Volume-2 Issue-9

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Volume-2 Issue-9, August 2014, ISSN: 2319-9598 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

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Edward Danso Ansong, J. B. Hayfron-Acquah, Dominic Damoah, Michael Asante, Brighter Agyeman

Paper Title:

Camouflage Worm Detection and Counter-Measures

Abstract: This research focuses special attention on a new class of worms called Camouflaging worm (C-Worm). The key difference between C-Worm and traditional worms is that, it displays the ability to intelligently analyse and make changes to its scan traffic volume over time.  This new class of active worms is an attack that spread itself on the internet by exploiting vulnerabilities on computer systems.

C-Worm, Camouflaging, traditional, vulnerabilities.


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2.        Chen, Z., Gao, L., & Ji, C. (2003). On Effectiveness of defense systems against active worms.

3.        Gu, G., Sharif, M., Qin, X., Dagon, D., Lee, W., & Riley, G. (2004). Worm detection, early warning and response based on local victim information. 20 th Annual Computer Security Applications Conference.

4.        M.A.BASEER, M., NARAYANA, M. P., & LAHANE, M. S. (2013). Modeling and Detection of Camouflaging Worm. INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGIES, VOL. 01, ISSUE 02, 99-104. Retrieved 12 2013

5.        M.K, P. C., & P.V, M. (2012). Modelling and Detection of Camouflaging Worms. International Journal of Emerging Technology and Advanced Engineering, 2-3. Retrieved 12 2013

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7.        Pele Li Mehdi Salour, X. S. (2008). Survey of Internet Worm Detection and Containment. IEEE Communications Surveys.

8.        Saudi, M. M., Seman, K., Tamil, E. M., Yamani, M., Idris, I., & Visualization, A. (2008). Worm Analysis through Computer Simulation (WAtCoS). Proceedings of the World Congress in Engineering 2008, 1.

9.        Singh, S., Estan, C., Varghese, G., & Savage, S. (2003). The EarlyBird System for Real-time Detection of Unknown Worms. Technical Report CS2003-0761. University of California, San Diego.

10.     Talli, P., & Krishna, M. V. (2012). Detection of Active Internet Worm: Camouflaging Worm. nternational Journal of Electronics Communication and Computer Engineering, 3(5), 1172-1175. Retrieved 12 2013

11.     Venkataraman, S., Song, D., Gibbons, P. B., & Blum, A. (2004). New Streaming Algorithms for Fast Detection of Superspreaders. Intel Corporation. Retrieved 1 2014

12.     Wang, X., Yu, W., Champion, A., Fu, X., & Xuan, D. (2007). Detecting Worms via Mining Dynamic Program Execution. Third International Conference on Security and
Privacy in Communication Networks and the Workshops, SecureComm 2007, (pp. 412-421). Nice,France.

13.     Wu, J., Vangala, S., Gao, L., & Kwiat, K. (2004). An Effective Architecture and Algorithm for Detecting Worms with Various Scan Techniques. 11th Annual Network and Distributed System Security Symposium (NDSS '04).

14.     Yi, B. k. (2006). Digital Signatures.

15.     Yu, W., Wang, X., Calyam, P., Xuan, D., & Zhao, W. (2011). Modeling and Detection of Camouflaging Worm. IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL., 1-3. Retrieved 12 29, 2013

16.     Yu, W., Wang, X., PrasadCalyam, Xuan, D., & Zhao, W. (n.d.). On Detecting Camouflaging Worm.

17.     Yu, W., Wang, X., Xuan, D., & Lee, D. (2006). Effective Detection of Active Worms with Varying Scan Rate. IEEE International Conference on Security and Privacy in Communication Networks (SecureComm).






Omar AL-Masari, Musa AL-Masari

Paper Title:

Influence of a Wind Farm on Power System Oscillatory Stability

Abstract: This paper deals with the influence of wind turbine generators on oscillatory stability. Examining low-frequency oscillatory stability is important for understanding the weakest mode that leads to oscillatory problems. The performance of three types of wind generators, the doubly fed induction generator, the squirrel cage induction generator, and the permanent magnet synchronous generator, when connected to a grid was examined. Eigenvalue analysis and time-domain analysis helped to identify oscillatory instability problems in the wind farm. Moreover, the advantages of a high voltage direct current link (HVDC) for improving instability issues was studied. The simulation results show the significance of the DC link in improving the stability of the system by isolating the wind farm at the point of common couple from a fault event. The simulation software tool DIgSILENT PowerFactory was used for all modelling of wind farms, HVDC, and the IEEE 14-bus test system.

Wind Turbine Generators, Oscilatory Stability, DFIG, PMSG, SCIG, HVDC, IEEE 14-bus test system, Eigenvalue analysis, DIgSILENT PowerFactory.


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Sonali Sharma, Chhatarpal, Ramanand Harijan

Paper Title:

Survey on Internet of Things and Design for a Smart Parking Area

Abstract: This paper introduces Internet of Things (IoTs), which offers capabilities to identify, share information and connect worldwide physical objects into a single system. In this research work, we will discuss how we can connect various objects in a better way and what are the basic requirements and functions to make them communicate and consequently make this world unified. This survey summarizes the easiest and most feasible way of connecting various objects of IoT and it also discuss about a prototype for smart parking area application of IoT. In this prototype we have used a microcontroller to handle all the devices. Security is also added to this model using scanners and finger print detectors. 

Internet of Things (IoT), Parking, Security, Addressability.


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