Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

A vision for attaining food security

Food is fundamental to human wellbeing and development. Increased food production remains a cornerstone strategy in the effort to alleviate global food insecurity. But despite the fact that global food production over the past half century has kept ahead of demand, today around one billion people do not have enough to eat, and a further billion lack adequate nutrition. Food insecurity is facing mounting supply-side and demand-side pressures; key among these are climate change, urbanisation, globalisation, population increases, disease, as well as a number of other factors that are changing patterns of food consumption. Many of the challenges to equitable food access are concentrated in developing countries where environmental pressures including climate change, population growth and other socio-economic issues are concentrated. Together these factors impede people's access to sufficient, nutritious food; chiefly through affecting livelihoods, income and food prices. Food security and human development go hand in hand, and their outcomes are co-determined to a significant degree. The challenge of food security is multi-scalar and cross-sector in nature. Addressing it will require the work of diverse actors to bring sustained improvements inhuman development and to reduce pressure on the environment. Unless there is investment in future food systems that are similarly cross-level, cross-scale and cross-sector, sustained improvements in human wellbeing together with reduced environmental risks and scarcities will not be achieved. This paper reviews current thinking, and outlines these challenges. It suggests that essential elements in a successfully adaptive and proactive food system include: learning through connectivity between scales to local experience and technologies high levels of interaction between diverse actors and sectors ranging from primary producers to retailers and consumers, and use of frontier technologies.

Committing to quality learning through adaptive online assessment

With advances in computer-based technologies and the emergence of e-learning, there are unprecedented opportunities to reconsider assessment of learning (and, axiomatically, of teaching) and how this can be undertaken. One approach is adaptive assessment. Although it has existed in the tertiary environment since the time of the oral examination, advanced technologies allow much fuller exploitation of the possibilities inherent in a dynamic system of testing that responds to the user. Having described the characteristics of adaptive assessment, this paper considers how it can achieve significant pedagogical aims within the sector. The paper differentiates between adaptive assessment to assist learning and adaptive assessment to assess achievement. How adaptive assessment can be put in place and salient issues, such as security and system integrity, when such assessment is used for credit, are then discussed. The paper concludes that the capability exists but it has yet to be exploited within higher education as a viable approach to assessment and as a contributor to quality learning.

Editorial : advances in network and system security

Current parallel and distributed networks/systems are facing serious threats from network terrorism and crime, which cause huge financial loss and potential life hazard. As attacking tools are becoming more widely available, more easy-to-use, more sophisticated, and more powerful, more efforts have been made in building more effective, more intelligent, and more adaptive defense systems which are of distributed and networked nature. This special issue focuses on issues related to Network and System Security, such as authentication, access control, availability, integrity, privacy, confidentiality, dependability and sustainability of computer networks and systems.

Certificate-based signature : security model and efficient construction

In Eurocrypt 2003, Gentry introduced the notion of certificate-based encryption. The merit of certificate-based encryption lies in the following features: (1) providing more efficient public-key infrastructure (PKI) that requires less infrastructure, (2) solving the certificate revocation problem, and (3) eliminating third-party queries in the traditional PKI. In addition, it also solves the inherent key escrow problem in the identity-based cryptography. In this paper, we first introduce a new attack called the “Key Replacement Attack” in the certificate-based system and refine the security model of certificate-based signature. We show that the certificate-based signature scheme presented by Kang, Park and Hahn in CT-RSA 2004 is insecure against key replacement attacks. We then propose a new certificate-based signature scheme, which is shown to be existentially unforgeable against adaptive chosen message attacks under the computational Diffie-Hellman assumption in the random oracle model. Compared with the certificate-based signature scheme in CT-RSA 2004, our scheme enjoys shorter signature length and less operation cost, and hence, our scheme outperforms the existing schemes in the literature.

Paradigm shift to enhanced water supply planning through augmented grids, scarcity pricing and adaptive factory water : a system dynamics approach

This paper details a system dynamics model developed to simulate proposed changes to water governance through the integration of supply, demand and asset management processes. To effectively accomplish this, interconnected feedback loops in tariff structures, demand levels and financing capacity are included in the model design, representing the first comprehensive life-cycle modelling of potable water systems. A number of scenarios were applied to Australia's populated South-east Queensland region, demonstrating that introducing temporary drought pricing (i.e. progressive water prices set inverse with availability), in conjunction with supply augmentation through rain-independent sources, is capable of efficiently providing water security in the future. Modelling demonstrated that this alternative tariff structure reduced demand in scarcity periods thereby preserving supply, whilst revenues are maintained to build new water supply infrastructure. In addition to exploring alternative tariffs, the potential benefits of using adaptive pressure-retarded osmosis desalination plants for both potable water and power generation was explored. This operation of these plants for power production, when they would otherwise be idle, shows promise in reducing their net energy and carbon footprints. Stakeholders in industry, government and academia were engaged in model development and validation. The constructed model displays how water resource systems can be reorganised to cope with systemic change and uncertainty.

Adaptive device with underlying mechanism defined by a programming language

An adaptive device is made up of an underlying mechanism, for instance, an automaton, a grammar, a decision tree, etc., to which is added an adaptive mechanism, responsible for allowing a dynamic modification in the structure of the underlying mechanism. This article aims to investigate if a programming language can be used as an underlying mechanism of an adaptive device, resulting in an adaptive language.

Multi-Camera very wide baseline feature matching based on view-adaptive junction detection

This paper presents a strategy for solving the feature matching problem in calibrated very wide-baseline camera settings. In this kind of settings, perspective distortion, depth discontinuities and occlusion represent enormous challenges. The proposed strategy addresses them by using geometrical information, specifically by exploiting epipolar-constraints. As a result it provides a sparse number of reliable feature points for which 3D position is accurately recovered. Special features known as junctions are used for robust matching. In particular, a strategy for refinement of junction end-point matching is proposed which enhances usual junction-based approaches. This allows to compute cross-correlation between perfectly aligned plane patches in both images, thus yielding better matching results. Evaluation of experimental results proves the effectiveness of the proposed algorithm in very wide-baseline environments.

Why Belgium Needs a Special Operations Command. Security Policy Brief No. 70, April 2016

The setting up of a Special Operations Command (SOCOM) constitutes a key element of the ongoing Belgian defence reforms. This Policy Brief aims to put the present demand for special operations forces in its historical context and engage in the discussion on how to structure and employ this special instrument of policy. Building on the legacy of the paracommando regiment, the future Belgian SOCOM constitutes a critical capability within an adaptive force structure. This new entity must be able to deliver results in a variety of unconventional missions that require high readiness, intellectual flexibility and maximum discretion or surprise. At the same time, special operations forces do not constitute a substitute for having a comprehensive security policy. They function best when used as force multipliers alongside other instruments of power towards joint effect. As the proverbial tip of the spear, they must lead the way for Belgian defence regeneration in general.

Real leadership and the U.S. Army : overcoming a failure of imagination to conduct adaptive work /

This monograph begins with a case study that provides a means for analyzing the complexity of organizational leadership in the contemporary security environment. As such, it presents a high stakes problem-set that required an operational adaptation by a cavalry squadron conducting combat operations in Baghdad. This problematic reality triggered the struggle to find a creative response to a very deadly problem, while cultural norms served as barriers that prevented the rejection of previously accepted solutions that had proven successful in the past, even though those successful solutions no longer fit in the context of the reality of the present. The case study highlights leaders who were constrained by deeply-held assumptions that inhibited their ability to adapt quickly to a changed environment. The case study then moves on to provide an example of a successful application of adaptive leadership and adaptive work that was performed by the organization after a period of reflection and the willingness to experiment and assume risk. The case study serves as a microcosm of the challenges facing the U.S. Army, and the corresponding leadership framework presented in this monograph can be used as a model for the Army as it attempts to move forward in its effort to make adaptation an institutional imperative. The paper presents a more holistic approach to leadership where the leader transcends that of simply being an authority figure and becomes a real leader who provides a safe and creative learning environment where the organization can tackle and solve adaptive challenges. The paper concludes by recommending that U.S. Army leaders apply Harvard Professor Dean Williams's theory to the challenges confronting the Army's leader development process thereby fostering a culture of adaptive leaders.

Adaptive sending rate over wireless mesh networks using SNR

Wireless Mesh Networks (WMNs) have emerged as a key technology for the next generation of wireless networking. Instead of being another type of ad-hoc networking, WMNs diversify the capabilities of ad-hoc networks. Several protocols that work over WMNs include IEEE 802.11a/b/g, 802.15, 802.16 and LTE-Advanced. To bring about a high throughput under varying conditions, these protocols have to adapt their transmission rate. This paper proposes a scheme to improve channel conditions by performing rate adaptation along with multiple packet transmission using packet loss and physical layer condition. Dynamic monitoring, multiple packet transmission and adaptation to changes in channel quality by adjusting the packet transmission rates according to certain optimization criteria provided greater throughput. The key feature of the proposed method is the combination of the following two factors: 1) detection of intrinsic channel conditions by measuring the fluctuation of noise to signal ratio via the standard deviation, and 2) the detection of packet loss induced through congestion. The authors show that the use of such techniques in a WMN can significantly improve performance in terms of the packet sending rate. The effectiveness of the proposed method was demonstrated in a simulated wireless network testbed via packet-level simulation.

Development of local homeland security networks in the state of Florida: A social network analysis approach

How do local homeland security organizations respond to catastrophic events such as hurricanes and acts of terrorism? Among the most important aspects of this response are these organizations ability to adapt to the uncertain nature of these "focusing events" (Birkland 1997). They are often behind the curve, seeing response as a linear process, when in fact it is a complex, multifaceted process that requires understanding the interactions between the fiscal pressures facing local governments, the institutional pressures of working within a new regulatory framework and the political pressures of bringing together different levels of government with different perspectives and agendas. ^ This dissertation has focused on tracing the factors affecting the individuals and institutions planning, preparing, responding and recovering from natural and man-made disasters. Using social network analysis, my study analyzes the interactions between the individuals and institutions that respond to these "focusing events." In practice, it is the combination of budgetary, institutional, and political pressures or constraints interacting with each other which resembles a Complex Adaptive System (CAS). ^ To investigate this system, my study evaluates the evolution of two separate sets of organizations composed of first responders (Fire Chiefs, Emergency Management Coordinators) and community volunteers organized in the state of Florida over the last fifteen years. Using a social network analysis approach, my dissertation analyzes the interactions between Citizen Corps Councils (CCCs) and Community Emergency Response Teams (CERTs) in the state of Florida from 1996–2011. It is the pattern of interconnections that occur over time that are the focus of this study. ^ The social network analysis revealed an increase in the amount and density of connections between these organizations over the last fifteen years. The analysis also exposed the underlying patterns in these connections; that as the networks became more complex they also became more decentralized though not in any uniform manner. The present study brings to light a story of how communities have adapted to the ever changing circumstances that are sine qua non of natural and man-made disasters.^