devices and the massive, high-dimensional data they produce need the development of more effective searches and learning algorithms. By implementing optimization algorithms on the BoT-IoT dataset, an intruder recognition method for IoT based on DLTs (Deep Learning Techniques). An advanced DLT namely FR-CNN (Faster Recurrent Convolution Neural Network) is used in this framework to categorize incursions. In this paper, a novel GA-FR-CNN (Genetic Algorithm and Faster Recurrent Convolution Neural Network) has been proposed. Additionally, this paper introduces a brand-new feature selection method for IDSs. Network dataset's complexities are greatly reduced and the usage of AAFSO (Assimilated Artificial Fish Swarm Optimization) method to improve recommended systems assisted in identifying characteristics that were important to the problem. After gathering the features, they were sent into GA-FR-CNN algorithms for processing. The experimental result shows the suggested method for an intruder detecting systems, which is based on DLTs, while using UNSW-NB 15 dataset, the AAFSO with GA-FR-CNN provides high accuracy of 94.4880% when compared to the existing methods. When using BOT-IoT dataset, the AAFSO with GA-FR-CNN provides high accuracy of 93.7756%. The proposed method achieves better performance in UNSW-NB 15 dataset than BOT-IoT dataset.

Intruder familiarity and not duet similarity influences the territory defense in a year-round territorial bird species

To avoid unnecessary energy expenditures in territorial defense, many species (e.g., insects, amphibians, birds, and mammals) have developed the capability to distinguish between different intruder types using visual, acoustic, and/or chemical signals. Determining the mechanism used for intruder recognition is key to understanding the dynamics of territorial behaviors. In birds that use vocalizations for territorial defense, the frequency and duration of vocalizations or the familiarity with the intruder may be the main mechanism used for intruder recognition. Here, we conducted a playback experiment with territorial White-eared Ground-sparrows (Melozone leucotis), to analyze if territorial pairs recognize intruders using frequency and duration characteristics (a bird's response is based on how structurally similar the intruders' duets are to their own) or by familiarity with the intruders (neighbors vs. non-neighbors). We focused on duets because this species uses duets exclusively for territorial defense. We broadcasted a duet from a territorial neighbor, two duets from non-neighbors (with different frequency and duration characteristics), and a duet from a control species in 39 territorial pair from three populations. During playback we measured five behavioral responses: latency of the first vocalization, latency of the approach to the speaker, time spent close the speaker (within 5 ​m), number of individuals that approached the speaker, and the number of vocalizations. We found that territorial White-eared Ground-sparrow pairs responded stronger to neighbors than non-neighbors, and this response is not influenced by duet duration or frequency characteristics. This result suggests that neighbors represent a greater territorial threat for White-eared Ground-sparrows than non-neighbors. Further work is necessary to understand how common this observation is for tropical species that defend small territories year-round.

Dynamic keystroke pattern analysis and classifiers with competence for user recognition

The classification of biometric data is always a difficult task because these data are often unstable and depends on behavioural condition of a person. Personal keystroke activity is difficult to imitate and can be used for identity authentication. In this article, we suggest that the analysis of keystroke dynamics can dramatically increase the level of security of a computer system without disturbing the user’s comfort. First, the user’s established behavioural profile is loaded and then this profile is continuously compared with the current use of the keyboard. If a user’s temporary behavioural profile differs from their established profile, then the access to the computer is blocked. If a current profile of the user is recognized as legitimate, then profile can be dynamically changed, which allows to adjust profiles according to users abilities. Security based on keystroke dynamics analysis depends primarily on the quality of recognizing changes in a user’s profile. Recognition is performed on the dynamic analysis of the feature vector recorded while using the keyboard. In the presented approach, we propose using classifiers with their competence selection, which significantly improves the recognition of users. To select the most appropriate classifiers, the competences of the classifiers in a pool are calculated and then, the most powerful classifiers are selected. Conducted experiments, supported by the proper statistical analysis, confirm the usefulness of the proposed strategy in authorized user and intruder recognition.

An enhanced security alert system for smart home using IOT

<p>Today due to advancement in technology and Internet of Things, to deal with step-by-step jobs like mailing, accessing bank entries, watching degree of hotness and other jobs PCs were utilized. Because of fast improvement in IOT nowadays tablets, advanced mobile phones are utilized for such assignments [1]. Home security can be characterized as observing the home remotely located or centrally located. Today, home security is getting to be vital as the conceivable outcomes of interruption is expanding step by step, yet they have issues like postponement, non-web empowered and hard to deal. Intruder recognition is basic parts of home computerization and home security frameworks. Most generally, utilized specialized devices are mobile phones and sending mails are considered for controlling home appliances remotely by proposing productive structures. An Enhanced Security Alert System for Smart Home using IOT is composed in our proposed work. It identifies the intruder when no one is in home by sending alert message or caught picture to the proprietor (or) owner. Proposed framework is ease home security framework utilizes an IP Web-camera and Raspberry pi for limiting delay during the time of sending alert message. Fog Computing is incorporated to proposed framework to expand the level of security and limit the engendering delay. Proposed framework is to give minimal effort arrangement and adaptable association instrument for coordinating Internet of Things with home security frameworks.</p><p><em> </em></p>

Caste-dependent brood retrieval by workers in the ant Formica exsecta

The ability to distinguish friends from foe is a widespread phenomenon among social animals. In ants, recognition of intruders is important for the maintenance of colony integrity and survival. Intruders are typically adult, but the acceptance of non-nestmate brood could result in severe fitness costs, depending on the caste of the brood. Accepting non-nestmate worker brood may not carry a cost, as they should not drain resources of the adoptive colony but may instead add to the workforce. Sexual brood, however, would typically not contribute to colony performance, yet require resources, and should thus be rejected. Here, we tested whether workers of the narrow-headed ant, Formica exsecta, which strongly discriminate between adult nestmates and non-nestmates, also discriminate between nestmate and non-nestmate pupae. Furthermore, we investigated whether the caste of the brood (workers/sexuals) affects discrimination. We carried out analysis of surface chemicals to investigate whether the chemical distance between colonies was associated with the propensity to accept non-nestmate pupae. We show that worker pupae were retrieved irrespective of their origin, whereas nestmate sexual pupae were retrieved at a slightly higher rate than non-nestmates. Our chemical data, however, suggest that both the reproductive and the worker brood carry sufficient chemical information for discrimination, as they both express colony signatures. However, this information is acted upon only in the case of sexual brood. Our results thus suggest that workers selectively capitalize on the chemical information in agreement with fitness predictions, albeit to a lower extent than during discrimination between adult individuals.

Design and Implementation of an Embedded Smart Intruder Surveillance System

Remote and scattered valuable and sensitive locations such as labs and offices inside university campus need efficient monitoring and warning system. As well as scattered area and belonging. This research presents a Real-Time intruder Surveillance System based on a single board computer (SBC). Thus the design and development of a cost effective surveillance management system based SBC that can be deployed efficiently in remote and scattered locations such as universities belonging. The fusion of embedded Python codes with SBC that attached to cameras, Long distance sensors, alerting circuitry and wireless module presents a novel integration based effective cost solution and enhances SBC of much flexibility of improvement and development for pervasive remote locations. The system proves the high integrity of smooth working with web application, it’s cost effective and thus can be deployed as many of units to seize and concisely covered remote and scattered area as well as university belonging and departments. The system can be administrated by a remote user sparsely or geographically away from any networked workstation. The proposed solution offers efficient stand alone, flexibility to upgrade and cheap development and installation as well as cost effective ubiquitous surveillance solution. In conclusion, the system acceptable boundaries of successful intruder recognition and warning alert are computed between 1m and 3m distance of intruder from system camera. Recognition rate of 95% and 83% are achieved and the successful warning alert were in the range of 86-97%.

Multi-sensor systems for monitoring access to restricted areas: capabilities of the intrusion detection video analytical channel

The analysis of research publications dealing with security of critical facilities and their protection from terrorist threats suggests that the multisensor systems proposed in the literature need to be supplemented with a video analytical system to enhance the reliability of detecting the intrusion to the restricted access area and recognition of intruders' intentions. An algorithm for solving the first part of the problem, based on the implementation of the principle of accumulation, is proposed. The issue of recognizing the intruders' intentions is partially addressed. The probabilities of an error of the first and second kind for the proposed intrusion detection algorithm are estimated.

Nestmate Recognition in the Amazonian Myrmecophyte Ant Pseudomyrmex concolor Smith (Hymenoptera, Formicidae)

Nestmate recognition is fundamental to colonial cohesion in social insects, since it allows altruistic behavior towards relatives, recognition of intruders, territorial monopoly and resources defense. In ants, olfactory cues is a key factor in this process. Pseudomyrmex concolor is a highly aggressive ant that defends their host plant Tachigali myrmecophila against herbivores. However, this defense depends on the ant ability to discriminate in order to treat differentially between members of their own colony and intruders . In this study we investigated “whether” and “how” P. concolor recognizes nestmates from non-nestmates. We hypothesized that P. concolor is skillful in recognizing nestmates and tested it in field with experiments using nestmates and non-nestmates. Additionally, to test the efficiency of resident ants against intraspecific competition during colony foundation, we simulate the plant occupation by a competitor queen, introducing non-nestmates queens in plants previously occupied by P. concolor. For the issue of the "how", we hypothesized that the main cue used by this ant in nestmate recognition is olfactory signal. Thus, we tested adaptive threshold model, which predicts that, if the individual odor and colony’s internal template are discrepant enough, the resident nestmate will behave aggressively towards incoming individuals. In this case, we confined nestmates with non-nestmates odors, and then, we reintroduced them in its host plants. In each experiment the frequency of aggressive behaviors were recorded and compared. Results showed that P. concolor recognize and discriminate nestmates from non-nestmates workers (biting and stinging them) and exclude potential competitors queens. Workers reintroduced in their own colony after impregnated with non-familiar odor were treated as non-nestmates. The adaptive threshold hypothesis was confirmed, the main cue used by this ant species in nestmate recognition is olfactory signals.

How to escape from the host nest: Imperfect chemical mimicry in eucharitid parasitoids and exploitation of the ants’ hygienic behavior

Communication in ants is based to a great extent on chemical compounds. Recognition of intruders is primarily based on cuticular hydrocarbon (CHC) profile matching but is prone to being cheated. Eucharitid wasps are specific parasitoids of the brood of ants; the immature stages are either well integrated within the colony or are protected within the host cocoons, whereas adult wasps at emergence must leave their host nest to reproduce and need to circumvent the ant recognition system to escape unscathed. The behavioral interactions between eucharitid wasps and workers of their host, the Neotropical ant Ectatomma tuberculatum, are characterized. In experimental bioassays, newly emerged parasitoids were not violently aggressed. They remained still and were grabbed by ants upon contact and transported outside the nest; host workers were even observed struggling to reject them. Parasitoids were removed from the nest within five minutes, and most were unharmed, although two wasps (out of 30) were killed during the interaction with the ants. We analyzed the CHCs of the ant and its two parasitoids, Dilocantha lachaudii and Isomerala coronata, and found that although wasps shared all of their compounds with the ants, each wasp species had typical blends and hydrocarbon abundance was also species specific. Furthermore, the wasps had relatively few CHCs compared to E. tuberculatum (22–44% of the host components), and these were present in low amounts. Wasps, only partially mimicking the host CHC profile, were immediately recognized as alien and actively removed from the nest by the ants. Hexane-washed wasps were also transported to the refuse piles, but only after being thoroughly inspected and after most of the workers had initially ignored them. Being recognized as intruder may be to the parasitoids’ advantage, allowing them to quickly leave the natal nest, and therefore enhancing the fitness of these very short lived parasitoids. We suggest that eucharitids take advantage of the hygienic behavior of ants to quickly escape from their host nests.

An Effective Method for Protecting the Integrity of Mobile Agent

Abstract. A mobile agent is software which performs an action autonomously and independently as a person or organizations assistance. Mobile agents are used for searching information, retrieval information, filtering, intruder recognition in networks, and so on. One of the important issues of mobile agent is their security. It must consider different security issues in effective and secured usage of mobile agent. One of those issues is the integrity’s protection of mobile agents.In this paper, the advantages and disadvantages of each method, after reviewing the existing methods, is examined. Regarding to this matter that each method has its own advantage or disadvantage, it Seems that by combining these methods and using Agents Attributes one can reach to a better method for protecting the integrity of mobile agents. Therefore, this method is provided in this paper and then is evaluated in terms of existing method. Finally, this method is simulated and its results are the sign of improving the possibility of integrity’s protection of mobile agents.

Testing the adjustable threshold model for intruder recognition on Myrmica ants in the context of a social parasite

Social insect colonies are like fortresses, well protected and rich in shared stored resources. This makes them ideal targets for exploitation by predators, parasites and competitors. Colonies of Myrmica rubra ants are sometimes exploited by the parasitic butterfly Maculinea alcon. Maculinea alcon gains access to the ants' nests by mimicking their cuticular hydrocarbon recognition cues, which allows the parasites to blend in with their host ants. Myrmica rubra may be particularly susceptible to exploitation in this fashion as it has large, polydomous colonies with many queens and a very viscous population structure. We studied the mutual aggressive behaviour of My. rubra colonies based on predictions for recognition effectiveness. Three hypotheses were tested: first, that aggression increases with distance (geographical, genetic and chemical); second, that the more queens present in a colony and therefore the less-related workers within a colony, the less aggressively they will behave; and that colonies facing parasitism will be more aggressive than colonies experiencing less parasite pressure. Our results confirm all these predictions, supporting flexible aggression behaviour in Myrmica ants depending on context.

Discovery and design of carbohydrate-based therapeutics

Importance of the field: Till now, the importance of carbohydrates has been underscored, if compared with the two other major classes of biopolymers such as oligonucleotides and proteins. Recent advances in glycobiology and glycochemistry have imparted a strong interest in the study of this enormous family of biomolecules. Carbohydrates have been shown to be implicated in recognition processes, such as cell–cell adhesion, cell–extracellular matrix adhesion and cell–intruder recognition phenomena. In addition, carbohydrates are recognized as differentiation markers and as antigenic determinants. Due to their relevant biological role, carbohydrates are promising candidates for drug design and disease treatment. However, the growing number of human disorders known as congenital disorders of glycosylation that are being identified as resulting from abnormalities in glycan structures and protein glycosylation strongly indicates that a fast development of glycobiology, glycochemistry and glycomedicine is highly desirable.Areas covered in this review: The topics give an overview of different approaches that have been used to date for the design of carbohydrate-based therapeutics; this includes the use of native synthetic carbohydrates, the use of carbohydrate mimics designed on the basis of their native counterpart, the use of carbohydrates as scaffolds and finally the design of glyco-fused therapeutics, one of the most recent approaches. The review covers mainly literature that has appeared since 2000, except for a few papers cited for historical reasons.What the reader will gain: The reader will gain an overview of the current strategies applied to the design of carbohydrate-based therapeutics; in particular, the advantages/disadvantages of different approaches are highlighted. The topic is presented in a general, basic manner and will hopefully be a useful resource for all readers who are not familiar with it. In addition, in order to stress the potentialities of carbohydrates, several examples of carbohydrate-based marketed therapeutics are given.Take home message: Carbohydrates are a rich class of natural compounds, possessing an intriguing and still not fully understood biological role. This richness offers several strategies for the design of carbohydrate-based therapeutics.

Standing and hovering guards of the stingless bee Tetragonisca angustula complement each other in entrance guarding and intruder recognition

SummaryPrevious research has shown that colonies of the stingless bee Tetragonisca angustula have hovering guards that can detect allospecific intruder bees with volatile odours or different body colour, but conspecific intruders were not detected. Here we show that T. angustula colony entrances are also defended by guards standing on the entrance tube. These standing guards made very few errors in recognition, accepting 100% of the nestmates and rejecting 92% of the conspecific non-nestmates presented to them at the nest entrance. In addition, 87% of the nestmates contaminated with odours from the stingless bee Scaptotrigona bipunctata were rejected. Standing guards also reacted to volatile odours from the stingless bees S. bipunctata and Melipona rufiventris by switching to hovering. The defence reaction, i.e. the increase in the number of hovering guards, was not, however, comparable to the reaction previously reported to citral, the propaganda chemical used by the obligate robber bee Lestrimelitta limao when attacking other bee colonies.

Implication of transglutaminase in mitogen-induced human lymphocyte blast transformation.

Lymphocytes are unique cells evolved to guard, in collaboration with other accessory cells (such as macrophages), the selfness of vertebrate organisms against the invasiveness of alien elements or macromolecules. Recognition of intruders is obtained either by cell-cell or cell-molecule interactions, in which sophisticated biochemical machineries, endowed in the lymphocyte plasma membrane, are set in action as important parts of defence mechanisms used by singles to defend their own individualities. As a consequence of the activity of all these surface molecular devices, a metabolic turmoil is triggered in these cells. Numerous intra- and extra-cellular biochemical signals are released, bringing about in a short time marked modifications of a number of important metabolic pathways such as those related to: 1) energy production; 2) control of electrolyte traffic in the cell; 3) transcription and translation of specific messenger RNA; 4) biosynthesis of tRNA and rRNA; 5) control of DNA replication and cell division1–10.

Olfactory control of aggression in lactating female housemice

Wild female lactating mice were tested for aggression toward strange wild male mice doused with either the test female's own urine (Owns), the urine of other wild females (Novels), or water (Controls). Treatment effects were assessed against an aggression index comprised of 5 different behaviors shown to be related by a factor analysis. Females aggressed more toward Novel-scented opponents than toward either Owns or Controls, the latter 2 conditions failing to differ statistically. It was concluded that an olfactorily-mediated mechanism controls the recognition of intruders by aggressive lactating housemice.