Automatic Decision of Findings Text in Development Models
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.393-397, Mar-2018
Abstract
Automated feature choice is essential for text categorization to range back the feature size and to hurry up the educational method of classifiers. Allocated engineering tasks are often conducted using process models. In this circumstance, it is necessary that these models do not contain structural or terminological inconsistencies. To this end, many automatic analysis techniques have been proposed to provide quality assurance. While appropriate properties of control flow can be checked in an automated fashion, there is a lack of techniques addressing textual quality. More particularly, there is currently no technique available for handling the issue of lexical ambiguity caused by homonyms and synonyms. In this paper, we tackle this research gap and intend a modus operandi that detect and resolve lexical ambiguities in practice models.
Key-Words / Index Term
Text categorization, X-Drop Algorithm
References
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Citation
S.V.Paulraj, L.Jayasimman, N.sugavaneswaran, "Automatic Decision of Findings Text in Development Models", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.393-397, 2018.
An Efficient and Usable Client-Side Phishing Detection Application
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.398-401, Mar-2018
Abstract
Phishing is a main problem on the Web. Despite the important attention it has established over the years, there has been no ultimate solution. While the state-of-the-art solutions have reasonably good presentation, they suffer from quite a few drawbacks counting potential to compromise consumer privacy, difficulty of detecting phishing websites whose content change dynamically, and confidence on features that are too dependent on the preparation data. To address these limits we present a new move toward for detecting phishing WebPages in real-time as they are visited by a browser. It relies on modeling inherent phisher limits stemming from the constraints they face while building a webpage. Consequently, the implementation of our approach, Off-the-Hook, exhibits several notable properties including high accuracy, brand-independence and good language-independence, speed of decision, resilience to dynamic phish and flexibility to evolution in phishing techniques. Off-the-Hook is implemented as a fully-client-side browser add-on, which preserves user privacy. In addition, Off-the-Hook identifies the target website that a phishing webpage is attempting to imitate and includes this target in its warning. We evaluated our proposed genetic algorithm in below user studies.
Key-Words / Index Term
Client
References
[1] K. Thomas, C. Grier, J. Ma, V. Paxson, and D. Song, “Design and evaluation of a real-time url spam filtering service,” in Proceedings of the IEEE Symposium on Security and Privacy, 2011, pp. 447–462.
[2] C. Whittaker, B. Ryner, and M. Nazif, “Large-scale automatic classification of phishing pages,” in Proceedings of the 2010 Network and Distributed System Security (NDSS) Symposium, 2010.
[3] Google, “Safe browsing.” [Online]. Available: https://www.chromium. org/developers/design-documents/safebrowsing
[4] Phishtank, “Out of the Net, into the Tank.” [Online]. Available: https://www.phishtank.com/
[5] X. Han, N. Kheir, and D. Balzarotti, “Phisheye: Live monitoring of sandboxed phishing kits,” in ACM CCS, 2016, pp. 1402–1413.
[6] M. Al-Daeef, N. Basir, and M. Saudi, “A review of client-side toolbars as a user-oriented anti-phishing solution,” in Advanced Computer and Communication Engineering Technology, 2016, pp. 427–437.
[7] B. Liang, M. Su, W. You, W. Shi, and G. Yang, “Cracking classifiers for evasion: A case study on the google’s phishing pages filter,” in International Conference on World Wide Web, 2016, pp. 345–356.
[8] D. Akhawe and A. P. Felt, “Alice in warningland: A large-scale field study of browser security warning effectiveness,” in Proceedings of the 22nd USENIX Conference on Security, 2013, pp. 257–272.
[9] APWG, “Phishing Activity Trends Report,” APWG, Tech. Rep. 3Q2016, 2016.
[10] G. Xiang and J. I. Hong, “A hybrid phish detection approach by identity discovery and keywords retrieval,” in Proceedings of the 18th International Conference on World Wide Web, 2009, pp. 571–580.
[11] Y. Pan and X. Ding, “Anomaly based web phishing page detection,” in Proceedings of the 22nd Annual Computer Security Applications Conference (ACSAC), 2006, pp. 381–392.
[12] A. Le, A. Markopoulou, and M. Faloutsos, “PhishDef: URL names say it all,” in Proceedings of IEEE INFOCOM, 2011, pp. 191–195.
[13] S. Marchal, J. Franc¸ois, R. State, and T. Engel, “Proactive discovery of phishing related domain names,” in Research in Attacks, Intrusions, and Defenses, 2012.
[14] SSG@Aalto, “Off-the-Hook - A phishing prevention system.” [Online]. Available: https://ssg.aalto.fi/projects/phishing/add-on.html
[15] KangoExtensions, “Cross-browser extension framework.” [Online]. Available: http://kangoextensions.com/
Citation
P.Priyadevi, V.Lalithadevi, M.sughashini, "An Efficient and Usable Client-Side Phishing Detection Application", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.398-401, 2018.
An Efficient Analysis of Deduplication among Cloud Storage
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.402-405, Mar-2018
Abstract
In recent years, by increasing the volume of information available in data warehouse most of the system may be affected by the replicas. Record deduplication is the important key operation in data integration from multiple data sources on server. To achieve high quality information, remove replica data and more simplified data representation, data preprocessing is required. Data clean-up is one among the data preprocessing steps. Data clean-up includes the process of parsing, Data tree analysis, data transformation, duplicate elimination and arithmetic methods. If two data sets represent the same real world entity then it is called duplicated data’s. The problem of detecting and eliminating duplicate data’s is called record deduplication. This survey presents an analysis of record BAT algorithm, Modified BAT algorithm and Hidden Face algorithms that identify and remove the duplicate records. Duplicate data removal to possible savings in computational time and resources to process this data.
Key-Words / Index Term
Data deduplication, Data Integration, Data preprocessing, BAT algorithm, Modified BAT algorithm, Hidden Face algorithm
References
[1] Moises G. de Carvalho, Alberto H.F. Laender, Marcos AndreGoncalves, and Altigran S. da silva, “A Genetic Programming Approach to Record Deduplication”, IEEE Trans. Knowledge and Data Eng., vol. 24,no. 3, pp. 399-412, Mar. 2012.
[2] A.K. Elmagarmid, P.G. Ipeirotis, and V.S. Verykios, “Duplicate Record Detection: A Survey”, IEEE Trans. Knowledge and Data Eng., vol. 19, no. 1, pp. 1-16, Jan. 2007.
[3] V. Subramaniyaswamy, S. Chenthur Pandian, “A Complete Survey of Duplicate Record Detection Using Data Mining Techniques”, Information Technology Journal 11(8)., ISSN 1812-5638, pp.941- 945, 2012.
[4]. M. Carvalho, A. Laender, M. Goncalves, and A. da Silva. Replica identification using genetic programming. In Proceedings of the 2008 ACM symposium on Applied computing, pages 1801-1806. ACM, 2008.
[5] Faritha Banu, A, Chandrasekar C, “An Optimized Approach of Modified BAT Algorithm to Record Deduplication”, International Journal of Computer Applications (0975 – 8887) Volume 62– No.1, January 2013.
[6] Baoping Zhang, Yuxin Chen, Weiguo Fan, Edward A. Fox , Marcos Gonc¸alves, Marco Cristo, P´avel Calado, “Intelligent GP Fusion from Multiple Sources for Text Classification”
[7] An´ısio Lacerda1 Marco Cristo1 Marcos Andr´e Gonc¸ alves, “Learning to Advertise”, “SIGIR’06, August 6– 11, 2006, Seattle, Washington, USA. Copyright 2006 ACM 1595933697/06/0008.
[8] N. Koudas, S. Sarawagi, and D. Srivastava, “Record linkage: similarity measures and algorithms,” ACM SIGMOD International Conference on Management of Data, pp. 802–803, 2006
Citation
M.Raja, G.Lalithadevi, N.sugavaneswaran, "An Efficient Analysis of Deduplication among Cloud Storage", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.402-405, 2018.
A Novel Approach for Efficient Usage of Intrusion Detection System In Mobile Ad Hoc Networks
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.406-411, Mar-2018
Abstract
Due to the lack process of wireless links, it is hard to decide if small package losses are due to wireless induced belongings or from spiteful discarding. Many prior pains on detecting malicious packet drops rely on proof collected via passive monitoring by neighbor nodes; however, they do not examine the cause of packet losses. In this paper, we ask: Given certain macroscopic parameters of the system similar to traffic strength and node mass what is the probability that data exists with admiration to a broadcast and, How can these parameters be used to do a forensic analysis of the cause for the losses. Towards answering the above questions, primary build an logical framework that computes the probability that evidence call this transmission evidence or TE for short exists with high opinion to transmissions, in terms of a set of system parameters. Here, validate our logical framework via both simulations as well as real-world experiments on two dissimilar wireless test beds. The analytical structure is then used as a basis for a procedure within a forensic analyzer to assess the cause of pack losses and decide the likelihood of forwarding misbehaviors.
Key-Words / Index Term
MANET Networks
References
[1] S. Zeadally , R. Hunt, Y-S. Chen, A. Irwin and A. Hassan, ”Vehicular ad hoc networks (VANETS): status, results, and challenges,” Telecommunication Systems, vol. 50, no. 4, pp. 217-241, 2012.
[2] S. K. Bhoi and P. M. Khilar, ”Vehicular communication: a survey”, IET Networks, vol. 3, no. 3, pp. 204 - 217, 2014.
[3] S. Marti, T. J. Giuli, K. La and M. Baker, ”Mitigating Routing Misbehavior in a Mobile Ad-hoc Environment,” Proc. 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking, pp. 255- 265, August 2000.
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[10] I. Khalil, S. Bagchi and N. B. Shroff, ”SLAM: Sleep-Wake Aware Local Monitoring in Sensor Networks,” Proc. 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2007 (DSN 2007), 565-574.
Citation
T.Ravichandran, G.lalithadevi, M.Sughasini, "A Novel Approach for Efficient Usage of Intrusion Detection System In Mobile Ad Hoc Networks", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.406-411, 2018.
A Classic Performance Analysis Using Cooperative Retransmission Protocols for Mac Layer
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.412-415, Mar-2018
Abstract
A cross-layer draws near for enabling high-throughput routing in multi-hop wireless networks. This approach builds on a MAC-layer cooperative retransmission system, which is explicitly designed to exploit the benefits of MAC-layer retransmission-based consistency, cooperative communications, and link-quality awareness. Based on this instrument, we produce a routing metric, called the unsurprising cooperative transmission count (ECTX), to detain the combined effects of MAC-layer supportive retransmission and per-link estimates of packet delivery ratios. Cooperative retransmission can much improve link reliability over lossy and time-varying wireless links. However, comparing retransmission protocols is tough, and usually requires simplistic assumptions specific to each protocol. In this paper, we develop a general form to assess helpful retransmission protocols with distributed, slot-based argument algorithms. Specifically, we suggest calculating the spread time-out probabilities at a MAC time-slot scale, formulate retransmission outcomes as function of the time-out probability, and derive the probability of a retransmission process for every data frame.
Key-Words / Index Term
cooperative retransmission, opportunistic re- transmission, IEEE 802.11, MAC, ARQ, CMAC, DAFMAC, Δ-MAC, PRO
References
[1]A. Bletsas, H. Shin, and M. Z. Win, “Cooperative communications with outage-optimal opportunistic relaying,” IEEE Trans. Wireless Commun., vol. 6, no. 7, pp. 3450–3460, Sep. 2007.
[2]P. Liu, Z. Tao, and S. Panwar, “A cooperative MAC protocol for wireless local area networks,” in Proc. IEEE ICC, Seoul, Korea, May 2005, pp. 2962–2968.
[3]B. Sen, J. Guo, X. Zhao, and S. Jha, “ECTX: A high-throughput path metric for multi-hop wireless routing exploiting MAC-layer cooperative retransmission,” in Proc. IEEE WoWMoM, San Francisco, USA, Jun. 2012, pp. 1–9.
[4]P. A. Anghel and M. Kaveh, “On the performance of selection coop- eration ARQ,” in Proc. IEEE ICC, Dresden, Germany, Jun. 2009, pp. 1–6.
[5]B. Hagelstein, M. Abolhasan, D. Franklin, and F. Safaei, “An efficient opportunistic cooperative diversity protocol for 802.11 networks,” in Proc. ACM IWCMC, Caen, France, Jul. 2010, pp. 417–421.
[6]M.-H. Lu, P. Steenkiste, and T. Chen, “Opportunistic retransmission in WLANs,” IEEE Trans. Mobile Comput., vol. 11, no. 12, pp. 1953–1969, Dec. 2012.
[7]Z. Wang, C. Li, and Y. Chen, “Local cooperative relay for opportunistic data forwarding in mobile ad-hoc networks,” in Proc. IEEE ICC, Ottawa, Canada, Jun. 2012, pp. 1–6.
[8]L. Xiong, L. Libman, and G. Mao, “Optimal strategies for cooperative MAC-layer retransmission in wireless networks,” in Proc. IEEE WCNC, Las Vegas, USA, Mar. 2008, pp. 1495–1500.
[9]N. S. Shankar, C.-T. Chou, and M. Ghosh, “Cooperative communication MAC (CMAC) - a new MAC protocol for next generation wireless LANs,” in Proc. IEEE ICWNCMC, Maui, USA, Jun. 2005, pp. 1–6.
Citation
S.Sarugasini, L.Jayasimman, V.Upendran, "A Classic Performance Analysis Using Cooperative Retransmission Protocols for Mac Layer", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.412-415, 2018.
Resolving the Conflicts Data in an Organization using Classifier Process
Review Paper | Journal Paper
Vol.06 , Issue.02 , pp.416-420, Mar-2018
Abstract
A sequence of Files losses in the Organization network, we are interested in determining whether the losses are caused by link errors only, or by the collective effect of link errors and malicious drop. Link error and malicious packet reducing are two sources for packet losses in multi-hop wireless ad hoc network. We are chiefly nervous in the insider-attack case, whereby hateful nodes that are fraction of the way exploit their knowledge of the communication context to selectively drop a miniature quantity of packets dangerous to the network presentation. Because the File dropping velocity in this case is equivalent to the channel error rate, “conventional algorithms” that are based on detecting the File loss rate cannot realize reasonable detection accuracy. To recover the detection accuracy, we suggest extending the correlations between lost Files. Furthermore, to assurance directly computation of these correlations, we expand a “homomorphic linear authenticator (HLA)” based public auditing structural design that allows the detector to substantiate the truthfulness of the files loss in sequence reported by nodes. This construction is privacy preserving, collusion evidence, and incurs low communication and storage expenses. To reduce the calculation glide of the baseline system, a “packet-block-based mechanism” is also proposed, which allows one to trade detection accuracy for inferior computation complexity
Key-Words / Index Term
Data fusion, truth discovery, heterogeneous data
References
[1] J. Bleiholder and F. Naumann, “Data fusion,” ACM Computing Surveys, vol. 41, no. 1, pp. 1:1–1:41, 2009.
[2] X. L. Dong and F. Naumann, “Data fusion: Resolving data conflicts for integration,” PVLDB, vol. 2, no. 2, pp. 1654–1655, 2009.
[3] Z. Jiang, “A decision-theoretic framework for numerical attribute value reconciliation,” TKDE, vol. 24, no. 7, pp. 1153–1169, 2012.
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[5] A.Galland,S.Abiteboul,A.Marian,andP.Senellart,“Corroborating information from disagreeing views,” in Proc. of WSDM, 2010, pp. 131–140.
[6] B. Zhao, B. I. P. Rubinstein, J. Gemmell, and J. Han, “A bayesian approach to discovering truth from conflicting sources for data integration,” PVLDB, vol. 5, no. 6, pp. 550–561, 2012.
[7] X. L. Dong and D. Srivastava, “Big data integration,” in Proc. of ICDE, 2013, pp. 1245–1248.
[8] V. Vydiswaran, C. Zhai, and D. Roth, “Content-driven trust propagation framework,” in Proc. of KDD, 2011, pp. 974–982.
[9] J. Pasternack and D. Roth, “Making better informed trust decisions with generalized fact-finding,” in Proc. of IJCAI, 2011, pp. 2324– 2329
[10] X. L. Dong, L. Berti-Equille, and D. Srivastava, “Integrating conflicting data: The role of source dependence,” PVLDB, vol. 2, no. 1, pp. 550–561, 2009.
Citation
L.Sampath, R.Umadevi, N.Vijayaraj, "Resolving the Conflicts Data in an Organization using Classifier Process", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.416-420, 2018.
Camouflage Traffic: Minimizing Message Delay for Applications under Jamming
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.421-424, Mar-2018
Abstract
Time Division Multiple Access (TDMA) is frequently used in Wireless Sensor Networks (WSNs), specially for critical applications, as it provides high efficiency, reliable performance, guaranteed bandwidth, bounded and predictable latency, and absence of collisions. However, TDMA is easily vulnerable to choosy jamming attacks. In TDMA transmission, all the slots are usually pre-allocated to sensor nodes, and each slot is used by the identical node for a number of consecutive superframes. Hence, an adversary could frustrate a victim node’s communication by simply jamming its slot(s). Such attack turns out to be proficient, energy efficient, and extremely difficult to detect. In this paper, we propose a novel approach JAMMY, a distributed and reliable solution to selective jamming in TDMA-based WSNs. Unlike conventional approaches, JAMMY changes the slot utilization pattern at every superframe, thus making it unpredictable to the adversary. JAMMY is decentralized, as sensor nodes determine the next slot consumption pattern in a distributed and autonomous way. Results from performance analysis of the proposed solution show that JAMMY introduces tiny overhead yet allows many nodes to join the network, in a limited number of superframes.
Key-Words / Index Term
WSNs, TDMA, Security, Selective Jamming, DoS, Secure Slot Permutation, Decentralized Slot Acquisition
References
[1] A. D. Wood, J. A. Stankovic and G. Zhou. DEEJAM: Defeating Energy-Efficient Jamming in IEEE 802.15.4-based Wireless Networks. In Proceedings of the 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pages 60–69. IEEE Computer Society, June 2007.
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[11] F. Ashraf, Y.-C. Hu and R.H. Kravets. Bankrupting the jammer in WSN. In Proceedings of the IEEE 9th International Conference on Mobile Adhoc and Sensor Systems, pages 317–325, October 2012.
[12] G. Dini and I. M. Savino. LARK: A Lightweight Authenticated ReKeying Scheme for Clustered Wireless Sensor Networks. ACM Transactions on Embedded Computing Systems, 10(4), 2011.
[13] G. Dini and M. Tiloca. HISS: a HIghly Scalable Scheme for group rekeying. The Computer Journal, 56(4):508–525, November 2013.
[14] H. Mustafa, X. Zhang, Z. Liu, W. Xu and A. Perrig. Jamming- Resilient Multipath Routing. IEEE Transactions on Dependable and Secure Computing, 9(6):852–864, November 2012.
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Citation
P.Sangeetha, V.Lalithadevi, M.sughasini, "Camouflage Traffic: Minimizing Message Delay for Applications under Jamming", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.421-424, 2018.
A Reliable Approach of Hierarchical Clustering Method for Distributed Systems
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.425-429, Mar-2018
Abstract
Clustering has happened to an increasingly important task in analyzing huge amounts of data. Traditional applications need that all data has to be located at the site where it is scrutinized. Nowadays, large amounts of heterogeneous, difficult records reside on different, independently working computers which are connected to each other via local or large area networks. Preliminary work on an algorithm for K-means clustering of homogeneously distributed data in a peer-to-peer system. The algorithm is asynchronous and every node operates locally by communicating only with its topological neighboring nodes. due to network bandwidth restrictions, or sense of the huge amount of distributed data. Due to the theatrical enlarge of data volumes in a different Appliance, it is suitably infeasible to keep these data in one centralized machine. It is suitable more and more natural to deal with distributed databases and networks. That is why distributed data mining technique includes. Individual of the mainly important data mining problems is data clustering. We regard as the clustering of very huge datasets distributed over a network of computational units using a decentralized K-means algorithm. To attain the equal codebook at every node of the network, we use a randomized gossip aggregation protocol where only small messages are exchanged.
Key-Words / Index Term
Distributed systems, clustering, partition-based clustering, density-based clustering, dynamic system
References
[1] K. M. Hammouda and M. S. Kamel, “Models of distributed data clustering in peer-to-peer environments,” Knowl. Inf. Syst., vol. 38, no. 2, pp. 303–329, 2014.
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Citation
R.Suganya, L.Jayasimman, R.Vijayalakshmi, "A Reliable Approach of Hierarchical Clustering Method for Distributed Systems", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.425-429, 2018.
A COMPARATIVE STUDY ON E-BANKING SERVICES BETWEEN PUBLIC AND PRIVATE SECTOR BANKS IN TRICHY DISTRICT
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.430-439, Mar-2018
Abstract
Electronic banking is an activity that is not new to banks or their customers. Banks having been providing their services to customers electronically for years through software programmes. These software programs allowed the user’s personal computer to dial up the bank directly. In the past however, banks have been very reluctant to provide their customers with banking via the Internet due to security concerns. Today, banks seem to be jumping on the bandwagon of Internet banking. Why is there a sudden increase of bank interests in the Internet? The first major reason is because of the improved security and encryption methods developed on the Internet. The second reason is that banks did not want to lose a potential market share to banks that were quick to offer their services on the Internet.
Key-Words / Index Term
References
[1]. Cooper D.R., Sachindler P.S. (2003), “Business Research Methods”, Tata McGraw-Hill.pg:25-34
[2]. Levin R.I., Rubil D.S. (2002), “Statistics for Management”,Pearson Education Asia.pg:152-163
[3]. Information Technology, Data communications & electronic banking, 2nd education, 2007, Banking Course Book, Indian Institute of Banking and Finance, Macmillian.pg:45-64
[4]. www.google.com
[5]. www.banknetindia.com
[6]. www.shodhganga.com
Citation
B. Narayanan, M. Arivalagan, "A COMPARATIVE STUDY ON E-BANKING SERVICES BETWEEN PUBLIC AND PRIVATE SECTOR BANKS IN TRICHY DISTRICT", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.430-439, 2018.
Financial Performance of District Central Cooperative Banks in India: Growth Rate Analysis
Research Paper | Journal Paper
Vol.06 , Issue.02 , pp.440-443, Mar-2018
Abstract
District Cooperative Central Bank, popularly known as DCC Bank is a co-operative banking network established in India to serve cooperatives and rural areas. It was established to provide banking to rural hinterland for agriculture sector with the branches primarily established at rural and semi-urban areas. The DCC Banks act as intermediaries between State Cooperative Bank (Apex Bank) and Primary Agriculture Cooperative Societies (PACSs). The success of cooperative credit movement in a district is largely depends on their financial strength. DCC Banks are key financing institution at the district level which shoulders responsibility of meeting credit needs of different types of cooperatives in the district. At present, most of the district central cooperative banks are facing the problems of overdue, recovery, nonperforming assets and other problems. Therefore, it is necessary to study financial performance of DCCBs in India. This paper attempts to analyze the financial performance of DCC Banks in India during the period 2010-2011 to 2015-2016. An analytical research design (Growth Rate) is followed in the present study. Empirical results show positive and sufficient growth of DCC Banks in India.
Key-Words / Index Term
Financial Performance, District Central Cooperative Banks, Overdue
References
[1]. Anil Kumar Soni and Abhay Kapre Financial performance of DCC bank limited Rajnandgon.Growth analysis – Golden Research thought Publications, 4th Oct.2012.
[2]. Cooperative Department, Govt. of kerala (2016), Annual Report.
[3]. National Federation of State Cooperative Banks Ltd.- Annual Report 2012.
[4]. National Federation of State Cooperative Banks Ltd.- Annual Report 2013
[5]. National Federation of State Cooperative Banks Ltd.- Annual Report 2014
[6]. National Federation of State Cooperative Banks Ltd.- Annual Report 2015
[7]. National Federation of State Cooperative Banks Ltd.- Annual Report 2016
[8]. Mane M.J. and Mane Abhijeet (2012), Problems and Prospects of District Central Cooperative Banks in India, Golden Research Thoughts, Vol. - I, ISSUE X/ April 2012.
Citation
K.Rajam, K M Sabeer, "Financial Performance of District Central Cooperative Banks in India: Growth Rate Analysis", International Journal of Computer Sciences and Engineering, Vol.06, Issue.02, pp.440-443, 2018.