Data Transfer Phase Research Articles

A governance framework for facilitating cross-agency data sharing

Linking data across local authorities and health boards has the potential to reduce inequalities and improve outcomes. However, cross-agency data sharing leads to complexities around data ownership, legal conditions for processing, organisational controls and risk assessments to ensure privacy and confidentiality of subjects whilst facilitating research and service improvements. We share a governance framework for cross-agency data sharing between a local authority and regional health board in Scotland. A cross-sector Child Neglect working group was established with representation from public sector agencies, the NHS, University researchers and a Trusted Research Environment to support research on children’s mental health prescribing and secondary specialist services provision and linking to the Aberdeen City Council Child Protection Register. Lessons learned were captured throughout the governance, data transfer and data linkage phases. Communication is the most important driver, with key individuals, deputies and routes of escalation agreed and involved throughout for clarity of roles and expectation setting. Key lessons learned include requiring input from all parties at the project initiation stage, particularly IG teams, including agreements on necessary templates. Knowledge exchange is required between the research team, data owners and data processors to ensure research protocol requirements are correctly understood and data transfer is supported. If possible, internal and/or external validation of data should also be performed before data is linked. Cross-agency data sharing is a vital means to understanding and improving outcomes for individuals and populations. Critical to this is establishing an action plan and formalised project process to achieve outcomes.

Kalman filtering and sine arithmetic optimization algorithm (KSAOA) for wireless sensor network clustering

Hierarchical routing is a crucial approach for enhancing the energy efficiency of Wireless Sensor Networks (WSN). The selection of sensor clusters poses a Non-deterministic Polynomial (NP) problem, typically addressed using meta-heuristic algorithms. However, existing research has not adequately considered the observation error of node energy and the limited convergence performance of their meta-heuristic algorithms. To address these challenges, we proposes a novel approach called KSAOA (Kalman filtering and Sine Arithmetic Optimization Algorithm) for WSN clustering, aimed at prolonging the service lifetime and enhancing the network balance of WSN. The proposed model combines Kalman filtering for estimating node energy and the Sine Arithmetic Optimization Algorithm (SAOA) for clustering nodes. SAOA builds upon the Arithmetic Optimization algorithm (AOA) by introducing a sine factor to extend the exploration boundary and a levy flight strategy to improve local exploration. Additionally, greedy algorithms are employed in the data transfer phase to enhance operational efficiency. The experimental results demonstrate the effectiveness of the proposed method in tabular and graphical form. The results are analyzed through comparative experiments to show that the proposed strategy is effective in improving the balance of network lifetime and network energy consumption.

A lightweight authentication and management method for Internet of Things

Internet of Things (IoT) devices are vulnerable due to their limited resources and inadequate security mechanisms. The number of IoT devices has increased day by day, so the number of devices that are connected to the Internet has also increased. Devices may be deployed anywhere and made available to anyone, making the management of numerous devices problematic. Device management is crucial, as the compromise of IoT devices might cause serious consequences and already there are examples of such a compromise caused widespread DDoS attacks. This paper aims to propose a mechanism that ensures the security of IoT devices and presents a management model and lightweight authentication mechanism simultaneously. The proposed mechanism is novel, computationally lightweight, financially low-cost, remotely usable, and requires no special hardware. This mechanism includes a key management phase to generate ephemeral keys for every session and a trivial and cost-efficient data transfer phase. The proposed mechanism provides an IoT device management model to achieve a scalable IoT environment. Data is transferred cost-effectively via XORs and hash functions. The security of the authentication mechanism is formally verified using AVISPA model checker.

Enhancing Cloud Forensic Investigation System in Distributed Cloud Computing Using DK-CP-ECC Algorithm and EK-ANFIS

The investigation as well as recovery of data gathered as of digital devices associated with computer crime is involved in Digital Forensics (DF). In a distributed Cloud Server (CS), DF investigation is more complicated (during collecting, preserving, and reporting the evidence) as well as insecure during gathering evidence as of the cloud sources. Centered on the DF investigation system, numerous works were performed. However, lots of challenges still remain that bring about cybercrime. The work developed a robust cloud forensic investigation system centered upon distributed Cloud Computing (CC) for conquering the challenges. It is framed into the ‘3’ phase (i.e.) originally, Group Key Generation (GKG) phase that enables the authorized user to upload or download the evidence for maintaining the evidence’s trustworthiness. Distributed Key Cipher Policy Elliptic Curve Cryptography (DK-CP-ECC) algorithm performed the Secure Data Transfer (SDT) phase. It aids in maintaining the evidence’s privacy together with confidentiality. Exponential Membership Function Adaptive Neuro-Fuzzy Interference System (EK-ANFIS) carries out the CS selection with the aid of a deer hunting genetic algorithm that evades the reporting issues and renders secure evidence storage. 97% Security Level (SL) is obtained by the proposed work that is better analogized to the prevailing frameworks.

A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks

The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios.

Fast and Efficient Security Scheme for Blockchain-Based IoT Networks

Internet of Things (IoT) has become widely used nowadays and tremendous increase in the number of users raises its security requirements as well. The constraints on resources such as low computational capabilities and power requirements demand lightweight cryptosystems. Conventional algorithms are not applicable in IoT network communications because of the constraints mentioned above. In this work, a novel and efficient scheme for providing security in IoT applications is introduced. The scheme proposes how security can be enhanced in a distributed IoT application by providing multilevel protection and dynamic key generation in the data uploading and transfer phases. Existing works rely on a single key for communication between sensing device and the attached gateway node. In proposed scheme, this session key is updated after each session and this is done by applying principles of cellular automata. The proposed system provides multilevel security by using incomparable benefits of blockchain, dynamic key and random number generation based on cellular automata. The same was implemented and tested with the widely known security protocol verification tool called Automated Validation of Internet Security Protocols and Applications (AVISPA). Results show that the scheme is secure against various attacks. The proposed scheme has been compared with related schemes and the result analysis shows that the new scheme is fast and efficient also.

A hierarchical secure data aggregation method using the dragonfly algorithm in wireless sensor networks

A wireless sensor network (WSN) consists of a set of sensor nodes that are widely scattered in inaccessible areas. When deployed in large areas, WSNs generate a large volume of the data. Therefore, efficient methods are needed to process the data. One solution to minimize traffic on large-scale wireless sensor networks is to use data aggregation schemes. In this paper, a secure data aggregation method is proposed. The proposed secure data aggregation scheme has three phases: intra-cluster data aggregation, inter-cluster data aggregation, and data transfer. In the intra-cluster data aggregation phase, a fuzzy scheduling system is designed to adjust the appropriate data transmission rates of the cluster member nodes. In the inter-cluster data aggregation phase, an aggregation tree is created between the cluster head nodes. The dragonfly algorithm (DA) is used to find the optimal aggregation tree between cluster head nodes. In the data transfer phase, the columnar transposition cipher method is used to establish a secure connection between cluster member nodes and their cluster head node. Also, a symmetric and lightweight encryption method based on the residue number system (RNS) is utilized to provide secure communications between the cluster head nodes. We modify RNS and call it RNS+. Finally, the simulation results of the proposed scheme are compared to three data aggregation methods including Sign-share, Sham-share, and RCDA. The results show that the proposed data aggregation scheme outperforms other data aggregation methods in terms of network lifetime, delay and packet delivery rate.

An Anti-Gray Hole Attack Scheme in Mobile Ad Hoc Network

Dynamic variation of network topology in mobile ad hoc networks (MANET) forces network nodes to work together and rely on each other for routing. Considering the lack of a central control node, some nodes appear maliciously and selectively drop the data packets instead of transmitting to the next hop node, which is known as the gray hole attack. In order to prevent and identify the gray hole attack, an intrusion detection system (IDS) is proposed on nodes to maintain network efficiency. In addition to establishing security, the proposed anti gray hole attack mechanism extracts abnormal differences between routing packets in the route discovery phase of the ad hoc on-demand distance vector (AODV) routing protocol. It then assigns a suspicious value to each participating node and monitors the exchange of data packets between neighboring nodes in the data transfer phase using a data transmission information table. If the suspicious value reaches a predetermined threshold, IDS nodes send an alert message to other nodes about the identity of the malicious node, in order to prevent its activity on the network. Simulation results indicate that the performance of the proposed scheme in terms of packet delivery rate, packet loss rate, and routing overhead outperforms those in the literature.

T-SEA: trust based secure and energy aware routing protocol for mobile ad hoc networks

A trust based secure and energy aware (T-SEA) routing protocol for detection and isolation of black/gray hole nodes in mobile ad hoc networks (MANETs) is proposed in this paper. Energy aware characteristic is a vital requirement for prolonging MANET lifespan. Intrusion detection systems (IDSs) are used to monitor and catch black/gray hole nodes. Nodes having sufficient energy, high value of trust and maximum connections are selected as IDS capable nodes. T-SEA first detects suspicious nodes during data transfer phase without requiring any node to activate in sniff mode. Only few nodes (IDS nodes) out of IDS capable nodes function in sniff manner for monitoring during data transmission phase. During monitoring, IDS nodes detect a node as malicious based on nodes’ current behavior, current trust and behavior recorded during previous transmissions. The detection technique is energy aware since IDS executes only on few nodes at a time subsequent to the discovery of attack. This paper employs NS-2 to validate the proposed protocol.

A Cross-Layer Design for a Multihop, Self-Healing, and Self-Forming Tactical Network

In mission and time critical applications, bandwidth and delay optimizations are the key goals of communication systems. This paper presents a cross-layer framework design that reduces the call setup time, provides collision-free communication, and reuses the empty slots of Time Division Multiple Access (TDMA) protocol which otherwise causes low throughput and large delay. As number of communicating nodes in tactical networks is small as compared to commercial mobile ad hoc networks (MANETs), classical TDMA will yield huge number of empty slots and any Carrier Sense Multiple Access/Collision Detection (CSMA/CD) technique may cause more delay in some critical scenarios. Proposed methodology gives a Cross-Layer Architecture for Network (NET) Layer and Medium Access Control (MAC) Layer. Our design provides bandwidth efficient, collision-free communication to Software-Defined Radios (SDRs) in self-forming and self-healing tactical networks with low call setup time and multihop routing. For this purpose TDMA as MAC layer protocol and Ad Hoc On Demand Distance Vector (AODV) as Network Layer Routing Protocol are used. Our slot allocation (SA) algorithm, Cross-Layer TDMA (CL-TDMA), consists of control phase where AODV control packets are exchanged and data transfer phase where transmission of data and voice occurs. All active radios in vicinity gather information about communicating nodes based on the exchange of control packets by SDRs. Our algorithm then uses this information to help all active SDRs find slot(s) that will be used for collision-free transmission. A number of experiments are performed to establish improved performance of the proposed technique compared to other established techniques and protocols.

LSSCW: A Lightweight Security Scheme for Cluster based Wireless Sensor Network

In last two decades, Wireless Sensor Network (WSN) is used for large number of Internet of Things (IoT) applications, such as military surveillance, forest fire detection, healthcare, precision agriculture and smart homes. Because of the wireless nature of communication, Wireless Sensor Network suffers from various attacks such as Denial of Service (DoS) attack and replay attack. Dealing with scalability and security issues is the challenging task in WSN. In this paper, we have presented a Lightweight Security Scheme for Cluster based Wireless Sensor Network (LSSCW). LSSCW has two phases: Initialization phase and data transfer phase. The work focuses on secured data aggregation in wireless sensor network with the help of symmetric and session key generation technique. Data from sensor nodes are securely transferred to base station. LSSCW is lightweight and satisfies security requirements includ-ing authenticity, confidentiality and integrity. The performance of LSSCW is verified using Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Results shows that LSSCW is secured and is efficient in terms of computation and communication overhead.

Fair testing and stubborn sets

Partial order methods alleviate state explosion by considering only a subset of actions in each constructed state. The choice of the subset depends on the properties that the method promises to preserve. Many methods have been developed ranging from deadlock-preserving to CTL $$^*$$ -preserving and divergence-sensitive branching bisimilarity preserving. The less the method preserves, the smaller state spaces it constructs. Fair testing equivalence unifies deadlocks with livelocks that cannot be exited and ignores the other livelocks. It is the weakest congruence that preserves whether or not the system may enter a livelock that it cannot leave. We prove that a method that was designed for trace equivalence also preserves fair testing equivalence. We demonstrate its effectiveness on a protocol with a connection and data transfer phase. This is the first practical partial order method that deals with a practical fairness assumption.

Processing Intrusion Data with Machine Learning and MapReduce

These past years, cyber-attacks became a daily issue for enterprises. A possible defence against this kind of threat is intrusion detection. One of the key challenges is information extraction from this large amount of logged data. My paper aims to identify cyber-attack types as patterns in log files using advanced parallel computing approach and machine learning techniques. The MapReduce programming model is applied to parallel computing, while decision tree algorithms are used from machine learning.I discuss two research questions in this paper. First, despite parallelization, are machine learning algorithms still able to provide results with acceptable accuracy measured by traditional data mining figures (accuracy, precision, recall, area under receiver operand characteristic [ROC] curve [AUC])? Second, is it possible to achieve significant performance improvement by measuring runtime execution of the algorithm by introducing several measurement points?I proved that the machine learning model with two categories in the target variable is preferred to the one having five categories. The average performance improvement was 4–5 times faster for the whole algorithm compared to a single core solution. I achieved most of these improvements during the data transfer phase.

An improved vTPM-VM live migration protocol

To prevent malicious virtual machine from harming the security of vTPM-VM live migration process, we propose an improved vTPM-VM live migration protocol which uses a TPM-based integrity verification policy and a specific encryption scheme to enhance security. The TPM-based integrity verification policy is presented to ensure that all participating entities in this process are trustworthy. In data transfer phase, the specific encryption scheme is designed to associate the decipher process with one certain platform status so that only the destination platform can gain the key data of the migrated VM and vTPM instance. The security of this new protocol is analyzed. The results show that this protocol can effectively resist most of the attacks in the process of vTPM-VM live migration.

Virtual Clustered MAC Layer Protocol Design of a Wireless Sensor Network: ES-MAC

Sensor-MAC (S-MAC), one kind of use common type activities / sleep cycle wireless sensor network MAC layer protocol, we propose a strengthening type Enhanced S-MAC, called ES-MAC, and part of its application in wireless sensor networks than the outer layer of low traffic. ES-MAC is divided into three stages: the first stage is to create a virtual cluster region and preset transmission path; third stage of data transfer; second stage of data collection and sorting. Sensing node virtual cluster in the region, competitive manner using micro slot (Mini-Slot) determine the order of data transmission. In the data transfer phase has been established using the sequential transfer of data, the sense node in order to reduce the unnecessary and excessive collision monitoring, sleep time, and the growth of nodes. Simulation results show that, ES-MAC under different flow and different cycles, compared with S-MAC has lower average packet delay time.

Analysis of Energy Consumption Using HTTP and FTP Protocols Over IEEE 802.11

This paper presents an overview on green computing and energy aware to network communication. There was a measurement of energy efficiency and comparison of the main network transfer protocols used on the Internet. A tool named Energy Consumption Model was developed and inserted into the discrete event simulator Opnet Modeler to run the tests. An exhaustive analysis of consumption was performed during the data transfer phase with HTTP and FTP protocol using different packet sizes. From data obtained it was possible not only to quantify the energy consumed by the protocols, but also perform a comparative analysis between them. The results suggest that the use of HTTP is most suitable than the FTP. However, this advantage decreases proportionately to larger objects.

PSO-based Energy-balanced Double Cluster-heads Clustering Routing for wireless sensor networks

Regarding on how to optimize and improve the energy efficiency of nodes, here presents a clustering protocol based on PSO and has a balanced perception of distance and energy of the double cluster head centralized network. It mainly improves the original particle swarm optimization by optimising the fitness function. In addition, this algorithm Data transfer phase in the primary division of labor from the cluster heads to extend the cluster head re-election cycle, and the simulation results show that the algorithm in a balanced energy consumption across the network while extending the life cycle of the entire network.

The sensitivity of patient specific IMRT QC to systematic MLC leaf bank offset errors

Patient specific IMRT QC is performed routinely in many clinics as a safeguard against errors and inaccuracies which may be introduced during the complex planning, data transfer, and delivery phases of this type of treatment. The purpose of this work is to evaluate the feasibility of detecting systematic errors in MLC leaf bank position with patient specific checks. 9 head and neck (H&N) and 14 prostate IMRT beams were delivered using MLC files containing systematic offsets (+/- 1 mm in two banks, +/- 0.5 mm in two banks, and 1 mm in one bank of leaves). The beams were measured using both MAPCHECK (Sun Nuclear Corp., Melbourne, FL) and the aS1000 electronic portal imaging device (Varian Medical Systems, Palo Alto, CA). Comparisons with calculated fields, without offsets, were made using commonly adopted criteria including absolute dose (AD) difference, relative dose difference, distance to agreement (DTA), and the gamma index. The criteria most sensitive to systematic leaf bank offsets were the 3% AD, 3 mm DTA for MAPCHECK and the gamma index with 2% AD and 2 mm DTA for the EPID. The criterion based on the relative dose measurements was the least sensitive to MLC offsets. More highly modulated fields, i.e., H&N, showed greater changes in the percentage of passing points due to systematic MLC inaccuracy than prostate fields. None of the techniques or criteria tested is sufficiently sensitive, with the population of IMRT fields, to detect a systematic MLC offset at a clinically significant level on an individual field. Patient specific QC cannot, therefore, substitute for routine QC of the MLC itself.

Influence of time delay on trap stiffness in computer-controlled scanning optical tweezers

In scanning optical tweezers, the positions of optically trapped particles are individually controlled by periodically updating the scan data, which make up the data set of time-shared positions of a single-beam optical trap. The scan data are usually generated from the computer and are then transferred to the controller that sends electrical signals to the scanner. During the data generation and transfer phases, a short but noticeable time delay, indicated by the updating of scan data, is incurred and the scanner momentarily stalls. In this paper, we investigate the influence of this time delay on the trapped beads in scanning optical tweezers having a low scanning frequency. To understand the influence of the time delay, we analyzed the motions of two beads, trapped by the scanning optical traps, having a finite distance between them. We found that the trapped beads undergo relatively large vibrations during scanning, and the trap stiffness for one of the two beads significantly decreases with the time delay. We anticipate that our observation is essential to design scanning optical traps that need to manipulate trapped beads in real-time.

ON ARCHITECTURE FOR SLA-AWARE WORKFLOWS IN GRID ENVIRONMENTS

Service Level Agreements (SLAs) are currently one of the major research topics in Grid Computing, as they serve as a foundation for reliable and predictable Grids. SLAs define an explicit statement of expectations and obligations in a business relationship between provider and customer. Thus, SLAs should guarantee the desired and a-priori negotiated Quality of Service (QoS), which is a mandatory prerequisite for the Next Generation Grids. This development is proved by a manifold research work about SLAs and architectures for implementing SLAs in Grid environments. However, this work is mostly related to SLAs for standard, monolithic Grid jobs and neglects the dependencies between different steps of operation. The complexity of an SLA-specification for workflows grows significantly, as characteristics of correlated sub-jobs, the data transfer phases, the deadline constraints and possible failures have to be considered. Thus, an architecture for an SLA-aware workflow implementation needs sophisticated mechanisms for specification and management, sub-job mapping, data transfer optimization and fault reaction. Therefore, this paper presents an architecture for SLA-aware Grid workflows. The main contributions are an improved specification language for SLA-aware workflows, a mapping and optimization algorithm for sub-job assignment to Grid resources and a prototype implementation using standard middleware. Experimental measurements prove the quality of the development.