This paper studies methodologically robust options for giving logical contents to nodes in abstract argumentation networks. It defines a variety of notions of attack in terms of the logical contents of the nodes in a network. General properties of logics are refined both in the object level and in the metalevel to suit the needs of the application. The network-based system improves upon some of the attempts in the literature to define attacks in terms of defeasible proofs, (...) the so-called rule-based systems. We also provide a number of examples and consider a rigorous case study, which indicate that our system does not suffer from anomalies. We define consequence relations based on a notion of defeat, consider rationality postulates, and prove that one such consequence relation is consistent. (shrink)

In recent years, the network has become more complex, and the attacker’s ability to attack is gradually increasing. How to properly understand the network security situation and improve network security has become a very important issue. In order to study the method of extracting information about the security situation of the network based on cloud computing, we recommend the technology of knowledge of the network security situation based on the data extraction technology. It converts each (...) received cyber security event into a standard format that can be defined as multiple brochures, creating a general framework for the cyber security situation. According to the large nature of network security situation data, the Hadoop platform is used to extract aggregation rules, and perform model extraction, pattern analysis, and learning on a network security event dataset to complete network security situation rule mining, and establish a framework for assessing the state of network security. According to the results of the federal rule extraction, the level of network node security risk is obtained in combination with signal reliability, signal severity, resource impact, node protection level, and signal recovery factor. A simulation test is performed to obtain the intrusion index according to the source address of the network security alarm. Through the relevant experiments and analysis of the results, the attack characteristics obtained in this study were obtained after manually reducing the network security event in the 295 h window. The results show that after the security event is canceled, the corresponding window attack index decreases to 0, indicating that this method can effectively implement a network security situation awareness. The proposed technique allows you to accurately sense changes in network security conditions. (shrink)

Due to the complexity and versatility of network security alarm data, a cloud-based network security data extraction method is proposed to address the inability to effectively understand the network security situation. The information properties of the situation are generated by creating a set of spatial characteristics classification of network security knowledge, which is then used to analyze and optimize the processing of hybrid network security situation information using cloud computing technology and co-filtering technology. Knowledge and (...) information about the security situation of a hybrid network has been analyzed using cloud computing strategy. The simulation results show that a cyber security crash occurs in window 20, after which the protection index drops to window 500. The increase in the security index of 500 windows is consistent with the effectiveness of the concept of this document method, indicating that this document method can sense changes in the network security situation. Starting from the first attacked window, the defense index began to decrease. In order to simulate the added network defense, the network security events in the 295th time window were reduced in the original data, and the defense index increased significantly in the corresponding time period, which is consistent with the method perception results, which further verifies the effectiveness and reliability of this method on the network security event perception. This method provides high-precision knowledge of network security situations and improves the security and stability of cloud-based networks. (shrink)

We present a computer-supported approach for the logical analysis and conceptual explicitation of argumentative discourse. Computational hermeneutics harnesses recent progresses in automated reasoning for higher-order logics and aims at formalizing natural-language argumentative discourse using flexible combinations of expressive non-classical logics. In doing so, it allows us to render explicit the tacit conceptualizations implicit in argumentative discursive practices. Our approach operates on networks of structured arguments and is iterative and two-layered. At one layer we search for logically correct formalizations for (...) each of the individual arguments. At the next layer we select among those correct formalizations the ones which honor the argument’s dialectic role, i.e. attacking or supporting other arguments as intended. We operate at these two layers in parallel and continuously rate sentences’ formalizations by using, primarily, inferential adequacy criteria. An interpretive, logical theory will thus gradually evolve. This theory is composed of meaning postulates serving as explications for concepts playing a role in the analyzed arguments. Such a recursive, iterative approach to interpretation does justice to the inherent circularity of understanding: the whole is understood compositionally on the basis of its parts, while each part is understood only in the context of the whole. We summarily discuss previous work on exemplary applications of human-in-the-loop computational hermeneutics in metaphysical discourse. We also discuss some of the main challenges involved in fully-automating our approach. By sketching some design ideas and reviewing relevant technologies, we argue for the technological feasibility of a highly-automated computational hermeneutics. (shrink)

The study considers the development of methods for detecting anomalous network connections based on hybridization of computational intelligence methods. An analysis of approaches to detecting anomalies and abuses in computer networks. In the framework of this analysis, a classification of methods for detecting network attacks is proposed. The main results are reduced to the construction of multi-class models that increase the efficiency of the attack detection system, and can be used to build systems for classifying (...) class='Hi'>network parameters during the attack. A model of an artificial immune system based on an evolutionary approach, an algorithm for genetic-competitive learning of the Kohonen network and a method of hierarchical hybridization of binary classifiers with the addition to the detection of anomalous network connections have been developed. The architecture of the network distributed attack detection system has been developed. The architecture of the attack detection system is two-tier: the first level provides the primary analysis of individual packets and network connections using signature analysis, the second level processes the processing of aggregate network data streams using adaptive classifiers. A signature analysis was performed to study network performance based on the Aho-Korasik and Boyer-Moore algorithms and their improved analogues were implemented using OpenMP and CUDA technologies. The architecture is presented and the main points of operation of the network attack generator are shown. A system for generating network attacks has been developed. This system consists of two components: an asynchronous transparent proxy server for TCP sessions and a frontend interface for a network attack generator. The results of the experiments confirmed that the functional and non-functional requirements, as well as the requirements for computing intelligent systems, are met for the developed attack detection system. (shrink)

Security has become one of the important factors for any network communication and transmission of data packets. An organization with an optimal security system can lead to a successful business and can earn huge profit on the business they are doing. Different network devices are linked to route, compute, monitor, and communicate various real-time developments. The hackers are trying to attack the network and want to draw the organization’s significant information for its own profits. During the communication, (...) if an intrusion or eavesdropping occurs, it will lead to a severe disfigurement of the whole communication network, and the data will be controlled by wrong malicious users. Identification of attack is a way to identify the security violations and analyze the measures in a computer network. An identification system, which is effective and accurate, can add security to the existing system for secure and smooth communication among end to end nodes and can work efficiently in the identification of attack on data packets. The role of information security is to design and protect the entire data of networks and maintain its confidentiality, integrity, and availability for their right users. Therefore, there is a need for end to end security management, which will ensure the security and privacy of the network and will save the data inside networks from malicious users. As the network devices are growing, so the level of threats is also increasing for these devices. The proposed research is an endeavor toward the detection of data packets attack by using the rough set theory for a secure end to end communication. The experimental work was performed by the RSES tool. The accuracy of the K-NN was 88% for the total objects of 8459. For cross validation purposes, the decision rules and decomposition tree algorithms were used. The DR algorithm showed accuracy of 59.1%, while the DT showed accuracy of 61.5%. The experimental results of the proposed study show that the research is capable of detecting data packets attack. (shrink)

The computer’s effect on our understanding of causation has been enormous. By the mid‐1980s, philosophical and social‐scientific work on the topic had left us with (1) no reasonable reductive account of causation and (2) a class of statistical causal models tied to linear regression. At this time, computer scientists were attacking the problem of equipping robots with models of the external that included probabilistic portrayals of uncertainty. To solve the problem of efficiently storing such knowledge, they introduced Bayes (...) Networks and directed graphs. By attaching a causal interpretation to Bayes Networks, the philosophy of causation changed dramatically. We are now able to be extremely general about how causal structure connects to data, and systematic about when causal structures are empirically indistinguishable. In this essay I try to motivate and describe this synthesis. (shrink)

This paper identifies two conceptions of security in contemporary concerns over the vulnerability of computers and networks to hostile attack. One is derived from individual-focused conceptions of computer security developed in computer science and engineering. The other is informed by the concerns of national security agencies of government as well as those of corporate intellectual property owners. A comparative evaluation of these two conceptions utilizes the theoretical construct of “securitization,”developed by the Copenhagen School of International Relations.

Given an argumentation network we associate with it a modal formula representing the 'logical content' of the network. We show a one-to-one correspondence between all possible complete Caminada labellings of the network and all possible models of the formula.

In 2005 the author introduced networks which allow attacks on attacks of any level. So if a → b reads a attacks 6, then this attack can itself be attacked by another node c. This attack itself can attack another node d. This situation can be iterated to any level with attacks and nodes attacking other attacks and other nodes. In this paper we provide semantics to such networks. We offer three different approaches to obtaining (...) semantics. 1. The translation approach This uses the methodology of ' Logic by translation'. We translate faithfully the new networks into ordinary Dung networks with more nodes and extract the semantics from the translation. 2. The labelling approach This method regards the arrows as additional entities to be attacked and to mount attacks and applies a variation of the usual machinery of Camindada like labelling to the network. The new concept we need to employ here is that of 'joint attacks'. 3. The logic programming approach We translate the higher level network into a logic program and obtain semantics for it through known semantics for logic programs. We then compare our methods with those of S. Modgil and P. M. Dung et al. (shrink)

This paper provides equational semantics for Dung's argumentation networks. The network nodes get numerical values in [0,1], and are supposed to satisfy certain equations. The solutions to these equations correspond to the ?extensions? of the network. This approach is very general and includes the Caminada labelling as a special case, as well as many other so-called network extensions, support systems, higher level attacks, Boolean networks, dependence on time, and much more. The equational approach has its conceptual (...) roots in the nineteenth century following the algebraic equational approach to logic by George Boole, Louis Couturat, and Ernst Schroeder. (shrink)

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation (...) of the ITS was done by a group of students and teachers. The results were acceptable. (shrink)

The traditional Dung networks depict arguments as atomic and study the relationships of attack between them. This can be generalised in two ways. One is to consider various forms of attack, support, feedback, etc. Another is to add content to nodes and put there not just atomic arguments but more structure, e.g. proofs in some logic or simply just formulas from a richer language. This paper offers to use temporal and modal language formulas to represent arguments in the nodes of (...) a network. The suitable semantics for such networks is Kripke semantics. We also introduce a new key concept of usability of an argument. This is the beginning of a continuing research for adding contents to the nodes of an argumentation network. This research will allow us to address notions like ?what does it exactly mean for a node to attack another? or ?what does it mean for a network to be consistent? or ?can we give proper proof rules to manipulate networks?, and more. (shrink)

In order to correct the deficiencies of intrusion detection technology, the entire computer and network security system are needed to be more perfect. This work proposes an improved k-means algorithm and an improved Apriori algorithm applied in data mining technology to detect network intrusion and security maintenance. The classical KDDCUP99 dataset has been utilized in this work for performing the experimentation with the improved algorithms. The algorithm’s detection rate and false alarm rate are compared with the experimental (...) data before the improvement. The outcomes of proposed algorithms are analyzed in terms of various simulation parameters like average time, false alarm rate, absolute error as well as accuracy value. The results show that the improved algorithm advances the detection efficiency and accuracy using the designed detection model. The improved and tested detection model is then applied to a new intrusion detection system. After intrusion detection experiments, the experimental results show that the proposed system improves detection accuracy and reduces the false alarm rate. A significant improvement of 90.57% can be seen in detecting new attack type intrusion detection using the proposed algorithm. (shrink)

As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables (...) and control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning-based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications. (shrink)

Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...) of opacity in artificial neural networks (ANNs) explodes with the adoption of current Deep Learning techniques [LeCun, Bengio, Hinton, 2015]. In this paper we argue that the explanatory deficit of such techniques represents an important problem, that limits their adoption in the cognitive modelling and computational cognitive science arena. In particular we will show how the current attempts of providing explanations of the deep nets behaviour (see e.g. [Ritter et al. 2017] are not satisfactory. As a possibile way out to this problem, we present two different research strategies. The first strategy aims at dealing with the opacity problem by providing a more abstract interpretation of neural mechanisms and representations. This approach is adopted, for example, by the biologically inspired SPAUN architecture [Eliasmith et al., 2012] and by other proposals suggesting, for example, the interpretation of neural networks in terms of the Conceptual Spaces framework [Gärdenfors 2000, Lieto, Chella and Frixione, 2017]. All such proposals presuppose that the neural level of representation can be considered somehow irrelevant for attacking the problem of explanation [Lieto, Lebiere and Oltramari, 2017]. In our opinion, pursuing this research direction can still preserve the use of deep learning techniques in artificial cognitive models provided that novel and additional results in terms of “transparency” are obtained. The second strategy is somehow at odds with respect to the previous one and tries to address the explanatory issue by avoiding to directly solve the “opacity” problem. In this case, the idea is that one of resorting to pre-compiled plausible explanatory models of the word used in combination with deep-nets (see e.g. [Augello et al. 2017]). We argue that this research agenda, even if does not directly fits the explanatory needs of Computational Cognitive Science, can still be useful to provide results in the area of applied AI aiming at shedding light on the models of interaction between low level and high level tasks (e.g. between perceptual categorization and explanantion) in artificial systems. (shrink)

Bankruptcy of listed companies or shareholders delisting usually causes the crisis spreading in stock markets. Based on the systematic analysis of the epidemic diseases and rumors spreading on the complex networks, the SIR model is introduced to research the crisis spreading in shareholding networks of listed companies and their main holders on the basis of the data about ownership structure in Chinese Stock Markets. The characteristics of shareholding networks are studied, and the parameters for the SIR model are obtained by (...) empirical approach. Then, the numerical computation method is successfully used to analyze the crisis spreading in the networks when the networks meet random failures or intentional attacks. We find the networks have good robustness against the random failures. However, the crisis will spread at a high speed and cause catastrophic damage if there are some failures or attacks on hub vertices in the networks. Under this condition, the networks show obvious vulnerability. Last but not least, the controllability of the networks under the condition of intentional attacks and random failures is studied. The results show that if the network is controlled globally, it is more reliable to allow a politically good new or an appropriate exciting economical policy to play the role in orienting markets under the control of public opinions as the crisis occurs. However, under normal circumstances, controlling a small part of driver vertices representing listed companies, applying appropriate control strategies, and using its characteristics of high efficiency of sending information can effectively control the stock market. Our research provides a new reference to further exploration about the transmission mechanism of the crisis based SIR model and further research on the controllability of crisis spreading in financial markets. (shrink)

This paper studies general numerical networks with support and attack. Our starting point is argumentation networks with the Caminada labelling of three values 1=in, 0=out and ½=undecided. This is generalised to arbitrary values in [01], which enables us to compare with other numerical networks such as predator?prey ecological networks, flow networks, logical modal networks and more. This new point of view allows us to see the place of argumentation networks in the overall landscape of networks and import and export ideas (...) to and from argumentation networks. We make a special effort to make clear how general concepts in general networks relate to the special case of argumentation networks. We pay special attention to the handling of loops and to the special features of numerical support. We find surprising connections with the Dempster?Shafer rule and with the cross-ratio in projective geometry. This paper is an expansion of our 2005 paper and so we also consider higher level features such as numerical attacks on attacks, and propagation of numerical values.We conclude with a brief view of temporal numerical argumentation and with a detailed comparison with related papers published since 2005. (shrink)

In recent years, while extensive researches on various networks properties have been proposed and accomplished, little has been proposed and done on network robustness and node vulnerability assessment under cascades in directed large-scale online community networks. In essential, an online directed social network is a group-centered and information spread-dominated online platform which is very different from the traditional undirected social network. Some further research studies have indicated that the online social network has high robustness to random (...) removals of nodes but fails to the intentional attacks, particularly to those attacks based on node betweenness or node directed coefficient. To explore on the robustness of directed social network, in this article, we have proposed two novel node centralities of ITG and I M p v. These two new centrality models are designed to capture this cascading effect in directed online social networks. Furthermore, we also propose a new and highly efficient computing method based on iterations for I M p v. Then, with the abundant experiments on the synthetic signed network and real-life networks derived from directed online social media and directed human mobile phone calling network, it has been proved that our ITG and I M p v based on directed social network robustness and node vulnerability assessment method is more accurate, efficient, and faster than several traditional centrality methods such as degree and betweenness. And we also have proposed the solid reasoning and proof process of iteration times k in computation of I M p v. To the best knowledge of us, our research has drawn some new light on the leading edge of robustness on the directed social network. (shrink)

Network theory is necessary for the realization of cognitive representations and resulting empirical observations of social groups. We propose that the triadic primitives denoting individual roles are multilayer, with positive and negative relations feeding into cost–benefit calculations. Through this, we advance a computational theory that generalizes to different scales and to contexts where conflict is not present.

Biometrics readers are deployed in many public sites and are used for user identification and verification. Nowadays, most biometrics readers can be connected to local area networks, and consequently, they are potential targets for network attacks. This article investigates the robustness of several fingerprint and iris readers against common denial of service attacks. This investigation has been conducted using a set of laboratory experiments and DoS attack generator tools. The experiments show clearly that the tested biometric readers (...) are very vulnerable to common DoS attacks, and their recognition performances deteriorate significantly once they are under DoS attacks. Finally, the article lists some security consideration that should be taken into consideration when designing secure biometrics readers. (shrink)

Education ecology is a new crossover research field in network age. Its research content can be either microscopic classroom teaching or macro educational ecology research on teaching and culture. The university music classroom is a special kind of ecology. The reason why this is special is that compared to natural ecology, the classroom ecology of university music has a unique relationship between the environment and the subject. The classroom is ecological and becomes the logical prerequisite for ecological research in (...) the classroom. In the Internet age, as the most advanced teaching medium, it has become the need for the development of the new era. The Internet era has broadened the channels and scope of people's access to information and greatly enriched the information resources. The design of teacher's music teaching should have sustainable development. It is no longer a pursuit of only the answer. It must consider the students' multiple ways of learning and must leave room for students to practice independently. Guides help students continue to explore musical arts. This article mainly conveys the innovation of the traditional teaching “learning” and “learning” dichotomy to form an interactive and harmonious classroom ecosystem. The interaction between various factors has handled according to the principles of educational ecology, combined with the development of network technology and Cultivate students' enthusiasm for learning, self-study ability and practical ability, to improve the effectiveness of university music teaching. (shrink)

This aricle discusses the similarity between the propagation of pathogens (viruses and worms) on computer networks and the proliferation of pathogens in cellular organisms (organisms with genetic material contained within a membrane-encased nucleus). It introduces several biological mechanisms which are used in these organisms to protect against such pathogens and presents security models for networked computers inspired by several biological paradigms, including genomics (RNA interference), proteomics (pathway mapping), and physiology (immune system). In addition, the study of epidemiological models for (...) disease control can inspire methods for controlling the spread of pathogens across multiple nodes of a network. It also presents results based on the authors’ research in immune system modeling. (shrink)

Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper - even (...) if you do not have a general background on networking - you will be able to manage your own network and be able to distribute and control your ip. (shrink)

In Belnap's useful 4-valued logic, the set 2 = {T, F} of classical truth values is generalized to the set 4 = ������(2) = {Ø, {T}, {F}, {T, F}}. In the present paper, we argue in favor of extending this process to the set 16 = ᵍ (4) (and beyond). It turns out that this generalization is well-motivated and leads from the bilattice FOUR₂ with an information and a truth-and-falsity ordering to another algebraic structure, namely the trilattice SIXTEEN₃ with an (...) information ordering together with a truth ordering and a (distinct) falsity ordering. Interestingly, the logics generated separately by the algebraic operations under the truth order and under the falsity order in SIXTEEN₃ coincide with the logic of FOUR₂, namely first degree entailment. This observation may be taken as a further indication of the significance of first degree entailment. In the present setting, however, it becomes rather natural to consider also logical systems in the language obtained by combining the vocabulary of the logic of the truth order and the falsity order. We semantically define the logics of the two orderings in the extended language and in both cases axiomatize a certain fragment comprising three unary operations: a negation, an involution, and their combination. We also suggest two other definitions of logics in the full language, including a bi-consequence system. In other words, in addition to presenting first degree entailment as a useful 16-valued logic, we define further useful 16-valued logics for reasoning about truth and (non-)falsity. We expect these logics to be an interesting and useful instrument in information processing, especially when we deal with a net of hierarchically interconnected computers. We also briefly discuss Arieli's and Avron's notion of a logical bilattice and state a number of open problems for future research. (shrink)

A great deal of attention has been paid in recent years to the legality of the actions of states and state agents in international and non-international cyber conflicts. Less attention has been paid to ethical considerations in these situations, and very little has been written regarding the ethics of the participation of non-state actors in such conflicts. In this article, I analyze different categories of non-state participation in cyber operations and undertake to show under what conditions such actions, though illegal, (...) might be morally defensible. (shrink)

Today’s computer network technologies are sociologically founded on hunter-gatherer principles; common users may be possible subjects of surveillance and sophisticated internet-based attacks are almost impossible to prevent. At the same time, information and communication technology, ICT offers the technical possibility of embedded privacy protection. Making technology legitimate by design is a part of the intentional design for democracy. This means incorporating options for socially acceptable behaviour in technical systems, and making the basic principles of privacy protection, rights (...) and responsibilities, transparent to the user. The current global e-polis already has, by means of different technologies, de facto built-in policies that define the level of user-privacy protection. That which remains is to make their ethical implications explicit and understandable to citizens of the global village through interdisciplinary disclosive ethical methods, and to make them correspond to the high ethical norms that support trust, the essential precondition of any socialization. The good news is that research along these lines is already in progress. Hopefully, this will result in a future standard approach to the privacy of network communications. (shrink)

This book deals with the major ethical and social implications of computer networking and its technological development. In this book, a number of leading thinkers--philosophers, computer scientists and researchers--address some fundamental questions posed by the new technology.

This text presents the research field of natural/unconventional computing as it appears in the book COMPUTING NATURE. The articles discussed consist a selection of works from the Symposium on Natural Computing at AISB-IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. The COMPUTING NATURE is about nature considered as the totality of physical existence, the universe. (...) By physical we mean all phenomena, objects and processes, that are possible to detect either directly by our senses or via instruments. Historically, there have been many ways of describing the universe (cosmic egg, cosmic tree, theistic universe, mechanistic universe) while a particularly prominent contemporary approach is computational universe, as discussed in this article. See more: http://arxiv.org/abs/1210.7784. (shrink)

Role-based database management systems are most widely used for information storage and analysis but are known as vulnerable to insider attacks. The core of intrusion detection lies in an adaptive system, where an insider attack can be judged if it is different from the predicted role by performing classification on the user’s queries accessing the database and comparing it with the authorized role. In order to handle the high similarity of user queries for misclassified roles, this paper proposes a (...) deep metric neural network with strategic sampling algorithm that properly extracts salient features and directly learns a quantitative measure of similarity. A strategic sampling method of heuristically generating and learning training pairs through Monte Carlo search is proposed to select a training pair that can represent the entire dataset. With the TPC-E–based benchmark data trained with 11,000 queries for 11 roles, the proposed model produces the classification accuracy of 95.41%, which is the highest compared with the previous models. The results are verified through comparison of quantitative and qualitative evaluations, and the feature space modelled in the neural network is analysed by t-SNE algorithm. (shrink)

Various algorithms have been proposed for learning (partial) genetic regulatory networks through systematic measurements of differential expression in wild type versus strains in which expression of specific genes has been suppressed or enhanced, as well as for determining the most informative next experiment in a sequence. While the behavior of these algorithms has been investigated for toy examples, the full computational complexity of the problem has not received sufficient attention. We show that finding the true regulatory network requires (in (...) the worst-case) exponentially many experiments (in the number of genes). Perhaps more importantly, we provide an algorithm for determining the set of regulatory networks consistent with the observed data. We then show that this algorithm is infeasible for realistic data (specifically, nine genes and ten experiments). This infeasibility is not due to an algorithmic flaw, but rather to the fact that there are far too many networks consistent with the data (10 18 in the provided example). We conclude that gene perturbation experiments are useful in confirming regulatory network models discovered by other techniques, but not a feasible search strategy. (shrink)

In this wide-ranging conversation, Berry and Galloway explore the implications of undertaking media theoretical work for critiquing the digital in a time when networks proliferate and, as Galloway claims, we need to ‘forget Deleuze’. Through the lens of Galloway’s new book, Laruelle: Against the Digital, the potential of a ‘non-philosophy’ for media is probed. From the import of the allegorical method from excommunication to the question of networks, they discuss Galloway’s recent work and reflect on the implications of computation for (...) media theory, thinking about media objects, and critical theory. (shrink)

The connected and acyclic components contained in a network are identified by the computation of its complexity, where complexity of a network refers to the total number of spanning trees present within. The article in hand deals with the enumeration of the complexity of various networks’ operations such as sum, product, difference K 2, n ⊖ K 2, and the conjunction of S n with K 2. All our computations have been concluded by implementation of the methods of (...) linear algebra and matrix theory. Our derivations will also be highlighted with the assistance of 3D plots at the end of this article. (shrink)

I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend
the following theses. (1) Many neural networks compute—they perform computations. (2) Some neural networks compute in a classical way.
Ordinary digital computers, which are very large networks of logic gates, belong in this class of neural networks. (3) Other neural networks
compute in a non-classical way. (4) Yet other neural networks do not perform computations. Brains may well fall into this last class.

A basic deep neural network (DNN) is trained to exhibit a large set of input–output dispositions. While being a good model of the way humans perform some tasks automatically, without deliberative reasoning, more is needed to approach human‐like artificial intelligence. Analysing recent additions brings to light a distinction between two fundamentally different styles of computation: content‐specific and non‐content‐specific computation (as first defined here). For example, deep episodic RL networks draw on both. So does human conceptual reasoning. Combining the two (...) takes advantage of the complementary costs and benefits of each. It also offers a better model of human cognitive competence. (shrink)

The title of this book was inspired by a passage in Charles Sherrington's Man on his Nature.

A graph’s entropy is a functional one, based on both the graph itself and the distribution of probability on its vertex set. In the theory of information, graph entropy has its origins. Hex-derived networks have a variety of important applications in medication store, hardware, and system administration. In this article, we discuss hex-derived network of type 1 and 2, written as HDN 1 n and HDN 2 n, respectively of order n. We also compute some degree-based entropies such as (...) Randić, ABC, and G A entropy of HDN 1 n and HDN 2 n. (shrink)

We study human performance in two classical NP‐hard optimization problems: Set Cover and Maximum Coverage. We suggest that Set Cover and Max Coverage are related to means selection problems that arise in human problem‐solving and in pursuing multiple goals: The relationship between goals and means is expressed as a bipartite graph where edges between means and goals indicate which means can be used to achieve which goals. While these problems are believed to be computationally intractable in general, they become more (...) tractable when the structure of the network resembles a tree. Thus, our main prediction is that people should perform better with goal systems that are more tree‐like. We report three behavioral experiments which confirm this prediction. Our results suggest that combinatorial parameters that are instrumental to algorithm design can also be useful for understanding when and why people struggle to choose between multiple means to achieve multiple goals. (shrink)

Fluid neural networks can be used as a theoretical framework for a wide range of complex systems as social insects. In this article we show that collective logical gates can be built in such a way that complex computation can be possible by means of the interplay between local interactions and the collective creation of a global field. This is exemplified by a NOR gate. Some general implications for ant societies are outlined. ©.