Understanding and Managing Behavioural Risks -The Case of Food Risks Caused by Malpractice in Poultry Production

The probability that actors in economic relationships break rules increases with the profits they thus expect to earn. It decreases with the probability and level of short- and long-term losses resulting from disclosure. It also decreases with the level of social context factors and intrinsic values which shield actors from yielding to economic temptations. This paper assesses the relative merits of various scientific approaches concerned with risks in economic relationships and outlines their contribution to the study of opportunistic rule-breaking. Since the identification of (misdirected) economic incentives faced by firms and individuals represents the starting point for a systematic analysis of opportunism in any field, we also outline a microeconomic approach that systematically provides this crucial information. The approach is applied to the problem of food quality and safety threatened by opportunistic malpractice of food business operators. Its essentials are illustrated through a study which systematically searches for the temptations to break production-related rules in the poultry industries.asymmetric information, control theories, economic misconduct, game theory, moral hazard, principal-agent model, opportunism, protective factors, relational risks, Food Consumption/Nutrition/Food Safety, A13, K32, K42,

Scalable Techniques for Anomaly Detection

Computer networks are constantly being attacked by malicious entities for various reasons. Network based attacks include but are not limited to, Distributed Denial of Service (DDoS), DNS based attacks, Cross-site Scripting (XSS) etc. Such attacks have exploited either the network protocol or the end-host software vulnerabilities for perpetration. Current network traffic analysis techniques employed for detection and/or prevention of these anomalies suffer from significant delay or have only limited scalability because of their huge resource requirements. This dissertation proposes more scalable techniques for network anomaly detection. We propose using DNS analysis for detecting a wide variety of network anomalies. The use of DNS is motivated by the fact that DNS traffic comprises only 2-3% of total network traffic reducing the burden on anomaly detection resources. Our motivation additionally follows from the observation that almost any Internet activity (legitimate or otherwise) is marked by the use of DNS. We propose several techniques for DNS traffic analysis to distinguish anomalous DNS traffic patterns which in turn identify different categories of network attacks. First, we present MiND, a system to detect misdirected DNS packets arising due to poisoned name server records or due to local infections such as caused by worms like DNSChanger. MiND validates misdirected DNS packets using an externally collected database of authoritative name servers for second or third-level domains. We deploy this tool at the edge of a university campus network for evaluation. Secondly, we focus on domain-fluxing botnet detection by exploiting the high entropy inherent in the set of domains used for locating the Command and Control (C&C) server. We apply three metrics namely the Kullback-Leibler divergence, the Jaccard Index, and the Edit distance, to different groups of domain names present in Tier-1 ISP DNS traces obtained from South Asia and South America. Our evaluation successfully detects existing domain-fluxing botnets such as Conficker and also recognizes new botnets. We extend this approach by utilizing DNS failures to improve the latency of detection. Alternatively, we propose a system which uses temporal and entropy-based correlation between successful and failed DNS queries, for fluxing botnet detection. We also present an approach which computes the reputation of domains in a bipartite graph of hosts within a network, and the domains accessed by them. The inference technique utilizes belief propagation, an approximation algorithm for marginal probability estimation. The computation of reputation scores is seeded through a small fraction of domains found in black and white lists. An application of this technique, on an HTTP-proxy dataset from a large enterprise, shows a high detection rate with low false positive rates

Three Decades of Deception Techniques in Active Cyber Defense -- Retrospect and Outlook

Deception techniques have been widely seen as a game changer in cyber defense. In this paper, we review representative techniques in honeypots, honeytokens, and moving target defense, spanning from the late 1980s to the year 2021. Techniques from these three domains complement with each other and may be leveraged to build a holistic deception based defense. However, to the best of our knowledge, there has not been a work that provides a systematic retrospect of these three domains all together and investigates their integrated usage for orchestrated deceptions. Our paper aims to fill this gap. By utilizing a tailored cyber kill chain model which can reflect the current threat landscape and a four-layer deception stack, a two-dimensional taxonomy is developed, based on which the deception techniques are classified. The taxonomy literally answers which phases of a cyber attack campaign the techniques can disrupt and which layers of the deception stack they belong to. Cyber defenders may use the taxonomy as a reference to design an organized and comprehensive deception plan, or to prioritize deception efforts for a budget conscious solution. We also discuss two important points for achieving active and resilient cyber defense, namely deception in depth and deception lifecycle, where several notable proposals are illustrated. Finally, some outlooks on future research directions are presented, including dynamic integration of different deception techniques, quantified deception effects and deception operation cost, hardware-supported deception techniques, as well as techniques developed based on better understanding of the human element.Comment: 19 page

The Beginnings and Prospective Ending of “End-to-End”: An Evolutionary Perspective On the Internet’s Architecture

The technology of “the Internet” is not static. Although its “end-to- end” architecture has made this “connection-less” communications system readily “extensible,” and highly encouraging to innovation both in hardware and software applications, there are strong pressures for engineering changes. Some of these are wanted to support novel transport services (e.g. voice telephony, real-time video); others would address drawbacks that appeared with opening of the Internet to public and commercial traffic - e.g., the difficulties of blocking delivery of offensive content, suppressing malicious actions (e.g. “denial of service” attacks), pricing bandwidth usage to reduce congestion. The expected gains from making “improvements” in the core of the network should be weighed against the loss of the social and economic benefits that derive from the “end-to-end” architectural design. Even where technological “fixes” can be placed at the networks’ edges, the option remains to search for alternative, institutional mechanisms of governing conduct in cyberspace.

Agri-food business: Global challenges â Innovative solutions

The rise of a western-style middle class in many successful emerging economies like China currently is inducing deep structural changes on agricultural world markets and within the global agri-food business. As a result of both higher incomes and concerns over product safety and quality the global demand for high-quality and safe food products is increasing significantly. In order to meet the new required quality, globally minimum quality standards are rising and private standards emerging. All over the world these developments cause adjustments at the enterprise, chain and market levels. At the same time, the tremendously increasing demand for renewable energy has led to the emergence of a highly promising market for biomass production. This has far-reaching consequences for resource allocation in the agri-food business, for the environment, for the poor in developing countries and for agricultural policy reforms. The challenges increase with ongoing liberalisation, globalisation and standardisation, all of which change trade patterns for agricultural and food commodities, and influence production costs and commodity prices. The objective of the IAMO Forum is to show opportunities as well as risks for all participants of the food economy in the ongoing globalisation process: for small peasants in developing countries, farmers in Europe and globally active food enterprises and retailers. The success of enterprises depends on the ability to find innovative solutions with regard to the organisation of enterprises, chains, and markets, as well as future policy design. Concerning bio-energy strategies has to be identified to combat global warming most efficiently and concurrently attenuate the competition between "tank and table" on farmland. IAMO Forum 2008, as well as this book, would not have been possible without the engagement of many people and institutions. We thank the authors of the papers, as well as the referees. Furthermore we are highly indebted to MARLIES LOHR, NADINE GIEMSA and RONNY RECKE who in an outstanding way contributed to the organisation of the Forum. This is true as well for the IAMO administration, whose work we gratefully acknowledge. Many sponsors has funded the IAMO Forum 2008. We are very grateful to the German Research Foundation (DFG), The Federal Ministry of Food, Agriculture and Consumer Production in Germany, The Ministry of Cultural Affairs of the Federal State Saxony-Anhalt, Germany and last but not least the City of Halle. Further Conference sponsors are the BIONADE Corporation, Gaensefurther Mineral Water, The Wine Growers Association of the Region Saale-Unstrut, Germany, Obsthof am SüÃen See GmbH, Monsanto Company, KWS Saat AG, Sachsen-Anhalt-Tours, Baumkuchen Salzwedel and the Hallesches Brauhaus.Agribusiness, Agricultural and Food Policy, Agricultural Finance, Community/Rural/Urban Development, Industrial Organization, Institutional and Behavioral Economics, International Development, Marketing, Political Economy,

Agri-food business: global challenges - innovative solutions

The rise of a western-style middle class in many successful emerging economies like China currently is inducing deep structural changes on agricultural world markets and within the global agri-food business. As a result of both higher incomes and concerns over product safety and quality the global demand for high-quality and safe food products is increasing significantly. In order to meet the new required quality, globally minimum quality standards are rising and private standards emerging. All over the world these developments cause adjustments at the enterprise, chain and market levels. At the same time, the tremendously increasing demand for renewable energy has led to the emergence of a highly promising market for biomass production. This has far-reaching consequences for resource allocation in the agri-food business, for the environment, for the poor in developing countries and for agricultural policy reforms. The challenges increase with ongoing liberalisation, globalisation and standardisation, all of which change trade patterns for agricultural and food commodities, and influence production costs and commodity prices. CONTENTS: Preface... i; On the political economy of food standards ... 1, Johan F. M. Swinnen, Thijs Vandemoortele; An analytical framework for the study of deviant behaviour in production... 11, Norbert Hirschauer, Gaetano Martino; Netchain innovations for sustainable pork supply chains in an EU Context... 22, Rannia Nijhoff-Savvaki, Jacques Trienekens, Onno Omta; Inclusion of dairy farms in supply chain in Bulgaria - Modes, efficiency, perspectives... 35, Hrabrin Bachev; The effective traceability on the example of Polish supply chain ... 47, Agnieszka Bezat, Sebastian Jarzebowski; Geographical indications in transition countries: Governance, vertical integration and territorial impact. Illustration with case studies from Serbia... 58, Marguerite Paus; Processing and marketing feasibility of underutilized fruit species of Rajasthan, India ... 70, Dheeraj Singh, Lobsang Wangshu, V. C. Prahalad; Future impact of new technologies upon food quality and health in Central Eastern European countries... 82, Lajos Zoltán Bakucs, Imre Ferto, Attila Havas; Are food industry companies interested in co-financing collective agricultural marketing?... 95, Anikó Tóth, Csaba Forgács; Farmers' reasons for engaging in bioenergy utilisation and their institutional context: A case study from Germany ... 106, Melf-Hinrich Ehlers; Degree and pattern of agro-food trade integration of South-Eastern European countries with the European Union ... 118, Štefan Bojnec, Imre Ferto; Competitiveness of cotton and wheat production and processing in Central Asia ... 133, Inna Levkovych --

Advances in Grid Computing

This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

Scalable Techniques for Anomaly Detection

Computer networks are constantly being attacked by malicious entities for various reasons. Network based attacks include but are not limited to, Distributed Denial of Service (DDoS), DNS based attacks, Cross-site Scripting (XSS) etc. Such attacks have exploited either the network protocol or the end-host software vulnerabilities for perpetration. Current network traffic analysis techniques employed for detection and/or prevention of these anomalies suffer from significant delay or have only limited scalability because of their huge resource requirements. This dissertation proposes more scalable techniques for network anomaly detection. We propose using DNS analysis for detecting a wide variety of network anomalies. The use of DNS is motivated by the fact that DNS traffic comprises only 2-3% of total network traffic reducing the burden on anomaly detection resources. Our motivation additionally follows from the observation that almost any Internet activity (legitimate or otherwise) is marked by the use of DNS. We propose several techniques for DNS traffic analysis to distinguish anomalous DNS traffic patterns which in turn identify different categories of network attacks. First, we present MiND, a system to detect misdirected DNS packets arising due to poisoned name server records or due to local infections such as caused by worms like DNSChanger. MiND validates misdirected DNS packets using an externally collected database of authoritative name servers for second or third-level domains. We deploy this tool at the edge of a university campus network for evaluation. Secondly, we focus on domain-fluxing botnet detection by exploiting the high entropy inherent in the set of domains used for locating the Command and Control (C&C) server. We apply three metrics namely the Kullback-Leibler divergence, the Jaccard Index, and the Edit distance, to different groups of domain names present in Tier-1 ISP DNS traces obtained from South Asia and South America. Our evaluation successfully detects existing domain-fluxing botnets such as Conficker and also recognizes new botnets. We extend this approach by utilizing DNS failures to improve the latency of detection. Alternatively, we propose a system which uses temporal and entropy-based correlation between successful and failed DNS queries, for fluxing botnet detection. We also present an approach which computes the reputation of domains in a bipartite graph of hosts within a network, and the domains accessed by them. The inference technique utilizes belief propagation, an approximation algorithm for marginal probability estimation. The computation of reputation scores is seeded through a small fraction of domains found in black and white lists. An application of this technique, on an HTTP-proxy dataset from a large enterprise, shows a high detection rate with low false positive rates

Hidden in Plain Sight: A Machine Learning Approach for Detecting Prostitution Activity in Phoenix, Arizona

Prostitution has been a topic of study for decades, yet many questions remain about where prostitution occurs. Difficulty in identifying prostitution activity is often attributed to the hidden and seemingly victimless nature of the crime. Despite numerous challenges associated with policing street prostitution, these encounters become more difficult to identify when they take place indoors, especially in locations away from public view, such as hotels. The purpose of this paper is to develop a strategy for identifying hotel facilities and surrounding areas that may be experiencing elevated levels of prostitution activity using high-volume, user-generated data, namely hotel reviews written by guests and posted to Travelocity.com. A unique synthesis of methods including data mining, natural language processing, machine learning, and basic spatial analysis are combined to identify facilities that may require additional law enforcement resources and/or social/health service outreach. Prostitution hotspots are identified within the city of Phoenix, Arizona and policy implications are discussed