Recent Research Articles in Internet of Things (IoT)
International Journal of Computer Networks & Communications (IJCNC)
(Scopus, ERA Listed)
ISSN 0974 – 9322 (Online); 0975 – 2293 (Print)
Availability Aspects through Optimization Techniques Based Outlier Detection Mechanism in Wireless and Mobile Networks
Neeraj Chugh, Adarsh Kumar and Alok Aggarwal
University of Petroleum & Energy Studies, Dehradun, India
Radio Frequency IDentification (RFID) and Wireless Sensor Networks (WSN) are the two most prominent wireless technologies for implementing a complete smart environment for the Internet of Things (IoT). Both RFID and WSN are resource constraint devices, which forces us to go for lightweight cryptography for security purposes. Security in terms of confidentiality, integrity, authentication, authorization, and availability. Key management is one of the major constraints for resource constraint mobile sensor devices. This work is an extension of the work done by Kumar et al. using efficient error prediction and limit of agreement for anomaly score. This work ensures cryptographic property, availability, in RFID-WSN integrated network through outlier detection mechanism for 50 to 5000 nodes network. Through detection ratios and anomaly scores system is tested against outliers. The proposed outlier detection mechanism identifies the inliers and outliers through anomaly score for protection against Denial-of-Service (DoS) attack. Intruders can be detected in few milliseconds without giving any conflict to the access rights. In terms of throughput, a minimum improvement of 6.2% and a maximum of 219.9% is observed for the proposed protocol as compared to Kumar et al. Protocol and in terms of percentage of Packet Delivery Ratio (PDR), a minimum improvement of 8.9% and a maximum of 19.5% is observed for the proposed protocol as compared to Kumar et al. protocol.
WSN, MANET, RFID, ANOMALY, SECURITY
For More Details: http://aircconline.com/ijcnc/V10N6/10618cnc05.pdf
Volume Link: http://airccse.org/journal/ijc2018.html
 A. Kumar, K. Gopal and A. Aggarwal, “Outlier Detection and Treatment for Lightweight Mobile Ad Hoc Networks,” in In International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, Greater Noida,India,11-12 January 2013, pp.750-763.
 A. Kumar, A. Agarwal and Charu, “Efficient Hierarchical Threshold Symmetric Group Key Management Protocol for Mobile Ad Hoc Networks,”Inter. Conf. on Contemporary Computing – IC3 2012, Noida,India,6-8 August 2012, pp. 335-346.
 D. Bonch and M. Franklin, “Identity-based encryption from weil pairing,” Advances in CryptologyCrypto 2001,Santa Barbara, California, USA,August 2001, pp. 213-229.
 Merwe, J. V. D., D. D. and M. S, ” A survey on peer-to-peer key management for mobile ad hoc networks,” ACM computing surveys (CSUR), Vol. 39, No. 1, 1, April 2007, pp. 1-45.
 H. Deng, A. Mukherjee and D. Aggarwal, “Threshold and identity based key management and authentication for wireless ad hoc networks,” in International conference on information technology:Coding and Computing (ITCC’s 04), Las Vegas, Nevada, April 2004, pp. 1-5.
 Y. Zhang, W. Liu, W. Lou and Y. Fang, “Securing mobile ad hoc networks with certificateless public keys,” IEEE Transaction on Dependable and Secure Computing, Vol. 3, No. 4,Dec. 2006, pp. 386-399.
 H. Harney, C. Muckenhirn, “Group key management protocol (GKMP) architecture”, Network Working Group, July 1997.[Online].Available:https://www.rfc-editor.org/info/rfc2094. [Accessed:Jan. 1, 2018].
 H. Harney, C. Muckenhirn, “Group Key Management Protocol(GKMP) Specification” ,Internet Request for Comments 2093,” July 1997.[Online]. Available:https://www.rfc-editor.org/info/rfc2093.%5BAccessed: Jan. 1, 2018].
 H. Harney ,U. Meth, A. Colegrove and G. Gross, “Group Secure Association Key Management Protocol(GKMP)”, Internet Request for Comments 4535,” June 2006. [Online].Available:https://www.rfc-editor.org/info/rfc4535. [Accessed: Jan. 1, 2018].
 B. Weis, S. Rowles and T. Hardjono, “The Group Domain of Interpretation(GDOI)”,Internet Request for Comments 6407, Oct.2011.[Online]. Available:https://www.rfc-editor.org/info/rfc6407.%5BAccessed: Jan. 1, 2018].
 Bryans, J. W., Fitzgerald and J. S., “Formal engineering of XACML access control policies in VDM++,” in International Conference on Formal Engineering Methods, Florida, USA, Berlin, Heidelberg, Nov. 2007, pp. 37–56.
 K. Fisler, S. Krishnamurthi, L. A. Meyerovich and M. C. Tschantz, “Verification and change-impact analysis of access control policies,” in Proc. of 27th International Conference on Software Engineering, MO, USA,May 2005, pp. 196-205.
 D. Jackson, , Software Abstractions: Logic, Languages, and Analysis, MIT Press, ISBN: 978-0-262-10114-1, 2006. .
 D. Jackson, “Micromodels of Software: Lightweight Modelling and Analysis with Alloy,” MIT Lab, Jan. 2002. [Online]. Available:https://courses.cs.washington.edu/courses/cse503/04sp/readings/alloyref.pdf. [Accessed: Jan. 1, 2018].
 D. Jackson, “Alloy: a lightweight object modelling notation,” ACM Trans. Soft. Eng. Methodol., Vol.11, No. 2, April 2002, pp. 256-290.
 V. Chandola, A. Banerjee and V. Kumar, “Anomaly Detection: A Survey,” ACM computing surveys,Vol. 41, No. 3, 2009, pp. 1-72.
 Y. Zhang, N. Meratnia and P. Havinga, “Outlier Detection Techniques for Wireless Sensor Networks:A Survey,” IEEE Communication Surveys & Tutorials, Vol. 12, No. 2, 2010, pp. 159-170.
 P. Gogoi, B. Borah and D. K. Bhattacharyya, “Anomaly Detection Analysis of Intrusion Data using Supervised and Unsupervised Approach,” Journal of Convergence Information Technology, Vol. 5,No. 1, Feb. 2010, pp. 95-110.
 P. Gogoi, D. K. Bhattacharyya, B. Borah and J. K. Kalita, ” A Survey of Outlier Detection Methods in Network Anomaly Identification,” The Computer Journal, Vol. 54, No. 4, April 2011, pp. 570-588.
 D. M. Hawkin, Identification of Outliers, London: Chapman and Hall, 1980.
 V. A. Traag, A. Browet, F. Calabrese and F. Morlot, “Social Event Detection in Massive Mobile Phone Data Using Probabilistic Location Interference,” in SocialCom/PASSAT, 9-11 October 2011.
 B. Krishnamachari and S. Iyengar, “Distributed Bayesian algorithms for fault tolerant event region detection in wireless sensor networks,” IEEE Transactions on Computers, Vol. 53, No. 3, March 2004, pp. 241-250.
 F. Martincic and L. Schwiebert, “Distributed event detection in sensor networks,” in Proceedings of Systems and Network Communication, French, Polynesia, Nov. 2006, pp. 1-6.
 M. Ding, D. Chen, K. Xing and X. Cheng, ” Localized fault tolerant event boundary detection in sensor networks,” in IEEE conference of computer and communications socities, Florida, USA,March 2005, pp. 902-913.
 A. P. R. Silva, M. H. T. Martins, B. P. S. Rocha, A. A. F. Loureiro, L. B. Ruiz and H. C. Wong,”Decentralized intrusion detection in wireless sensor networks,” 1st ACM international workshop on Quality of Service and Security in Wireles., Quebec, Canada Oct. 2005, pp. 16-23.
 J. Chen, S. Kher and A. Somani, “Distributed fault detection of wireless sensor networks,”Proceedings of the 2006 workshop on dependability issues in wireless ad hoc networks and sensor networks, CA, USA, Sep. 2006, pp. 65-72.
 X. Luo, M. Dong and Y. Huang, “On distributed fault tolerant detection in wireless sensor networks,”IEEE Transactions on computers, Vol. 55, No.1, Jan. 2006 pp. 58-70.
 J. Raja, X. R. Wang, O. Obst and P. Valencia, “Wireless sensor network anomalies: Diagnosis and detection strategies,“Intelligence-Based Systems Engineering, Berlin, Heidelberg, 2011, pp. 309-325.
 W. Hu, T. Tan, L.Wang and S. Maybank, “A survey on visual surveillance of object motion and behaviors,” IEEE transavtion, Vol. 34, No. 3,July 2004, pp. 334-352.
 D. M. Hawkins, Ident fication of outliers, London: Chapman and Hall, 1980.
 E. M. Knorr and R. T. Ng, “Algorithm for mining distance based outliers in large datasets,” 24th international conference on very large databases, New York, USA, 1998, pp. 392-403.
 M. M. Breunig, H. P. Kriegel, R. T. Ng and J. Sander, “LOF: Identifying Density Based Local Outliers,” ACM SIGMOD, Dallas, TX, USA, May 2000, pp. 93-104.
 B. Wang and W. Perrizo, “RDF: a density-based outlier detection method using vertical data representation,” in Fourrth IEEE InternationalConference on Data Mining, Nov. 2004, pp. 1-4.
 S. Rajagopalan, R. Karwoski, B. Bartholmai and R. Robb, “Quantitative image analytics for strtified pulmonary medicine,” in IEEE Int. Symposium on Biomedical Imaging (ISBI), Barcelona, Spain,May 2012, pp. 1779-1782.
 J. W. Branch, C. Giannelia, B. Szymanski, R. Wolff and H. Kargupta, “In-network outlier detection in wireless sensor networks,” Knowledge and information systems, Vol. 34, No. 1, Jan. 2013, pp. 23-54.
 H. Ayadi, A. Zouinkhi and B. Boussaid, “A Machine Learning Methods: Outlier detection in WSN,”in 16th international conference on Sciences and Techniques of Automatic control, Monastir, Tunisia,December 2015, pp. 722-727.
 C. Titouna, M. Aliouat and M. Gueroui, “Outlier Detection Approach Using Bayes Classifiers,”Wireless Pers. Communications, Vol. 85, No. 3, June 2015, pp. 1009-1023.
 J. C. M. Teo and C. H. Tan, “Energy-efficient and scalable group key agreement for large ad hoc networks,” in Proceedings of the 2nd ACM international workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks, Quebec, Canada, October 2005, pp. 114-121.
 E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik, Vol. 1,No. 1, December 1959,pp. 269-271.
 J. Spinrad, “Recognition of circle graphs,” Journal of Algorithms, Vol. 16, No. 2, March 1994, pp.264-282.
 W. J. Gutjahr, “A graph-based Ant System and its convergence,“ Future Generation Computer Systems, Vol. 16, No. 9, June 2000, pp. 873-888.
 A. Shamir, “How to share a secret,” Communications of the ACM, Vol. 22, No. 11, November 1979,pp. 612- 613.
 J. V. D. Merwe, D. Dowoud and S. McDonald, “A Survey on Peer to Peer key management for Mobile Ad Hoc Networks,” ACM Computing Surveys, Vol. 39, No. 1, Article 1, April 2007, pp. 1-45.
 “The Network Simulator – ns-2,” [Online]. Available: https://www.isi.edu/nsnam/ns/. [Accessed 18 7 2018].
 “scipy.cluster.hierarchy.dendrogram.html,”[Online].Available: https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.dendrogram.html.[Accessed 18 7 2018].
 A. Kumar, K. Gopal and A. Aggarwal,” Novel Trusted Hierarchy Construction for RFID Sensor–Based MANETs Using ECCs,” ETRI Journal, Vol. 37, No. 1, July 2015, pp. 186-196.
 A. Kumar, K. Gopal and A. Aggarwal, ” Simulation and analysis of authentication protocols for mobile Internet of Things (MIoT),” 2014 IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC), JUIT, Waknaghat, India, 2014, pp.423-428.
 A. Kumar, K. Gopal and A. Aggarwal, “Design and Analysis of Lightweight Trust Mechanism for Accessing Data in MANETs,” KSII Transactions on Internet & Information Systems, Vol. 8, No. 3, March 2014, pp. 1119-1143.
 A. Kumar, K. Gopal and A. Aggarwal, “Cost and Lightweight Modeling Analysis of RFID Authentication Protocols in Resource Constraint Internet of Things,” Journal of Communications Software and Systems, Vol. 10, No. 3, September 2014, pp. 179-143.
 A. Kumar, K. Gopal and A. Aggarwal, ” A complete, efficient and lightweight cryptography solution for resource contrainsts Mobile Ad-Hoc Networks”, 2nd IEEE International Conference on Parallel,Distributed and Grid Computing (PDGC), JUIT, Waknaghat, India, Feb. 2013, pp. 854-860.
 A. Kumar, K. Gopal and A. Aggarwal,” Design and Analysis of Lightweight Trust Mechanism for Secret Data using Lightweight Cryptographic Primitives in MANETs”, IJ Network Security, Vol. 18,No. 1, Jan. 2016, pp.1-18.
 A. Kumar, K. Gopal and A. Aggarwal,”A novel lightweight key management scheme for RFIDsensor integrated hierarchical MANET based on internet of things”, International Journal of Advanced Intelligence Paradigms, Vol. 9, No. 2-3, 2017, pp. 220-245.
 N. Chugh, A. Kumar and A. Aggarwal, “Security aspects of a RFID-sensor integrated low-powered devices for internet-of-things”, 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC), JUIT, Waknaghat, India, Dec. 2016, pp. 759-763.
Neeraj Chugh is an Assistant Professor in University of Petroleum & Energy Studies, Dehradun, India and enrolled in PhD (CSE) from Uttrakhand Technical University (UTU), Uttrakhand, India. He received his M. Tech. (CSE) from Kurukshetra University Kurukshetra, India in 2001. His research interests includes Database Management system, Data Mining, and Outlier/Anomaly detection and event detection in sensor networks.
Adarsh Kumar received his ME degree in Software Engineering from Thapar University, Patiala, Punjab, India, in 2005 and earned his PhD degree from JIIT university, Noida, India in 2016 followed by Post Doctoral from AIT, Ireleand during 2016-2018. From 2005 to 2016, he has been associated with the Department of Computer Science Engineering & Information Technology, Jaypee Institute of Information Technology, Noida, UttarPardesh, India, where he worked as Assistant Professor. Currently he is working with University of Petroleum & Energy Studies,Dehradun, India as Associate Professor in CSE department. His main research interests are cryptography, network security, and adhoc networks.
Alok Aggarwal received his bachelors’ and masters’ degrees in Computer Science& Engineering in 1995 and 2001 respectively and his PhD degree in Engineering from IITRoorkee, Roorkee, India in 2010. He has academic experience of 18 years, industry experience of 4 years and research experience of 5 years. He has contributed more than 150 research contributions in different journals and conference proceedings. Currently he is working with University of Petroleum & Energy Studies, Dehradun, India as Professor in CSE department. His main research interests are wired/wireless networks, security, and coding theory.
Ensemble of Probabilistic Learning Networks For Iot Edge Intrusion Detection
Tony Jan and A.S.M Sajeev, Melbourne Institute of Technology, Australia
This paper proposes an intelligent and compact machine learning model for IoT intrusion detection using an ensemble of semi-parametric models with Ada boost. The proposed model provides an adequate real time intrusion detection at an affordable computational complexity suitable for the IoT edge networks. The proposed model is evaluated against other comparable models using the benchmark data on IoT-IDS and shows comparable performance with reduced computations as required.
Adaboosted ensemble learning, IoT edge security, machine learning for IoT
For More Details: http://aircconline.com/ijcnc/V10N6/10618cnc08.pdf
Volume Link: http://airccse.org/journal/ijc2018.html
 Muhammad Umar Farooq, Muhammad Waseem, Anjum Khairi, and Sadia Mazhar, (2015) “A critical analysis on the security concerns of internet of things (IoT)”, International Journal of Computer Applications, Vol. 111, No. 7.
 Manos Antonakakis, Tim April, Michael Bailey, Matt Bernhard, Elie Bursztein, Jaime Cochran, Zakir Durumeric, J Alex Halderman, Luca Invernizzi, Michalis Kallitsis, et al., (2017) “Understanding the mirai botnet”, in USENIX Security Symposium.
 Antonio Brogi and Stefano Forti, (2017) “QoS-aware deployment of IoT applications through the fog”, IEEE Internet of Things Journal, Vol. 4, No. 5, pp. 1185–1192.
 Farhoud Hosseinpour, Payam Vahdani Amoli, Juha Plosila, Timo Ham ¨ al¨ ainen, and Hannu ¨ Tenhunen, (2016) “An Intrusion Detection System for Fog Computing and IoT based Logistic Systems using a Smart Data Approach”, International Journal of Digital Content Technology and its Applications, Vol. 10.
 Bernard W Silverman, (2018) Density estimation for statistics and data analysis, Routledge.
 Ron Kohavi, David H Wolpert, et al., (1996) “Bias plus variance decomposition for zero-one loss functions”, in ICML, Vol. 96, pp. 275–83.
 Yair Meidan, Michael Bohadana, Yael Mathov, Yisroel Mirsky, Dominik Breitenbacher, Asaf Shabtai, and Yuval Elovici, (2018) “N-BaIoT: Network-based Detection of IoT Botnet Attacks Using Deep Autoencoders”, arXiv preprint arXiv:1805.03409.
 Alya Geogiana Buja, Shekh Faisal Abdul-Latip, and Rabiah Ahmad, (2018) “A Security Analysis of IoT Encryption: Side-channel Cube Attack on Simeck32/64”, arXiv preprint arXiv:1808.03557.
 Ryan Williams, Emma McMahon, Sagar Samtani, Mark Patton, and Hsinchun Chen, (2017) “Identifying vulnerabilities of consumer Internet of Things (IoT) devices: A scalable approach”, in Intelligence and Security Informatics (ISI), 2017 IEEE International Conference on, pp. 179–181.
 Sudhi R Sinha and Youngchoon Park, (2017) Building an Effective IoT Ecosystem for Your Business, Springer.
 Briana Arrington, LiEsa Barnett, Rahmira Rufus, and Albert Esterline, (2016) “Behavioral modeling intrusion detection system (bmids) using internet of things (iot) behavior-based anomaly detection via immunity-inspired algorithms”, in Computer Communication and Networks (ICCCN), 2016 25th International Conference on, pp. 1–6.
 Otavio Carvalho, Manuel Garcia, Eduardo Roloff, Emmanuell Diaz Carre ´ no, and ˜Philippe OA Navaux, (2017) “IoT Workload Distribution Impact Between Edge and Cloud Computing in a Smart Grid Application”, in Latin American High Performance Computing Conference, pp. 203–217.
 Eduardo Cuervo, Aruna Balasubramanian, Dae ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl, (2010) “MAUI: making smartphones last longer with code offload”, in Proceedings of the 8th international conference on Mobile systems, applications,and services, pp. 49–62.
 Mark S Gordon, Davoud Anoushe Jamshidi, Scott A Mahlke, Zhuoqing Morley Mao, and Xu Chen, (2012) “COMET: Code Offload by Migrating Execution Transparently.”, in OSDI,Vol. 12, pp. 93–106.
 Sokol Kosta, Andrius Aucinas, Pan Hui, Richard Mortier, and Xinwen Zhang, (2012) “Thinkair: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading”, in Infocom, 2012 Proceedings IEEE, pp. 945–953.
 Takayuki Nishio, Ryoichi Shinkuma, Tatsuro Takahashi, and Narayan B Mandayam, (2013) “Service-oriented heterogeneous resource sharing for optimizing service latency in mobile cloud”, in Proceedings of the first international workshop on Mobile cloud computing & networking, pp. 19–26.
 Elike Hodo, Xavier Bellekens, Andrew Hamilton, Pierre-Louis Dubouilh, Ephraim Iorkyase, Christos Tachtatzis, and Robert Atkinson, (2016) “Threat analysis of IoT networks using artificial neural network intrusion detection system”, in Networks, Computers and Communications (ISNCC), 2016 International Symposium on, pp. 1–6.
 Nof Abuzainab, Walid Saad, Choong-Seon Hong, and H Vincent Poor, (2017) “Cognitive hierarchy theory for distributed resource allocation in the internet of things”, arXiv preprint arXiv:1703.07418.
 Abdulla Amin Aburomman and Mamun Bin Ibne Reaz, (2016) “A novel SVM-kNN-PSO ensemble method for intrusion detection system”, Applied Soft Computing, Vol. 38, pp.360–372.
 Wathiq Laftah Al-Yaseen, Zulaiha Ali Othman, and Mohd Zakree Ahmad Nazri, (2017) “Multi-level hybrid support vector machine and extreme learning machine based on modified K-means for intrusion detection system”, Expert Systems with Applications, Vol. 67, pp.296–303.
 Milad Yousefi, Moslem Yousefi, Ricardo Poley Martins Ferreira, Joong Hoon Kim, and Flavio S Fogliatto, (2018) “Chaotic genetic algorithm and Adaboost ensemble metamodeling approach for optimum resource planning in emergency departments”, Artificial intelligence in medicine, Vol. 84, pp. 23–33.
 YANG Xinwu, M A Zhuang, and YUAN Shun, (2016) “Multi-class Adaboost Algorithm Based on the Adjusted Weak Classifier”, Journal of Electronics & Information Technology,Vol. 38, No. 2, pp. 373–380.
 Anthony Zaknich, (1998) “Introduction to the modified probabilistic neural network for general signal processing applications”, IEEE Transactions on Signal Processing, Vol. 46,No. 7, pp. 1980–1990.
 Elike Hodo, Xavier Bellekens, Andrew Hamilton, Pierre-Louis Dubouilh, Ephraim Iorkyase,Christos Tachtatzis, and Robert Atkinson, (2016) “Threat analysis of IoT networks using artificial neural network intrusion detection system”, in Networks, Computers and Communications (ISNCC), 2016 International Symposium on, pp. 1–6.
A Future Mobile Packet Core Network Based on Ip-In-Ip Protocol
Mohammad Al Shinwan1 and Kim Chul-Soo2
1Amman Arab University, Amman, Jordan. 2Inje University, Gimhae, Republic of Korea.
The current Evolved Packet Core (EPC) 4th generation (4G) mobile network architecture features complicated control plane protocols and requires expensive equipment. Data delivery in the mobile packet core is performed based on a centralized mobility anchor between eNode B (eNB) elements and the network gateways. The mobility anchor is performed based on General Packet Radio Service tunnelling protocol (GTP), which has numerous drawbacks, including high tunnelling overhead and suboptimal routing between mobile devices on the same network. To address these challenges, here we describe new mobile core architecture for future mobile networks. The proposed scheme is based on IP encapsulated within IP (IP-in-IP) for mobility management and data delivery. In this scheme, the core network functions via layer 3 switching (L3S), and data delivery is implemented based on IP-in-IP routing, thus eliminating the GTP tunnelling protocol. For handover between eNB elements located near to one another, we propose the creation of a tunnel that maintains data delivery to mobile devices until the new eNB element updates the route with the gateway, which prevents data packet loss during handover. For this, we propose Generic Routing Encapsulation (GRE) tunnelling protocol. We describe the results of numerical analyses and simulation results showing that the proposed network core architecture provides superior performance compared with the current 4G architecture in terms of handover delay, tunnelling overhead and total transmission delay.
5G network, mobile core network, IP-in-IP, GRE
For More Details: http://aircconline.com/ijcnc/V10N5/10518cnc05.pdf
Volume Link: http://airccse.org/journal/ijc2018.html
 Cisco, (2016) “Visual Networking Index: Global Mobile Data Traffic Forecast Update”, 2015 – 2020,White paper.
 Ericsson, Huawei and Qualcomm, (2015) “The Road to 5G: Drivers, Applications, Requirements and Technical Development”, Technical Report.
 Shinwan, M.A. and Chul-Soo, K. (2017) “Enhanced Mobile Packet Core Network Scheme for Next-Generation Mobile Communication Systems”. International Journal of Electronics Communication and Computer Engineering (IJECCE), 8, 56-61.
 3GPP TS 23.002, (2016) “Technical Specification Group Services and System Aspects; Network architecture”, Technical Report, Rel-13 Ver. 13.5.0.
 Seite,P., P. Bertin, (2010) “Dynamic Mobility Anchoring”, IETF. https://tools.ietf.org/html/draft-seite-netext-dma-00
 D. Liu, P. Seite, H. Yokota and J. Korhonen, (2014) “Requirements for distributed mobility management”, IETF RFC 7333, https://doi.org/10.17487/rfc7333.
 F. Rebecchi, M. Dias de Amorim, V. Conan, A. Passarella, R. Bruno and M. Conti, (2015)” Data of loading Techniques in Cellular Networks: A Survey”. IEEE Communications Surveys and Tutorials,vol. 17, no. 2, pp. 580-603. https://doi.org/10.1109/comst.2014.2369742.
 K. Daoud, P. Herbelin and N. Crespi. (2015) UFA: Ultra Flat Architecture for high bitrate services in mobile networks. IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, pp.1-6. https://doi.org/10.1109/pimrc.2008.4699577.
 Gohar, M., Choi, JG. & Koh, SJ, (2016) “TRILL-Based Mobile Packet Core Network for 5G Mobile Communication Systems”. Wireless Pers Commun. volume 87, issue 1, (p.p 125 – 144),https://doi.org/10.1007/s11277-015-3035-5.
 Heeyoung Jung, Moneeb Gohar and Seok-Joo Koh, (2014) “RB-core: Routing bridge-based 5G mobile core network”, International Conference on Information and Communication Technology Convergence (ICTC), (pp.223-228), https://doi.org/10.1109/ictc.2014.6983122.
 Cisco, “Catalyst 2948G-L3 Switch High-Performance Layer 3 Switching”, Technical Report. http://www.cisco.com/en/US/products/hw/switches/ps606/products_data_sheet09186a008009267f.html
 Perkins, Charles, “IP encapsulation within IP”, (2003) IETF RFC 2003,https://doi.org/10.17487/rfc2003.
 3gpp.TS 23.401, (2016) “General Packet Radio Service (GPRS) enhancements for Evolved Universal Terrestrial Radio Access Network (EUTRAN) access”, Rel-13, Ver.13.6.1.
 S. Hanks, T. Li, D. Farinacci, P. Traina. (1994) “Generic routing encapsulation (GRE)”, IETF RFC 2784, https://doi.org/10.17487/rfc1701.
 Nuutti Varis, Jukka Manner and Johanna Heinonen., (2011) “A layer-2 approach for mobility and transport in the mobile backhaul”, ITS Telecommunications (ITST), 2011 11th International Conference, (pp.268-273), https://doi.org/10.1109/itst.2011.6060066.
 C. Makaya and S. Pierre. (2008) An Analytical Framework for Performance Evaluation of IPv6-Based Mobility Management Protocols. IEEE Transactions on Wireless Communications, vol. 7, no.3, pp. 972-983. https://doi.org/10.1109/twc.2008.060725.
 Ns-3 Open Source Network Simulator. https://www.nsnam.org/
 M. A. Shinwan, T.-D. Huy, and K. Chul-Soo, (2017) “A Flat Mobile Core Network for Evolved Packet Core Based SAE Mobile Networks,” Journal of Computer and Communications, vol. 05, no.05, pp. 62-73.
 B. Davaasambuu, F. Semaganga, and T. Sato, (2015) “Adaptive Handover Hysteresis and Call Admission Control for Mobile Relay Nodes,” International journal of Computer Networks & Communications, vol. 7, no. 6, pp. 87–98.
Mohammad Al Shinwan, received his B.S degree in Computer Science from Al al-Bayt university, Jordan, in 2009 and the master degree in 2013 from the institute of Mathematical and Computer Science, University of Sindh in Pakistan. He received a Ph.D. in Computer Networks from Inje University, Korea. He is currently an assistant professor in the Faculty of Computer Science and Informatics, Amman Arab University, Jordan. His current research interests include mobility management, network management and OAM (Operation, Administration and Maintenance) for future mobile network.
Chul-Soo Kim is a professor in the School of Computer Engineering of Inje University in Gimhae, Korea. He received Ph.D. from the Pusan National University (Pusan, Korea) and worked for ETRI (Electronics and Telecommunication research Institute) from 1985 – 2000 as senior researcher for developing TDX exchange. Aside from the involvement in various national and international projects, his primary research interests include network protocols, traffic management, OAM issue, and NGN charging. He is a member of ITU-T SG3, SG11, SG13 and a Rapporteur of ATM Lite from 1998 – 2002, and CEO in WIZNET from 2000 – 2001. He is currently the chairperson of BcN Reference Model in Korea, and a Rapporteur of ITU-T SG3 NGN Charging.
Multi-Constraints Adaptive Link Quality Index Based Mobile-Rpl Routing Protocol for Low Power Lossy Networks
Sneha K1 . and B G Prasad2
1BNM Institute of Technology, Bengaluru, Karnataka, India
2BMS College of Engineering, Bengaluru, Karnataka, India
The importance of IPv6 Routing Protocol for Low power and Lossy Networks (LLNs), also called RPL, has motivated in the development of a robust and quality of service (QoS) oriented Multi-Constraints Adaptive Link Quality Index (MALQI) based routing protocol. Unlike classical RPL protocols, MALQI enables mobile-RPL while ensuring fault-resilient, reliable and QoS communication over LLNs. MALQI protocol exploits key novelties such as signal strength based mobile node positioning, average received signal strength indicator (ARSSI) and ETX based objective function for fault tolerant best forwarding path selection. The functional architecture of MALQI enables it to be used as the parallel to the link layer RPL that even in the case of link failure can assist efficient data delivery over LLNs. Once detecting link outage, MALQI can execute node discover and best forwarding path selection to assist QoS delivery. Contiki-Cooja based simulation reveals that MALQI based mobile-RPL outperforms other state-of-art routing protocols.
Mobile-RPL; Adaptive Link Quality; Low Power Lossy Network; Routing Protocol; MALQI.
For More Details: http://aircconline.com/ijcnc/V10N5/10518cnc03.pdf
Volume Link: http://airccse.org/journal/ijc2018.html
 Heinzelman W., Kulik, J., Balakrishnan, H.: Adaptive Protocols for Information Dissemination in Wireless Sensor Networks. In proc. of the 5th ACM/IEEE Mobicom Conference (MobiCom ’99), Seattle, WA, August, pp. 174-85 (1999)
 Intanagonwiwat, C., Goninan R., Estrin, D.: Directed diffusion: a scalable and robust communication paradigm for sensor networks. In proc. of the ACM MobiCom ’00, Boston, MA, pp.56-67. Y (2000)
 Yao, Y., Gehrke, J.: The cougar approach to in-network query processing in sensor networks. In ACM SIGMOD Record, vol. 31, no. 3. (2002)
 Heinzelman, W., Chandrakasan A., Balakrishnan, H.: Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In proc. of the 33rd Hawaii International Conference on System Sciences (HICSS ’00) (2000)
 Lindsey, S., Raghavendra, C., PEGASIS: Power-Efficient Gathering in Sensor Information Systems.In proc. of the IEEE Aerospace Conference. vol. 3, pp. 1125-1130. (2002) Winter, T., Thubert, P., Brandt, A., Clausen, T., Hui, J., Kelsey, R., Levis, P., Pister, K., Struik R.,and Vasseur, J.: RPL: IPv6 Routing Protocol for Low power and Lossy Networks. RFC 6550, IETF ROLL WG. (2012)
 Vasseur, J.P: Terminology in Low power And Lossy Networks. Draftietf-roll-terminology- 06.txt. (2011)
 Lee, K.C., Sudhaakar, R., Ning, J., Dai, L., Addepalli, S., Vasseur, J. P., Gerla, M.: A Comprehensive Evaluation of RPL under Mobility. Hindawi Publishing Corporation International Journal of Vehicular Technology, Vol. 2012.
 Vasseur, J., Dunkels, A.: Interconnecting Smart Objects with IP: The Next Internet. Morgan Kaufmann, 1 edition. (2010)
 Tsiftes, N., Eriksson, J., Dunkels, A.: Low-power wireless ipv6 routing with contikiRPL. in Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, ser. IPSN ’10. New York, NY, USA: ACM, pp. 406– 407. (2010)
 Pavkovi´c, B., Theoleyre, F., Duda, A.: Multipath opportunistic RPL routing over IEEE 802.15.4. in Proceedings of the 14th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, ser. MSWiM ’11. New York, NY, USA: ACM, pp. 179–186. (2011)
 Duquennoy, S., Landsiedel, O., Voigt, T.: Let the tree bloom: Scalable opportunistic routing with ORPL. in Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, ser.SenSys ’13. New York, NY, USA: ACM, pp. 2:1–2:14. (2013)
 Hong, K.S., Choi, L.: Dag-based multipath routing for mobile sensor networks. in ICT Convergence (ICTC), 2011 International Conference on, pp. 261–266. (2011)
 Safdar, V., Bashir, F., Hamid, Z., Afzal, H., Pyun, J.Y.: A hybrid routing protocol for wireless sensor networks with mobile sinks. In Wireless and Pervasive Computing (ISWPC), 2012 7th International Symposium on, pp. 1–5. (2012)
 Ben Saad, L., Chauvenet, C., Tourancheau, B.: Simulation of the RPL Routing Protocol for IPv6 Sensor Networks: two cases studies. in International Conference on Sensor Technologies and Applications SENSORCOMM 2011. Nice, France: IARIA (2011)
 Ben Saad, L., Tourancheau, B.: Sinks Mobility Strategy in IPv6- based WSNs for Network Lifetime Improvement. in International Conference on New Technologies, Mobility and Security (NTMS).Paris, France: IFIP, pp. 1-5. (2011)
 Korbi, I.E., Ben Brahim, M., Adjih C., Saidane, L.A.: Mobility Enhanced RPL for Wireless Sensor Networks. 2012 Third International Conference on the Network of the Future (NOF), Gammarth, pp.1-8. (2012)
 Tripathi, J., de Oliveira, J., Vasseur, J.: A Perfor- mance Evaluation Study of RPL: Routing Protocol for Low Power and Lossy Networks. Information Sciences and Systems (CISS), 2010 44th Annual Conference on, pp. 1–6. (2010)
 Tsiftes, N., Eriksson, J., Dunkels, A.: Poster Abstract: Low-Power Wireless IPv6 Routing with ContikiRPL. IPSN10, Stockholm, Sweden. p. 1216. (2010)
 Kharrufa, H., Al-Kashoash, H., Al-Nidawi, Y., Mosquera, M.Q., Kemp, A.H.: Dynamic RPL for multi-hop routing in IoT applications. 2017 13th Annual Conference on Wireless On-demand Network Systems and Services (WONS), Jackson, WY, USA, pp. 100-103. (2017)
 Gaddour, O., Koubäa, A., Rangarajan, R., Cheikhrouhou, O., Tovar, E., Abid, M.: Co-RPL: RPL routing for mobile low power wireless sensor networks using Corona mechanism. Proceedings of the 9th IEEE International Symposium on Industrial Embedded Systems (SIES 2014). Pisa. pp. 200-209.(2014)
 Somaa, F., Korbi, I. E. l., Adjih, C., Saidane, L.A.: A modified RPL for Wireless Sensor Networks with Bayesian inference mobility prediction. 2016 International Wireless Communications and Mobile Computing Conference (IWCMC). Paphos, pp. 690-695. (2016)
 Barcelo, M., Correa, A., Vicario, J. L., Morell, A., Vilajosana, X.: Addressing Mobility in RPL With Position Assisted Metrics. In IEEE Sensors Journal, vol. 16, no. 7, pp. 2151-2161. (2016)
 Lohith, Y.S., Narasimman, T.S., Anand, S.V.R., Hedge, M.: Link Peek: A Link Outage Resilient IP Packet Forwarding Mechanism for 6LoWPAN/RPL Based Low-Power and Lossy Networks (LLNs).IEEE International Conference on Mobile Services. New York. NY. pp. 65-72. (2015)
 Lee et al., K.C.: RPL under Mobility. In proc. of the IEEE Consumer Communications and Networking Conference (CCNC) (2012)
 Levis, P., Clausen, T., Hui, J., Gnawali, O., Ko, J.: The Trickle Algorithm. RFC 6206 (Proposed Standard). (2011)
 Gungor, V.C., Hancke, G.P.: Industrial Wireless Sensor Networks: Applications, Protocols, and Standards. CRC Press, Inc., Boca Raton, FL, USA, 1st edition. (2013)
 Raman, B., Chebrolu, K., Madabhushi, N., Gokhale, D.Y., Valiveti, P. K., Jain, D.: Implications of link range and (in) stability on sensor network architecture. WiNTECH ’06, ACM. New York, NY.USA. pp. 65-72. (2006)
 Srinivasan, K., Levis, P.: RSSI is under appreciated. In Proceedings of the Third Workshop on Embedded Networked Sensors. EmNets. (2006)
 Sneha K, Dr. B.G.Prasad.: An Efficient Hand-off Optimization Based RPL Routing Protocol for Optimal Route Selection in Mobility Enabled LLNs in IEEE International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICSPICC-2016), Jalgaon,India: IEEE. (2016).
A Security Analysis of IoT Encryption: Side Channel Cube Attack on SIMECK32/64
Alya Geogiana Buja1,2, Shekh Faisal Abdul-Latip1 and Rabiah Ahmad1
1Universiti Teknikal Malaysia Melaka, Malaysia and 2Universiti Teknologi MARA, Malaysia
Simeck, a lightweight block cipher has been proposed to be one of the encryption that can be employed in the Internet of Things (IoT) applications. Therefore, this paper presents the security of the Simeck32/64 block cipher against side-channel cube attack. We exhibit our attack against Simeck32/64 using the Hamming weight leakage assumption to extract linearly independent equations in key bits. We have been able to find 32 linearly independent equations in 32 key variables by only considering the second bit from the LSB of the Hamming weight leakage of the internal state on the fourth round of the cipher. This enables our attack to improve previous attacks on Simeck32/64 within side-channel attack model with better time and data complexity of 235 and 211.29 respectively.
Block Cipher, IoT, Lightweight Encryption, Security Analysis, Simeck
For More Details: http://aircconline.com/ijcnc/V10N4/10418cnc06.pdf
Volume Link: http://airccse.org/journal/ijc2018.html
 G. Yang, B. Zhu, V. Suder, M. Aagaard, G. Gong, The Simeck Family of Lightweight Block Ciphers,CHES 2015. LNCS 9293 (2015) 307-329.
 R. Beaulieu, D. Shors, J. Smith, S. Treatman- Clark, B. Weeks, L. Wingers, The SIMON and SPECK Families of Lightweight Block Ciphers Cryptology ePrint Archive, Report 2013/404.
 V. Nalla, R. Sahu, V. Saraswat, Differential Fault Attack on SIMECK, Proceedings of the Third Workshop on Cryptography and Security in Computing Systems (2016) 45-48.
 I. Dinur, A. Shamir, Cube Attacks on Tweakable Black Box Polynomials, EUROCRYPT 2009.LNCS 5479 (2009) 278-299.
 J. Aumasson, I. Dinur, M. Meier, A. Shamir, Cube Testers and Key Recovery Attacks on Reducedround MD6 and Trivium, FSE 2009. LNCS 5665 (2009) 307-329.
 Z. Ahmadian, S. Rasoolzadeh, M. Salmasizadeh, M. Aref, Automated Dynamic Cube Attack on Block Ciphers: Cryptanalysis of SIMON and KATAN, Cryptology ePrint Archive, 2015/040.
 S.F. Abdul-Latip, M. Reyhanitabar, W. Susilo, J. Seberry, Extended Cubes: Enhancing the Cube Attack by Extracting Low-Degree Non-Linear Equations, ASIACCS 2011 (2011) 296-305.
 L. Yang, M. Wang, S. Qiao, Side Channel Cube Attack on PRESENT, CANS 2009. LNCS 5888 (2009) 379-391.
 S.F. Abdul-Latip, M. Reyhanitabar, W. Susilo, J. Seberry, On the Security of NOEKEON against Side Channel Cube Attacks, ISPEC 2010, LNCS 6047 (2010) 45-55.
 C. Canniere, O. Dunkelman, M. Knezevic, KATAN and KTANTAN-A Family of Small and Efficient Hardware-Oriented Block Ciphers, CHES 2009, LNCS 5747 (2008) 272-288.
 F. Abed, E. List, S. Lucks, J.Wenzel, Differential and Linear Cryptanalysis of Reduced-round Simon, http://eprint.iacr.org/2013/526. (2013).
 H. A. Alkhzaimi, M. M. Lauridsen, Cryptanalysis of the SIMON Family of Block Ciphers, https://eprint.iacr.org/2013/543.pdf. (2013).
 J. Daemen, V. Rijmen, AES Proposal: Rijndael, The First Advanced Encryption Standard Candidate Conference.
 R. Anderson, B. Biham, L. Knudsen, Serpent: A Proposal for the Advanced Encryption Standard, The First Advanced Encryption Standard Candidate Conference.
 X. Zhao, S. Guo, F. Zhang, T. Wang, Z. Shi, H. Liu, K. Ji, H. J, Efficient Hamming Weight-based Side-channel Cube Attacks on PRESENT, Journal of Systems and Software 86(3) (2013) 728-743.
 K. Zhang, J. Guan, B. Hu, D. Lin, Security Evaluation on Simeck against Zero Correlation Linear Cryptanalysis, Cryptology ePrint Archive, Report 2015/911.
 K. Qiao, L. Hu, S. Sun, Differential Security Evaluation of Simeck with Dynamic Key-guessing Techniques, Cryptology ePrint Archive, Report 2015/902.
 S. Kolbl, A. Roy, A Brief Comparison of SIMON and Simeck, Cryptology ePrint Archive, Report 2015/706.
 F. Zhang, S. Guo, X. Zhao, T. Wang, J. Yang, F.-X. Standaert, D. Gu, A Framework for the Analysis and Evaluation of Algebraic Fault Attacks on Lightweight Block Ciphers,10.1109/TIFS.2016.2516905, (2016).
 L. Qin, H. Chen, Linear Hull Attack on Round-reduced Simeck with Dynamic Key-guessing Techniques, Cryptology ePrint Archive, Report 2016/066.
 Z. Xiang, W. Zhang, Z. Bao, D. Lin, Applying MILP Method to Searching Integral Distinguishers based on Division Property for 6 Lightweight Block Ciphers, http://eprint.iacr.org/2016/857, (2016).
 N. Bagheri, Linear Cryptanalysis of Reduced-round Simeck Variant, Cryptology ePrint Archive, Report 2015/716.
 M. Blum, M. Luby, R. Rubinfield, Self-Testing/Correcting with Application to Numerical Problems, STOC (1990) 73-83.
 I. Dinur, A. Shamir, Side Channel Cube Attacks on Block Ciphers, Cryptology ePrint Archive, Report 2009/127.
 G. Bard, N. Courtois, J. Nakahara, P. Sepehrdad, B. Zhang, Algebraic, AIDA/Cube and Side-Channel Analysis of KATAN Family of Block Ciphers, INDOCRYPT.
 S. Madakam, R. Ramaswamy and S. Tripathi, S., 2015. Internet of Things (IoT): A literature review. Journal of Computer and Communications, 3(05), pp.164.
 A. Haroon, M. A. Shah, Y. Asim, W. Naeem, M. Kamran, Q. Javaid, 2016. Constraints in the IoT: The World in 2020 and Beyond, International Journal of Advanced Computer Science and Applications, Vol. 7, pp. 252-271.
Alya Geogiana Buja is a Ph.D. student at the Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Malaysia. Her research interests include information and network security. She involves actively in giving seminar and talk about information and security.
Shekh Faisal Abdul-Latip is a Senior Lecturer at the Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Malaysia. He received PhD degree in 2012 from the University of Wollongong, Australia, in the field of Symmetric-key Cryptography. Currently he is an executive committee member of Malaysian Society for Cryptology Research (MSCR) – a non-profit organization that promotes new ideas and activities in cryptology related areas in Malaysia. His research focuses on Cryptology (i.e. designing and breaking secret codes) and Information Security.
Rabiah Ahmad is a Professor at the Faculty of Information Technology and Communication, Universiti Teknikal Malaysia Melaka, Malaysia. She received her PhD in Information Studies (health informatics) from the University of Sheffield, UK, and M.Sc. (information security) from the Royal Holloway University of London, UK. Her research interests include healthcare system security and information security architecture. She has delivered papers at various health informatics and information security conferences at national as well as international levels. She has also published papers in accredited national/international journals. Besides that, she also serves as a reviewer for various conferences and journals.