Best Paper Award

The chief editor identifies several of the high quality papers accepted based on the reviewers’ comments. After receiving final feedback from technical committee, the chief editor decides which published paper will receive the Best Paper Award;
IJSRNSC Best paper selection criteria:

• Significance of the paper to the field of computer science;
• The extent to which the paper is interesting;
• Theoretical contribution;
• Scientific/technical significance of the topic or problem investigated;
• Use of appropriate methodological rigor;
• Clarity of writing.

• Open Access   Article

  Proposed Jamming Removal Technique for Wireless Sensor Network

  Amr M. Kishk, Nagy W. Messiha, Nawal A. El-Fishawy, Abdelrahman A. Alkafs, Ahmed H. Madian

  Research Paper | Journal (IJSRNSC)

  Vol.3 , Issue.2 , pp.1-14, Mar-2015

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  Abstract
  This electronic docum Wireless Sensor Network (WSN) is exposed to many threats to destroy data confidentiality during the transmission in the communication channel. The Jamming is one of these threats. To face this threat, we should discuss this problem from many directions. The discussion includes jamming types and its effects, jamming detection techniques, disturber localization methods, and defensive techniques. The reduction or removal of the effectiveness of jamming from the reconstructed data at the receiver enhances the performance of WSN. The techniques used to face this threat are discussed in this paper. The enhancements of these techniques are introduced in this paper which are extracted from their drawbacks. The weakness point of the disturber is the inability to jam the signal frequency which leads us to propose a defensive technique to remove the effectiveness of jamming completely from the reconstructed data at the receiver. The proposed defensive technique guides us to remove the attached redundancy of the coding techniques from the packets. And also, it reduces the transmission time of the transmitted message. So, the overall performance of WSN is improved due to jamming removal.

  Key-Words / Index Term
  Disturber Types; Victim Nodes; Jamming Detection Techniques; Disturber Localization Methods; Defensive Techniques

  References
  [1]. X. Wenyuan, T. Wade, Z. Yanyong, and W. Timothy, "The feasibility of launching and detecting jamming attacks in wireless networks", Mobihoc 2005, Urbana-Champaign, Illinois, USA, pp. 25-27, May 2005.
  [2]. S. Periyanayagi and V. Sumathy, "A swarm based defense technique for jamming attacks in wireless sensor networks", International Journal of Computer Theory and Engineering, vol. 3, no. 6, pp. 816-821, Dec. 2011.
  [3]. S. Uke, A. Mahajan, and R. Thool, "UML modeling of physical and data link layer security attacks in WSN", International Journal of Computer Applications, vol. 70, no. 11, pp. 25-28, May 2013.
  [4]. R. Muraleedharan and L. Osadciw, "Jamming attack detection and countermeasures in wireless sensor network using ant system", Proc. Wireless Sensing and Processing, vol. 6248, pp. 62480G, 2006.
  [5]. Sanchita Gupta and Pooja Saini, "Modified Pairwise Key Pre-distribution Scheme with Deployment Knowledge in Wireless Sensor Network", International Journal of Scientific Research in Network Security and Communication, Volume-01, Issue-02, Page No (21-23), May -Jun 2013.
  [6]. L. Mingyan, K. Iordanis, and P. Radha, "Optimal jamming attacks and network defense policies in WSN,” IEEE INFOCOM, 2007.
  [7]. R. Shivanagu and C. Deepti, "An assessment of security mechanisms against reactive disturber attack In wireless sensor networks", International Journal in Foundations of Computer Science & Technology (IJFCST), vol. 3, no.3, pp. 31-40, May 2013.
  [8]. M. Dawood, L. Ahila, S. Sadasivam, and G.Athisha, "Image compression in wireless sensor networks- A survey", International Journal of Applied Information Systems (IJAIS), Foundation of Computer Science FCS, New York, USA, vol.1, no. 9, pp. 11-15, Feb. 2012.
  [9]. W. Xu, T. Wood, W. Trappe, Y. Zhang, "Channel surfing and spatial retreats: defenses against wireless denial of service", In WiSe’04: Proceedings of the 2004 ACM Workshop on Wireless Security, pp. 80–89, New York, USA, 2004.
  [10]. G. Zhou, T. He, J. Stankovic, and T. Abdelzaher, "RID: Radio Interference Detection in wireless sensor networks", In Proceedings of the IEEE INFOCOM’2005, 2005.
  [11]. C. Murat, G. AKIRO, and A. Turan, "Design and evaluation of a query-based jamming detection algorithm for wireless sensor networks", Turk J Elec Eng & Comp Sci, vol. 19, no. 1, pp. 1-19, 2011.
  [12]. K. Siddhabathula, Q. Dong, L. Donggang, and M. Wright, "Fast jamming detection in sensor networks", IEEE International Conference on Communications (ICC), 2012.
  [13]. A. Wood, J. Stankovic, S. Son, "JAM: A jammed-area mapping service for sensor networks", 24th IEEE Real-Time Systems Symposium (RTSS’2003), pp. 286–297, 2003.
  [14]. C. Tianzhen, L. Ping, and Z. Sencun, "An algorithm for disturber localization in wireless sensor networks", IEEE 26th International Conference on Advanced Information Networking and Applications (AINA), 2012.
  [15]. A. Wood, J. Stankovic, and G. Zhou, "DEEJAM: Defeating Energy Efficient Jamming", In The 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), San Diego, CA, June 2007.
  [16]. S. Incheol, S. Yilin, X. Ying, M. Thai, and T. Znati, "Reactive jamming attacks in multi-radio wireless sensor networks: An efficient mitigating measure by identifying trigger nodes", FOWANC’09, New Orleans, Louisiana, USA, pp. 87-96, May 2009.
  [17]. N. Bulusu, J. Heidemann, and D. Estrin, "Gps-less low cost outdoor localization for very small devices," in IEEE Personal Communications Magazine, pp. 28-34, 2000.
  [18]. J. Blumenthal, R. Grossmann, F. Golatowski, and D. Timmermann, "Weighted Centroid localization in ZigBee-based sensor networks", in WISP`07: Proceedings of the IEEE International Symposium on Intelligent Signal Processing, pp. 1-6, 2007.
  [19]. H. Liu, W. Xu, Y. Chen, and Z. Liu, "Localizing disturbers in wireless networks," in PERCOM`09: Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications, pp. 1-6, 2009.
  [20]. A. Mpitziopoulos and D. Gavalas, "An effective defensive node against jamming attacks in sensor networks", Security and Communication Networks Security Comm. Networks, Published online in Wiley InterScience, 2008.
  [21]. M. Cagalj, S. Capkun, and J. Hubaux, "Wormhole-based antijamming techniques in sensor networks", IEEE Transactions on Mobile Computing, May 2006.
  [22]. RFC 2898. PKCS #5: Password-based cryptography specification version 2.0: http://rfc.net/rfc2898.html
  [23]. M. Matsumoto and T. Nishimura, "Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator", ACM Transactions on Modeling and Computer Simulation, vol. 8, no. 1, Jan. 1998.
  [24]. L. Rizzo, “Effective erasure codes for reliable computer communication protocols”, ACM CCR, vol. 27, no. 2, pp. 24–36, 1997.
  [25]. K. Siwiak, "Ultra-wide band radio: Introducing a new technology", Vehicular Technology Conference (VTC 2001) Spring, IEEE VTS 53rd, vol. 2, pp. 1088–1093, 2001.
  

  Citation
  Amr M. Kishk, Nagy W. Messiha, Nawal A. El-Fishawy, Abdelrahman A. Alkafs, Ahmed H. Madian, "Proposed Jamming Removal Technique for Wireless Sensor Network", International Journal of Scientific Research in Network Security and Communication, Vol.3, Issue.2, pp.1-14, 2015

• Open Access   Article

  Delving into Security of Networks - Times Need

  Annie Singla, Kamal Jain and Ajay Gairola

  Research Paper | Journal (IJSRNSC)

  Vol.2 , Issue.3 , pp.1-8, May-2014

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  Abstract
  Cyber space is an inevitable and indispensable place in every human beings life now. With the advent of Internet fad, the rapid digitization has taken place. But with the rapid digitization, there is a rapid increase in the occurrence of cyber disasters. Disasters are measured on two parameters-loss to life and property. In cyber disasters, there is a hell lot loss to money, zillions of people are getting affected on a daily basis and the loss of money is in billions of dollars in every disaster. They are bringing down the economy of the nation and people are also affecting on regular basis. Their privacy is being compromised. Due to the Internet fad, E-commerce, e-banking, online casinos are victimized. The vulnerability in the webpage of Gmail is found out during research study. The studies of vulnerability lead to cyber disasters using Phishing attacks through which the passwords were retrieved and accessed of various people. Users should be more aware as well as updated in terms of technology which can diminish these cyber disasters.

  Key-Words / Index Term
  Phishing Attack, DDoS

  References
  [1] Norton Report (2013). Available at (Retrieved on May, 2014)
  [2] Karnika Seth (8th May 2010). IT Act 2000 vs 2008- Implementation, Challenges, and the Role of Adjudicating Officers. Available at (Retrieved 29th May,2014)
  [3] 2013- The Impact of Cyber Crime. Available at (Retrieved on 23rd March,2014)
  [4] EERI Special Earthquake Report — April 2005 global cyber war and crime: A conceptual framework * Bryan School of Business and Economics, The University of North Carolina at Greensboro, Bryan Building, Room: 368, P.O. Box 26165, Greensboro, NC 27402-6165, USA ,Received 14 December 2004; accepted 14 September 2005.
  [5] Chris Welch(3rd October, 2013). Available at . (Retrieved on 29th Nov, 2013).
  [6] Kounteya Sinha (28th Feb, 2014). Available at . (Retrieved on 14th April, 2014).
  [7] Steven Musil (February 11, 2014). Available at < http://news.cnet.com/8301-1009_3-57618762-83/record-breaking-ddos-attack-in-europe-hits-400gbps/> (Retrieved 23rd March,2014)
  

  Citation
  Annie Singla, Kamal Jain and Ajay Gairola, "Delving into Security of Networks - Times Need", International Journal of Scientific Research in Network Security and Communication, Vol.2, Issue.3, pp.1-8, 2014

• Open Access   Article

  E-IRRIGATION: An Automation of Irrigation using Wireless Networks

  Chandraprakash Patidar

  Research Paper | Journal (IJSRNSC)

  Vol.1 , Issue.5 , pp.18-20, Nov-2013

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  Abstract
  The major influencing parameter of Indian economy is agricultural. Also in agricultural the most important factor is irrigation. Irrigation must be in time and proper for a better crop yield. The major irrigation is performed using electric water pumps. Irrigation by electric water pump introduced problems of frequent, intermittent, low voltage supply. This causes monitoring the supply of power and hurdles in irrigation. The unreliable power supply and frequent power cuts disturb the farmers and it leads to decrease the efficiency of farmers. This turns into the movement of farmer’s from farming to urban area. In this paper I introduced a system which shows how automation of irrigation is performed to solve the problems introduced by intermittent electrical power supply. In this paper I designed an embedded system which is controlled by sending a SMS from mobile phone. This embedded device can control maximum 8 devices.

  Key-Words / Index Term
  Agriculture and irrigation, WSN, GSM

  References
  [1]. Subhash, M., and Bansal, N. K. 2009. Sectoral Analysis forelectricity demand in India. www.ignou.ac.in
  [2]. Padmanaban, S., and Ashok Sarkar. 2006. Electricity Demand Side Management (DSM) In India – A Strategic And Policy Perspective. Office of Environment, Energy and Enterprise, US Agency for International Development, New Delhi, India.
  [3]. S. Padmanaban, C., and Govindarajalu. 2006. Economic Sector Work on Power Supply to Agriculture: Sub-Task Report on Cost Minimization Through Integrated Agricultural DSM. Office of Environment, Energy and Enterprise, US Agency for International Development, New Delhi, India.
  [4]. Nezhad, H. G., and Sarkar, A. 1997. Demand-Side Management: A Policy Model for India. Proceedings of the Twentieth Annual International Energy Conference of the International Association for Energy Economics (New Delhi, India). Volume II. 448-458.
  [5]. Siriginidi Subba Rao., 2008. Social development in Indianrural communities: Adoption of telecentres. International Journal of Information Management. Vol 28. 474–482.
  [6]. Sharma, G. Mission 2007 in India: Every village a knowledge centre. i4donline.net/sept04/mission2007
  [7]. Overview of power sector in India. 2005. India Core Publishing.
  [8]. wirelessdevnet.com/channels/sms/features/sms.ht
  [9]. Umesh Hodeghatta Rao, Sanjay Mohapatra Mobile Technology for Irrigation Problems in Rural India, November 2009 ICIS '09: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
  [10]. N. Wang, N. Zhang, M.Wang, Wireless sensors in agriculture and food industry-Recent development and future perspective, Computers and Electronics in Agriculture,2006,Vol.50,pp.1-14
  [11]. R. Beckwith. D. Teibel, and P. Bowen Jones, "Report from the Field: Results from an Agricultural Wireless Sensor Network", proceedings of 29th IEEE LCN'04, Tampa, Florida, November 15-17, 2004
  [12]. A. Baggio, "Wireless sensor networks in precision agriculture", proceedings of REALWSN'05, Stockholm, Jun 20-21, 2005
  [13]. K. Langendoen, A. Baggio, 0. Visser, "Murphy Loves Potatoes: Experiences from a Pilot Sensor Network Deployment in Precision Agriculture", 14th 14th Int. Workshop on Parallel and Distributed Real-Time Systems (WPDRTS), Rhodes, Greece, April, 2006
  [14]. D. Kim, T. Sanchez Lopez, S. Yoo, J. Sung, J. Kim, Y. Kim, Y. Doh, "ANTS: An Evolvable Network of Tiny Sensors", Lecture Notes in Computer Science (LNCS vol. 3824), pp. 142-151, 2005
  [15]. Jose A. Gutierrez, Ed. Callaway, and Raymond. Barrett, "Low-Rate Wireless Personal Area Networks: enabling wireless sensors with IEEE 802.15.4", IEEE Press, 2004
  

  Citation
  Chandraprakash Patidar, "E-IRRIGATION: An Automation of Irrigation using Wireless Networks", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.5, pp.18-20, 2013

• Open Access   Article

  Architecture for Network-Intrusion Detection and Response in open Networks using Analyzer Mobile Agents

  M.Shivakumar, R.Subalakshmi, S. Shanthakumari and S.John Joseph

  Research Paper | Journal (IJSRNSC)

  Vol.1 , Issue.4 , pp.1-7, Sep-2013

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  Abstract
  This paper describes the implementation of distributed agent architecture for intrusion detection and response in networked computers. Unlike conventional intrusion detection systems (IDS), this security system attempts to emulate mechanisms of the natural immune system using Java-based agents. These security agents monitor multiple levels like packet, process, system, user etc. of networked computers to determine correlation among the observed anomalous patterns, reporting such abnormal behavior to the network administrator and possibly taking some action to counter a suspected security violation. Here the focus is on the design aspects of such an intrusion detection system by integrating different artificial intelligence techniques and a mobile agent architecture. Here anomaly based intrusion mechanism will be taken into consideration with the help of agents.

  Key-Words / Index Term
  Component, Mobile Agents (MA), Intrusion Detection, Distributed Systems

  References
  [1]. William Stallings, “Cryptography and Network Security”, Principles and Practices, Third Edition.
  [2]. D. E. Denning, "An intrusion-detection model". IEEE Transactions on Software Engineering, Vol. SE-13 (No. 2):222-232, Feb. 1987.
  [3]. Stephen Northcutt, Judy Novak, “Network Intrusion Detection”, Third Edition, Pearson Education 2003.
  [4]. Anderson, James P., “Computer Security Threat Monitoring and Surveillance,” Technical Report, James P. Anderson Co., Fort Washington, PA, April1980.
  [5]. Amoroso, Edward, Intrusion Detection, Intrusion.net Books, Sparta, New Jersey, 1999. [ASAK99] M.Asaka, S.Okazawa, A.Taguchi, and S.Goto, "A Method of Tracing Intruders by Use of Mobile Agents," INET'99, June 1999.
  [6]. Bauer, David S. and Koblentz, Michael E., “NIDX: An Expert System for Real-Time Network Intrusion Detection,” Proceedings of the Computer Networking Symposium, pp. 90-106, April 1988, Washington, DC.
  [7]. Jeffrey M. Bradshaw, “An Introduction to Software Agents,” In Jeffrey M. Bradshaw, editor, Software Agents, chapter 1. AAAI Press/The MIT Press, 1997.
  [8]. Chess, D., B. Grosof, C. Harrison, D. Levine, C. Parris, G. Tsudik, “Itinerant Agents for Mobile Computing,” IBM Research Report, RC 20010, March 1995.
  [9]. Mark Crosbie and E. H. Spafford, “Active Defense of a Computer System Using Autonomous Agents,” Department of Computer Sciences, Purdue University, CSD-TR-95-008, 1995.
  [10]. Denning, Dorothy E., “An Intrusion Detection Model,” IEEE Transactions on Software Engineering, Vol. SE-13, No. 2, pp. 222-232, February 1987.
  [11]. Farmer, W.M., J.D. Guttman, and V. Swarup, “Security for Mobile Agents: Authentication and State Appraisal,” Proceedings of the 4th European Symposium on Research in Computer Security (ESORICS ’96), pp. 118-130, September1996.
  [12]. Farmer, W.M., J.D. Guttman, and V. Swarup, “Security for Mobile Agents: Issues and Requirements,” Proceedings: National Information Systems Security Conference, pp. 591-597, October 1996.
  [13]. Finin, T., R. Fritzson, D. McKay, and R. McEntire. “KQML as an Agent Communication Language,” Proceedings of the Third International Conference on Information and Knowledge Management (CIKM ’94), ACM Press, Nov. 1994.
  [14]. Hansoty, Jatin N., “LAVA: Secure Delegation of Mobile Applets,” Master’s Thesis North Carolina State Univ., 1997.
  [15]. Harrison, C.G., D.M. Chess, A. Kershenbaum, “Mobile Agents: Are they a good idea?,” IBM Research Report, March 1995.
  [16]. Danny Lange and Mitsuru Oshima, Programming and Deploying Java Mobile Agents with Aglets, Addison-Wesley, 1998.
  [17]. W. Lee, S.J. Stolfo, and K. Mok, “A Data Mining Framework for Building Intrusion Detection Models,” Proceedings of the IEEE Symposium on Security and Privacy, 1999.
  [18]. Marreale, P., “Agents on the Move,” IEEE Spectrum, April 1998, pp. 34-41.
  [19]. Stefano Martino, “A Mobile Agent Approach to Intrusion Detection,” Joint Research Centre-Institute for Systems, Informatics and Safety, Italy, June 1999.
  [20]. Michael M. Sebring et al., “Expert Systems in Intrusion Detection: A Case Study,” Proceedings, 11th National Computer Security Conference, pp. 74-81, October 1988.
  [21]. Stephen E. Smaha, “Haystack: An Intrusion Detection System,” Fourth Aerospace Computer Security Applications Conference, Orlando Florida, pp. 37-44, December 1988.
  [22]. Jonathan Smith, “A Survey of Process Migration Mechanisms,” Operating Systems Review, 22(3), ACM Special Interest Group on Operating Systems, pp. 28-40, July 1988.
  [23]. Wu, S.F., M. S. Davis, J. N. Hansoty, J. J. Yuill, S. Farthing, J. S. Webster, X. Hu. “LAVA: Secure Delegation of Mobile Applets,” Technical Report 96/42, Center for Advanced Computing and Communication, North Carolina State Univ., Raleigh, NC , October 1996.
  

  Citation
  M.Shivakumar, R.Subalakshmi, S. Shanthakumari and S.John Joseph, "Architecture for Network-Intrusion Detection and Response in open Networks using Analyzer Mobile Agents", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.4, pp.1-7, 2013

• Open Access   Article

  Modelling and simulation of DDOS Attack using SimEvents

  Abubakar Bala and Yahya Osais

  Research Paper | Journal (IJSRNSC)

  Vol.1 , Issue.2 , pp.5-14, Jun-2013

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  Abstract
  At the beginning of the 21st century, a new form of denial of service (DoS) attack emerged which is the Distributed DoS (DDoS). This new form of attack was launched on huge number of prominent websites such as yahoo, e-bay, Amazon, and buy.com, resulting in tremendous financial loses. DDoS attack has continued to increase over the years due to the rapid increase in internet users. Moreover, even more alarming is the fact that developers of DDoS tools have assumed unprecedented sophistication in their design methods, thus making their attacks highly destructive and undetectable. As a result of these reason and many others, researchers have focused their attention on the study of this new method of attack, they are particularly interested in studying its evolution, and with this knowledge they are being able to design anti-DDoS tools in order to prevent networks from falling into the clutches of DDoS attack. In this research work, a DDoS attack is simulated using MATLAB’s SimEvents, with the aim of finding the quantitative measure of its effect on the victim, experiments conducted in this study show that the server is scarcely utilized in its normal working condi-tions thus having high availability and low average utilization since it accepts requests only from legitimate clients. However, as the attacker launches an attack on the server, its utilization increases sharply and thus resulting in decrease in availability, this is because the server is flooded with illegal requests from the attacker as well as zombies from within the network domain. Additional study reveals that when a warm-up phase is added to the simulation of the server failure, the utilization suddenly increases due to the fact that the attacker seizes the opportunity of the slow recovery of the server to further overwhelm it and eventually push it into saturation.

  Key-Words / Index Term
  Modelling, simulation, DDoS, DoS, SimEvents, MATLAB

  References
  [1] A. Noureldien, “Protecting web servers from dos/ddos flooding attacks. a technical overview,” in International Conference on Web-Management for International Organisations. Proceedings. Geneva, 2002.
  [2] I. Kotenko and A. Ulanov, “Simulation of internet ddos attacks and defense,” in Information Security, pp. 327–342, Springer, 2006.
  [3] I. Kotenko, A. Alexeev, and E. Man’kov, “Formal framework for model-ing and simulation of ddos attacks based on teamwork of hackers-agents,” in Intelligent Agent Technology, 2003. IAT 2003. IEEE/WIC International Conference on, pp. 507–510, IEEE, 2003.
  [4] L. Li and G. Lee, “Ddos attack detection and wavelets,” Telecommunica-tion Systems, vol. 28, no. 3-4, pp. 435–451, 2005.
  [5] J. Ryan, M.-J. Lin, and R. Miikkulainen, “Intrusion detection with neural networks,” in Advances in neural information processing systems, pp. 943–949, MORGAN KAUFMANN PUBLISHERS, 1998.
  [6] G. Khazan and M. A. Azgomi, “A distributed attack simulation for quan-titative security evaluation using SimEvents,” in Computer Systems and Applications, 2009. AICCSA 2009. IEEE/ACS International Conference on, pp. 382–385, IEEE, 2009.
  [7] Mathworks,“Simevents,http://www.mathworks.com/help/simevents/release-notes.html.”

  Citation
  Abubakar Bala and Yahya Osais, "Modelling and simulation of DDOS Attack using SimEvents", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.2, pp.5-14, 2013