Trust Management for Secure Routing Forwarding Data Using Delay Tolerant Networks

Delay Tolerant Networks (DTNs) have established the connection to source and destination. For example this often faces disconnection and unreliable wireless connections. A delay tolerant network (DTNs) provides a network imposes disruption or delay. The delay tolerant networks operate in limited resources such as memory size, central processing unit. Trust management protocol uses a dynamic threshold updating which overcomes the problems .The dynamic threshold update reduces the false detection probability of the malicious nodes. The system proposes a secure routing management schemes to adopt information security principles successfully. It analyzes the basic security principles and operations for trust authentication which is applicable in delay tolerant networks (DTNs).For security the proposed system identifies the store and forward approach in network communications and analyzes the routing in cases like selfish contact and collaboration contact methods. The proposed method identifies ZRP protocol scheme and it enhances the scheme using methods namely distributed operation, mobility, delay analysis, security association and trust modules. This security scheme analyzes the performance analysis and proposed algorithm based on parameter time, authentication, security, and secure routing. From this analysis, this research work identifies the issues in DTNs secure routing and enhances ZRP (Zone Routing Protocol) by suggesting an authentication principle as a noted security principle for extremely information security concepts

Towards efficacy and efficiency in sparse delay tolerant networks

The ubiquitous adoption of portable smart devices has enabled a new way of communication via Delay Tolerant Networks (DTNs), whereby messages are routed by the personal devices carried by ever-moving people. Although a DTN is a type of Mobile Ad Hoc Network (MANET), traditional MANET solutions are ill-equipped to accommodate message delivery in DTNs due to the dynamic and unpredictable nature of people\u27s movements and their spatio-temporal sparsity. More so, such DTNs are susceptible to catastrophic congestion and are inherently chaotic and arduous. This manuscript proposes approaches to handle message delivery in notably sparse DTNs. First, the ChitChat system [69] employs the social interests of individuals participating in a DTN to accurately model multi-hop relationships and to make opportunistic routing decisions for interest-annotated messages. Second, the ChitChat system is hybridized [70] to consider both social context and geographic information for learning the social semantics of locations so as to identify worthwhile routing opportunities to destinations and areas of interest. Network density analyses of five real-world datasets is conducted to identify sparse datasets on which to conduct simulations, finding that commonly-used datasets in past DTN research are notably dense and well connected, and suggests two rarely used datasets are appropriate for research into sparse DTNs. Finally, the Catora system is proposed to address congestive-driven degradation of service in DTNs by accomplishing two simultaneous tasks: (i) expedite the delivery of higher quality messages by uniquely ordering messages for transfer and delivery, and (ii) avoid congestion through strategic buffer management and message removal. Through dataset-driven simulations, these systems are found to outperform the state-of-the-art, with ChitChat facilitating delivery in sparse DTNs and Catora unencumbered by congestive conditions --Abstract, page iv

A Taxonomy on Misbehaving Nodes in Delay Tolerant Networks

Delay Tolerant Networks (DTNs) are type of Intermittently Connected Networks (ICNs) featured by long delay, intermittent connectivity, asymmetric data rates and high error rates. DTNs have been primarily developed for InterPlanetary Networks (IPNs), however, have shown promising potential in challenged networks i.e. DakNet, ZebraNet, KioskNet and WiderNet. Due to unique nature of intermittent connectivity and long delay, DTNs face challenges in routing, key management, privacy, fragmentation and misbehaving nodes. Here, misbehaving nodes i.e. malicious and selfish nodes launch various attacks including flood, packet drop and fake packets attack, inevitably overuse scarce resources (e.g., buffer and bandwidth) in DTNs. The focus of this survey is on a review of misbehaving node attacks, and detection algorithms. We firstly classify various of attacks depending on the type of misbehaving nodes. Then, detection algorithms for these misbehaving nodes are categorized depending on preventive and detective based features. The panoramic view on misbehaving nodes and detection algorithms are further analyzed, evaluated mathematically through a number of performance metrics. Future directions guiding this topic are also presented

From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web

In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these requirements. We demonstrate a conceptual implementation of OAI-ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for Information Science and Technology (JASIST

Content Centric Mechanisms for Efficient Data Dissemination in Delay Tolerant Networks

Today’s internet was founded as a host centric abstraction for connecting machines over a geographically distributed data base. Since then it has exploded into a trillion dollar industry for providing services and content to the world. For meeting these ever growing consumer demands, internet service providers have used bolt-on approaches to patch the internet. On the other hand, the last decade has witnessed the worst natural disasters on earth which resulted in total or partial destruction of communication infrastructure. Understanding these challenges, researchers are committed to re-architect the internet with clean slate information centric approaches. These future internet architectures have shifted the dynamics from predominately location oriented models to data oriented models. These models provide location independence which eases the network configuration and implementation of network services in mobile environments. In this perspective, this thesis aims to hack content centric abstraction to provide optimized solutions for delay tolerant network scenarios. We provide information aware mechanisms which help to take adequate forwarding and caching decisions in these dynamic and challenged environments. This thesis proposes a unique popularity estimation algorithm and a name based prioritization algorithm for disseminating data more productively in intermittently connected networks. For evaluation it analyses the performance for both mechanisms and compare them with the latest solutions. Furthermore the thesis discusses potential research areas in the field of information centric networking and future directions for this thesis

Are well‐intended Buddhist practices an under‐appreciated threat to global aquatic biodiversity?

Abstract 1. The inherently pro‐conservation and humane Buddhist practice of ‘live release’, entailing the release into the wild of creatures destined for slaughter, poses potentially significant conservation consequences if inappropriate, invasive species are procured for release. 2. This article collates evidence, citing one legal case and other examples, about the risks of the live release of potentially invasive aquatic species that may result in serious, possibly irreversible, conservation threats to aquatic biodiversity and natural ecosystems, with ensuing adverse ecological and human consequences. 3. It is essential that practitioners are aware of these risks if their actions are not to work diametrically against the pro‐conservation and humane intents of the practice. 4. Ensuring that live release occurs safely necessitates raising awareness, with guidance informed by science, to ensure that good intentions do not result in perverse, environmentally destructive outcomes. 5. We propose four simple principles to achieve this, for dissemination to the global adherents of these otherwise entirely laudable practices

Digital provenance - models, systems, and applications

Data provenance refers to the history of creation and manipulation of a data object and is being widely used in various application domains including scientific experiments, grid computing, file and storage system, streaming data etc. However, existing provenance systems operate at a single layer of abstraction (workflow/process/OS) at which they record and store provenance whereas the provenance captured from different layers provide the highest benefit when integrated through a unified provenance framework. To build such a framework, a comprehensive provenance model able to represent the provenance of data objects with various semantics and granularity is the first step. In this thesis, we propose a such a comprehensive provenance model and present an abstract schema of the model. ^ We further explore the secure provenance solutions for distributed systems, namely streaming data, wireless sensor networks (WSNs) and virtualized environments. We design a customizable file provenance system with an application to the provenance infrastructure for virtualized environments. The system supports automatic collection and management of file provenance metadata, characterized by our provenance model. Based on the proposed provenance framework, we devise a mechanism for detecting data exfiltration attack in a file system. We then move to the direction of secure provenance communication in streaming environment and propose two secure provenance schemes focusing on WSNs. The basic provenance scheme is extended in order to detect packet dropping adversaries on the data flow path over a period of time. We also consider the issue of attack recovery and present an extensive incident response and prevention system specifically designed for WSNs

Using law enforcement data in trafficking research

Law enforcement data are a promising and largely untapped resource for academic research into human trafficking. Better use of such data can help inform and expand an evidence-based approach to counter-trafficking policy and practice. Authored by both academics and a senior law enforcement practitioner, this chapter provides rare and important insights into the theoretical, practical, legal and ethical considerations around using law enforcement data in human trafficking research. Its discussions should prove useful to researchers, practitioners and policy-makers interested in understanding and tackling human trafficking more effectively. The chapter begins with a critical appraisal of the human trafficking literature, highlighting particular gaps, imbalances and weaknesses. The stage is then set to explore the utility and applications of a long-neglected but empirically-rich source of data on human trafficking: those that law enforcement agencies generate and/or hold. The limitations of law enforcement data are made explicit and their benefits are explored, with reference to relevant human trafficking studies and innovative research into other crimes. Key considerations are addressed around the actual process of using law enforcement data, drawing on the authors’ experiences as researchers and a research-enabler. This section is informed in particular by four recent human trafficking studies in which the authors were involved, all of which used sensitive and hard-to-access law enforcement data. These innovative studies spanned both small- and large-scale datasets, qualitative, quantitative and mixed-method enquiries, internal and international trafficking movements and some of the main variants of human trafficking: sex trafficking, trafficking for domestic servitude and labour trafficking across diverse licit and illicit labour markets

Digital provenance - models, systems, and applications

Data provenance refers to the history of creation and manipulation of a data object and is being widely used in various application domains including scientific experiments, grid computing, file and storage system, streaming data etc. However, existing provenance systems operate at a single layer of abstraction (workflow/process/OS) at which they record and store provenance whereas the provenance captured from different layers provide the highest benefit when integrated through a unified provenance framework. To build such a framework, a comprehensive provenance model able to represent the provenance of data objects with various semantics and granularity is the first step. In this thesis, we propose a such a comprehensive provenance model and present an abstract schema of the model. ^ We further explore the secure provenance solutions for distributed systems, namely streaming data, wireless sensor networks (WSNs) and virtualized environments. We design a customizable file provenance system with an application to the provenance infrastructure for virtualized environments. The system supports automatic collection and management of file provenance metadata, characterized by our provenance model. Based on the proposed provenance framework, we devise a mechanism for detecting data exfiltration attack in a file system. We then move to the direction of secure provenance communication in streaming environment and propose two secure provenance schemes focusing on WSNs. The basic provenance scheme is extended in order to detect packet dropping adversaries on the data flow path over a period of time. We also consider the issue of attack recovery and present an extensive incident response and prevention system specifically designed for WSNs

Orchestrating product provenance story:When IOTA ecosystem meets electronics supply chain space

"Trustworthy data" is the fuel for ensuring transparent traceability, precise decision-making, and cogent coordination in the supply chain (SC) space. However, the disparate data silos act as a trade barrier in orchestrating the provenance of product story starting from the transformation of raw materials into the circuit board to the assembling of electronic components into end products available on the store shelf for customers. Therefore, to bridge the fragmented siloed information across global supply chain partners, the diffusion of blockchain (BC) as one of the advanced distributed ledger technology (DLT) takeover the on-premise legacy systems. Nevertheless, the challenging constraints of blockchain including scalability, accessing off-line data, fee-less microtransactions and many more lead to the third wave of blockchain called IOTA. In this paper, we propose a framework for supporting provenance in the electronic supply chain (ECS) by using permissioned IOTA ledger. Realizing the crucial requirement of trustworthy data, we use Masked Authenticated Messaging (MAM) channel provided by IOTA that allows the SC players to procure distributed information while keeping confidential trade flows, tamper-proof data, and fine-grained accessibility rights. To identify operational disruption, we devise a transparent product ledger through transaction data and consignment information to keep track of the complete product journey at each intermediary step during SC processes. Furthermore, we evaluate the secure provenance data construction time for varying payload size.Comment: 47 pages, 18 figure