Analysis of IPv6 through Implementation of Transition Technologies and Security attacks

IPv6 provides more address space, improved address design, and greater security than IPv4. Different transition mechanisms can be used to migrate from IPv4 to IPv6 which includes dual stack networks, tunnels and translation technologies. Within all of this, network security is an essential element and therefore requires special attention. This paper analyses two transition technologies which are dual stack and tunnel. Both technologies are implemented using Cisco Packet Tracer and GNS3. This work will also analyse the security issues of IPv6 to outline the most common vulnerabilities and security issues during the transition. Finally, the authors will design and implement the dual stack, automatic and manual tunnelling transition mechanisms using Riverbed Modeler simulation tool to analyse the performance and compare with the native IPv4 and IPv6 networks

Analysis of IPV6 Transition Technologies

Currently IPv6 is extremely popular with companies, organizations and Internet service providers (ISP) due to the limitations of IPv4. In order to prevent an abrupt change from IPv4 to IPv6, three mechanisms will be used to provide a smooth transition from IPv4 to IPv6 with minimum effect on the network. These mechanisms are Dual-Stack, Tunnel and Translation. This research will shed the light on IPv4 and IPv6 and assess the automatic and manual transition strategies of the IPv6 by comparing their performances in order to show how the transition strategy affects network behaviour. The experiment will be executed using OPNET Modeler that simulates a network containing a Wide Area Network (WAN), a Local Area Network (LAN), hosts and servers. The results will be presented in graphs and tables, with further explanation. The experiment will use different measurements such as throughput, latency (delay), queuing delay, and TCP delay.Comment: pages 19-38, Online link: http://airccse.org/journal/cnc/6514cnc02.pd

Analysis of WiFi and WiMAX and Wireless Network Coexistence

Wireless networks are very popular nowadays. Wireless Local Area Network (WLAN) that uses the IEEE 802.11 standard and WiMAX (Worldwide Interoperability for Microwave Access) that uses the IEEE 802.16 standard are networks that we want to explore. WiMAX has been developed over 10 years, but it is still unknown to most people. However compared to WLAN, it has many advantages in transmission speed and coverage area. This paper will introduce these two technologies and make comparisons between WiMAX and WiFi. In addition, wireless network coexistence of WLAN and WiMAX will be explored through simulation. Lastly we want to discuss the future of WiMAX in relation to WiFi.Comment: 16 pages. ISSN 0974-932

Analysis of corporate environmental reports using statistical techniques and data mining

Measuring the effectiveness of corporate environmental reports, it being highly qualitative and less regulated, is often considered as a daunting task. The task becomes more complex if comparisons are to be performed. This study is undertaken to overcome the physical verification problems by implementing data mining technique. It further explores on the effectiveness by performing exploratory analysis and structural equation model to bring out the significant linkages between the selected 10 variables. Samples of five hundred and thirty nine reports across various countries are used from an international directory to perform the statistical analysis like: One way ANOVA (Analysis of Variance), MDA (Multivariate Discriminant Analysis) and SEM (Structural Equation Modeling). The results indicate the significant differences among the various types of industries in their environmental reporting, and the exploratory factors like stakeholder, organization strategy and industrial oriented factors, proved significant. The major accomplishment is that the findings correlate with the conceptual frame work of GRI

Implementation of a modified wireless sensor network MAC protocol for critical environments

A Wireless Sensor Network (WSN) is a network of many nodes. These nodes are equipped with sensors which communicate wirelessly using techniques for radio frequency transmission. This network helps to measure and record the physical environment variables and to forward these results to a central location known as a sink. As WSN nodes are only supplied by a battery, the primary challenge is to reduce the energy consumption. The MAC layer is responsible for the establishment of a reliable and efficient communication link between WSN nodes and is responsible for energy waste. The newly proposed MAC protocol in this paper uses an improved variant of CSMA which implements weak signal detection (WSD). This technique enables dividing collisions from weak signals and takes appropriate decisions to reduce energy consumption. The CSMA/WSD protocol is presented as a flowchart and implemented in OMNeT++ by using the MiXiM framework structure. Implementation tests are performed to prove the validity of the implemented protocol in different scenarios. Different simulation scenarios show that this protocol offers a higher throughput, a smaller mean backoff time, and less average delay in critical environments

EGPred: prediction of eukaryotic genes using Ab initio methods after combining with sequence similarity approaches

EGPred is a Web-based server that combines ab initio methods and similarity searches to predict genes, particularly exon regions, with high accuracy. The EGPred program proceeds in the following steps: (1) an initial BLASTX search of genomic sequence against the RefSeq database is used to identify protein hits with an E-value <1; (2) a second BLASTX search of genomic sequence against the hits from the previous run with relaxed parameters (E-values <10) helps to retrieve all probable coding exon regions; (3) a BLASTN search of genomic sequence against the intron database is then used to detect probable intron regions; (4) the probable intron and exon regions are compared to filter/remove wrong exons; (5) the NNSPLICE program is then used to reassign splicing signal site positions in the remaining probable coding exons; and (6) finally ab initio predictions are combined with exons derived from the fifth step based on the relative strength of start/stop and splice signal sites as obtained from ab initio and similarity search. The combination method increases the exon level performance of five different ab initio programs by 4%-10% when evaluated on the HMR195 data set. Similar improvement is observed when ab initio programs are evaluated on the Burset/Guigo data set. Finally, EGPred is demonstrated on an ~95-Mbp fragment of human chromosome 13. The list of predicted genes from this analysis are available in the supplementary material. The EGPred program is computationally intensive due to multiple BLAST runs during each analysis. The EGPred server is available at http://www.imtech.res.in/raghava/egpred/

A Semi-Supervised Learning Approach for Tackling Twitter Spam Drift

Twitter has changed the way people get information by allowing them to express their opinion and comments on the daily tweets. Unfortunately, due to the high popularity of Twitter, it has become very attractive to spammers. Unlike other types of spam, Twitter spam has become a serious issue in the last few years. The large number of users and the high amount of information being shared on Twitter play an important role in accelerating the spread of spam. In order to protect the users, Twitter and the research community have been developing different spam detection systems by applying different machine-learning techniques. However, a recent study showed that the current machine learning-based detection systems are not able to detect spam accurately because spam tweet characteristics vary over time. This issue is called “Twitter Spam Drift”. In this paper, a semi-supervised learning approach (SSLA) has been proposed to tackle this. The new approach uses the unlabeled data to learn the structure of the domain. Different experiments were performed on English and Arabic datasets to test and evaluate the proposed approach and the results show that the proposed SSLA can reduce the effect of Twitter spam drift and outperform the existing techniques

Enhanced Cuckoo Search Algorithm for Virtual Machine Placement in Cloud Data Centers

In order to enhance resource utilisation and power efficiency in cloud data centres it is important to perform Virtual Machine (VM) placement in an optimal manner. VM placement uses the method of mapping virtual machines to physical machines (PM). Cloud computing researchers have recently introduced various meta-heuristic algorithms for VM placement considering the optimised energy consumption. However, these algorithms do not meet the optimal energy consumption requirements. This paper proposes an Enhanced Cuckoo Search (ECS) algorithm to address the issues with VM placement focusing on the energy consumption. The performance of the proposed algorithm is evaluated using three different workloads in CloudSim tool. The evaluation process includes comparison of the proposed algorithm against the existing Genetic Algorithm (GA), Optimised Firefly Search (OFS) algorithm, and Ant Colony (AC) algorithm. The comparision results illustrate that the proposed ECS algorithm consumes less energy than the participant algorithms while maintaining a steady performance for SLA and VM migration. The ECS algorithm consumes around 25% less energy than GA, 27% less than OFS, and 26% less than AC

Implementation and Evaluation of Steganography based Online Voting

Though there are online voting systems available, the authors propose a new and secure steganography based E2E (end-to-end) verifiable online voting system, to tackle the problems in voting process. This research implements a novel approach to online voting by combining visual cryptography with image steganography to enhance system security without degrading system usability and performance. The voting system will also include password hashed-based scheme and threshold decryption scheme. The software is developed on web-based Java EE with the integration of MySQL database server and Glassfish as its application server. The authors assume that the election server used and the election authorities are trustworthy. A questionnaire survey of 30 representative participants was done to collect data to measure the user acceptance of the software developed through usability testing and user acceptance testing