i-manager Publications

i-manager's Journal on Information Technology (JIT)

Current Issue Vol. 12 Issue 4

Most Cited

Volume 9 Issue 2 March - May 2020

Research Paper

Privacy Preservation in Big Data Application using Advanced Encryption Standard and Least Significant Bit Steganography

Abdulmalik Danlami Mohammed * , Oluwaseun A. Ojerinde , Moses Folorunsho Victor *, M. L. Agrawal****

*-**** Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Minna, Nigeria.

Mohammed, A. D., Ojerinde, O. A., Victor, M. F., and Kenneth, M. O. (2020). Privacy Preservation in Big Data Application using Advanced Encryption Standard and Least Significant Bit Steganography. i-manager's Journal on Information Technology, 9(2), 1-11. https://doi.org/10.26634/jit.9.2.17550

Abstract

Over the years, the proliferation of internet data and its widespread usage has contributed to increase in threats to security. Many new technologies are transforming the face of the world in the real environment of today. Nevertheless because of these emerging technologies, we are unable to secure our private information in a very effective manner and these days' cybercrimes are growing day by day. Several methods such as authentication, firewall, cryptography and steganography are used to safeguard this vast amount of data on the internet. Hence, this research aims at protecting the privacy of big data applications using the Advanced Encryption Standard (AES) technique and the Least Significant Bit (LSB) steganography technique. This proposed algorithm hides the generated cipher text using the AES algorithm inside a cover image to hide the presence of the cipher text using the LSB technique. Based on the PSNR, SNR, SSIM and MSE values obtained, it can be concluded that the proposed system is robust and reliable.

References

[1]. Abdullah, A. (2017). Advanced encryption standard (AES) algorithm to encr ypt and decr ypt data. Cryptography and Network Security.

[2]. Agarsana, B. G., Anjali, T. K., & Kirthika, M. S. S. (2018). Image steganography using secured force algorithm for hiding audio signal into colour image. International Research Journal of Engineering and Technology, 05(02), 1-5.

[3]. Ali, U. A. M. E., Sohrawordi, M., & Uddin, M. P. (2019). A robust and secured image steganography using LSB and random bit substitution. American Journal of Engineering Research, 8, 39-44.

[4]. Almazaydeh, W. I. A., & Sheshadri, H. (2016). Image steganography using LSB, LSB+Huffman code, and LSB+Arithmetic code. International Journal of Computer Applications, 155(11), 1–7. https://doi.org/10.5120/ijca2 016911478

[5]. Al-Mazaydeh, W. I. A. (2014). Image steganography using LSB and LSB+Huffman code. International Journal of Computer Applications, 99(5), 17-22. https://doi.org/ 10.5120/17370-7896

[6]. Al-Najjar, Y. A., & Soong, D. C. (2012). Comparison of image quality assessment: PSNR, HVS, SSIM, UIQI. International Journal of Scientific Engineering and Research, 3(8), 1-5.

[7]. Azad, V., & Sharma, P. (2014). A review on objective image quality assessment techniques. International Journal of Emerging Engineering Research and Technology, 2(5), 188-192.

[8]. Basahel, A. M., Yamin, M., & Abi Sen, A. A. (2019). Enhancing security of transmitted data by improved steganography method. International Journal of Computer Science and Network Security (IJCSNS), 19(4), 239-244.

[9]. Chandra, S., & Paira, S. (2019). Secure transmission of data using image steganography. Journal of Image Video Process, 10(1), 2049-2053. https://doi.org/10.2191 7/ijivp. 2019.0291

[10]. Deepika, A.,& Kaur, G. (2016). Review paper on enhancing data security for cloud environment cryptography and steganography technique. International Journal of Applied Science and Engineering, 2(1), 44–48.

[11]. Emam, M. M., Aly, A. A., & Omara, F. A. (2016). An improved image steganography method based on LSB technique with random pixel selection. International Journal of Advanced Computer Science & Applications, 1(7), 361-366. https://doi.org/10.14569/IJACSA.2016.070 350

[12]. Goswami, P., & Madan, S. (2017). A survey on big data & privacy preserving publishing techniques. Advances in Computational Sciences and Technology, 10(3), 395-408.

[13]. Hameed, M. A., Hassaballah, M., Aly, S., & Awad, A. I. (2019). An adaptive image steganography method based on histogram of oriented gradient and PVD-LSB techniques. IEEE Access, 7, 185189-185204. https://doi. org/10.1109/ACCESS.2019.2960254

[14]. Hemalatha, S., Acharya, D. U., Renuka, A., & Kamath, P. R. (2013). A secure and high capacity image steganography technique. Signal Image Process, 4(1), 83–89. https://doi.org/10.5121/sipij.2013.4108

[15]. Hore, A., & Ziou, D. (2010, August). Image quality th metrics: PSNR vs. SSIM. In 2010, 20 International Conference on Pattern Recognition (pp. 2366-2369). IEEE. https://doi.org/10.1109/ICPR.2010.579

[16]. Kumar, R., Sharma, G., & Sanduja, V. (2018). A real time approach to compare PSNR and MSE value of different original images and noise (salt and pepper, speckle, gaussian) added images. International Journal of Latest Technology in Engineering, Management and Applied Science, 7, 43-46.

[17]. Maganbhai, P. A. K., & Chouhan, K. (2015). A study and literature review on image steganography. International Journal of Computer Science and Information Technologies, 6(1), 685-688.

[18]. Maheswari, S. U., & Hemanth, D. J. (2015). Different methodology for image steganography-based data hiding. International Journal of Information and Communication Technology, 7(4-5), 521-536. https://doi. org/10.1504/IJICT.2015.070330

[19]. Nashat, D., & Mamdouh, L. (2019). An efficient steganographic technique for hiding data. Journal of the Egyptian Mathematical Society, 27(1), 1-14. https://doi. org/10.1186/s42787-019-0061-6

[20]. Osunade, O., & Adeniyi, G. I. (2016). Enhancing the least significant bit (LSB) algorithm for steganography. International Journal of Computer Applications, 149(3), 1–8. https://doi.org/10.5120/ijca2016911363

[21]. Pavani, M., Naganjaneyulu, S., & Nagaraju, C. (2013). A survey on LSB based steganography methods. International Journal of Engineering and Computer Science, 2(08), 2464-2467.

[22]. Pujari, A. A., & Shinde,S. S. (2016). Data security using cryptography and steganography. IOSR Journal of Computer Engineering, 18(04), 130–139. https://doi.org/ 10.9790/0661-180405130139

[23]. Rahman, M. S., Khalil, I., Yi, X., & Gu, T. (2019). A novel privacy preserving search technique for stego data in untrusted cloud. In The Hawaii International Conference on System Sciences. https://doi.org/10.2425 1/HICSS.2019.513

[24]. Reddy, D. L. K. D. A., & Jilani, S. A. K. (2016). Implementation of 128-bit AES algorithm in MATLAB. International Journal of Engineering Trends and Technology (IJETT), 33(3), 126-129. https://doi.org/10.144 45/22315381/IJETT-V33P223

[25]. Sara, U., Akter, M., & Uddin, M. S. (2019). Image quality assessment through FSIM, SSIM, MSE and PSNR—a comparative study. Journal of Computer and Communications, 7(3), 8-18. https://doi.org/10.4236/jcc. 2019.73002

[26]. Singh, S., & Lekha, B. (2014). A simple steganography technique for hiding data into image. International Journal of Computer Trends & Technology, 2(6).

Full Article (HTML)

Pdf

Research Paper

Comparitive Analysis between Two Security Models of NoSQL Database

M. Somasundara Rao * , K. Venkata Rao, M. H. M. Krishna Prasad*

* Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India.

Department of Computer Science and Engineering, Vignan's Institute of Information Technology, Visakhapatnam, Andhra Pradesh, India.

* Department of Computer Science and Engineering, University College of Engineering Kakinada, Andhra Pradesh, India.

Rao, M. S., Rao, K. V., and Prasad, M. H. M. K. (2020). Comparitive Analysis between Two Security Models of NoSQL Database. i-manager's Journal on Information Technology, 9(2), 12-19. https://doi.org/10.26634/jit.9.2.17685

Abstract

Nowadays, organizations collect volumes of data for future analysis. Motivated by this amount of data and requirements of Web 2.0, a plethora of non-relational databases (NoSQL) emerged in recent years. However, several security features in relational databases (e.g., access control) have been left in non-relational management systems to be developed by the application, which can raise security breaches. This paper proposes two distinctive security model, based on the use of metadata, to provide access control for NoSQL graph-oriented database management system and organization based system. The goal is to support the development of applications that use graph-oriented database in preserving the integrity of stored data and protect them from non-authorized access. A case study has been performed as proof of concept, where the model has been instantiated and implemented for Neo4j database. A network management data security technique for executives based on NoSQL is suggested for better assurance of Organization based security systems. These are the two distinctive security models presented in this study.

References

[1]. Albalawi, U. (2018, December). Countermeasure of statistical inference in database security. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 2044-2047). IEEE. https://doi.org/10.1109/BigData.201 8.8622241

[2]. Ali, R., Liu, R., Awan, S. A., Qayoom, A., Mahmood, S., ur Rehman, S., & Umer, M. (2020, February). Improvisation the security and privacy in real time database system. In 2020 International Conference on Information Science and Communication Technology (ICISCT) (pp. 1-6). IEEE. https://doi.org/10.1109/ICISCT49550.2020.9080027

[3]. Al-Maawali, Z. A., Noronha, H., & Kumar, P. U. (2019, January). Big data acquisition, preprocessing and analysis to develop and implement effective database th system with high security standards. In 2019, 4 MEC International Conference on Big Data and Smart City (ICBDSC) (pp. 1-4). IEEE. https://doi.org/10.1109/ICBDSC. 2019.8645583

[4]. Almutairi, A. H., & Alruwaili, A. H. (2012). Security in database systems, Global Journal of Computer Science and Technology Network, Web & Security, 12(17), 9-14.

[5]. Bao, H., He, H., Liu, Z., & Liu, Z. (2019, September). Research on network privacy information security management method based on NoSQL database. In 2019, International Conference on Virtual Reality and Intelligent Systems (ICVRIS) (pp. 415-419). IEEE. https://doi. org/10.1109/ICVRIS.2019.00107

[6]. Bertino, E., & Sandhu, R. (2005). Database securityconcepts, approaches, and challenges. IEEE Transactions on Dependable and Secure Computing, 2(1), 2-19. https://doi.org/10.1109/TDSC.2005.9

[7]. Cinar, O., Guncer, R. H., & Yazici, A. (2016, December). Database security in private database clouds. In 2016, International Conference on Information Science and Security (ICISS) (pp. 1-5). IEEE. https://doi.org/ 10.1109/ICISSEC.2016.7885847

[8]. Huijie, W. (2017, December). A security framework for th database auditing system. In 2017, 10 International Symposium on Computational Intelligence and Design (ISCID) (Vol. 1, pp. 350-353). IEEE. https://doi.org/10.1109/ ISCID.2017.64

[9]. Kumar, B., & Al Hasani, M. H. S. (2016, October). Database security—Risks and control methods. In 2016, First IEEE International Conference on Computer Communication and the Internet (ICCCI) (pp. 334-340). IEEE. https://doi.org/10.1109/CCI.2016.7778937

[10]. Malik, M., & Patel, T. (2016). Database security attacks and control methods. International Journal of Information, 6(1/2), 175-183.

[11]. Morgado, C., Baioco, G. B., Basso, T., & Moraes, R. (2018, July). A security model for access control in graph- oriented databases. In 2018, IEEE International Conference on Software Quality, Reliability and Security (QRS) (pp. 135-142). IEEE. https://doi.org/10.1109/QRS.2 018.00027

[12]. Rathore, S., & Sharma, A. (2018). Database securityattacks, threats and challenges. International Journal of Engineering Research & Technology (IJERT), 5(10).

Full Article (HTML)

Pdf

Research Paper

Dense Captioning of Images

Shreyas More * , Amrutesh Taral, Bhavya Shah, Sneh Joshi, Kirankumari Sinha

* Department of Computer Science, Indian Institute of Technology, Kharagpur, West Bengal, India.

-*** Department of Information Technology, K J Somaiya College of Engineering, Mumbai, Maharashtra, India.

More, S., Taral, A., Shah, B., Joshi, S., and Sinha, K. (2020). Dense Captioning of Images. i-manager's Journal on Information Technology, 9(2), 20-26. https://doi.org/10.26634/jit.9.2.17308

Abstract

Dense Image Captioning task describes the objects within an image by identifying them and their surroundings and establishing a relationship between them. The architecture comprises a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) language model that generates the captions. This project requires a system making use of computer vision to both find regions and describe them in natural language. The images are passed through a Convolutional network to identify the region features. These features then form the input for the Recurrent neural network, which generates the captions for the regions encompassing the relationships between the objects.

References

[1]. Barnard, K., Duygulu, P., Forsyth, D., Freitas, N. D., Blei, D. M., & Jordan, M. I. (2003). Matching words and pictures. Journal of Machine Learning Research, 3 (Feb), 1107-1135.

[2]. Bengio, Y., Ducharme, R., Vincent, P., & Jauvin, C. (2003). A neural probabilistic language model. Journal of Machine Learning Research, 3(Feb), 1137-1155.

[3]. Chen, X., & Lawrence Zitnick, C. (2015). Mind's eye: A recurrent visual representation for image caption generation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2422- 2431).

[4]. Chen, X., Fang, H., Lin, T. Y., Vedantam, R., Gupta, S., Dollár, P., & Zitnick, C. L. (2015). Microsoft coco captions: Data collection and evaluation server. Computer Vision and Pattern Recognition. Retrieved from https://arxiv.org/ abs/1504.00325

[5]. Faust, O., Hagiwara, Y., Hong, T. J., Lih, O. S., & Acharya, U. R. (2018). Deep learning for healthcare applications based on physiological signals: A review. Computer Methods and Programs in Biomedicine, 161, 1-13. https://doi.org/10.1016/j.cmpb.2018.04.005

[6]. Jianglin, Y., Zhigang, G., & Gang, C. (2019, February). Recurrent convolution attention model (RCAM) for text generation based on title. In Journal of Physics: Conference Series (Vol. 1168, No. 5, p. 052049). IOP Publishing.

[7]. Johnson, J., Karpathy, A., & Fei-Fei, L. (2016). Densecap: Fully convolutional localization networks for dense captioning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4565- 4574).

[8]. Li, X., Jiang, S., & Han, J. (2019, July). Learning object context for dense captioning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 8650- 8657). https://doi.org/10.1609/aaai.v33i01.33018650

[9]. Vinyals, O., Toshev, A., Bengio, S., & Erhan, D. (2015). Show and tell: A neural image caption generator. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 3156-3164).

[10]. Ya, J., Liu, T., Li, Q., Lv, P., Shi, J., & Guo, L. (2018, October). Fast and accurate typosquatting domains evaluation with Siamese networks. In Proceedings of IEEE Military Communications Conference (MILCOM 2018) (pp. 58-63). IEEE. https://doi.org/10.1109/MILCOM.2018. 85 99686

[11]. Zitnick, C. L., & Dollár, P. (2014, September). Edge boxes: Locating object proposals from edges. In European Conference on Computer Vision (pp. 391- 405). Cham: Springer. https://doi.org/10.1007/978-3-319- 1060 2-1_26

Full Article (HTML)

Pdf

Research Paper

Medical Image Encryption Technique using DNA Cryptography

Naga Raju C * , M. K. Gupta**

* Department of Computer Science and Engineering, Srinivasa Ramanujan Institute of Technology (Autonomous), Anantapur, Andhra Pradesh, India.

** Department of Computer Science and Engineering, YSR Engineering College of Yogi Vemana University, Proddatur, Andhra Pradesh, India.

Kumari, K. S., and Raju, C. N. (2020). Medical Image Encryption Technique using DNA Cryptography. i-manager's Journal on Information Technology, 9(2), 27-35. https://doi.org/10.26634/jit.9.2.17760

Abstract

In the medical field, telemedicine, smart health and e-health, are cutting-edge technologies. These technologies utilize digital medical information for end-user communication. Even though this digitalization reduces time, it is a open source for hackers. Hence, hackers can tamper the digital medical image during broadcast. In the medical field, most of the investigations are done through X-rays, MRI and CT scan images. Security must be provided to maintain secrecy of diseases for avoiding the panic in the patients and for improving the degree of security in the image broadcast through internet. The DNA cryptography provides powerful security to enhance the probability of preventing from the brute-force and statistical analysis attacks. In this paper, two level security is provided using DNA codons. In first level, image is encrypted into DNA sequences by selecting key. In second level, codons are generated with dynamic numbers for encryption of image and construct DNA alphabets. In this technique, the encrypted image is in hidden format so that it is very difficult for attacker with known image attacks. The experimental results of the proposed technique are investigated with histogram based method and statistical analysis attacks and confirmed the superior security level in the protection of the image transmission.

References

[1]. Awad, A., & Awad, D. (2010). Efficient image chaotic encryption algorithm with no propagation error. ETRI Journal, 32(5), 774-783. https://doi.org/10.4218/etrij.10. 1510.0063

[2]. Chirkkarottu, S., & Mathew, S. (2013). Summarization on DNA cr yptography. International Journal of Engineering Research & Technology (IJERT), 2(11), 303- 306.

[3]. Enayatifar, R., Abdullah, A. H., & Lee, M. (2013). A weighted discrete imperialist competitive algorithm (WDICA) combined with chaotic map for image encryption. Optics and Lasers in Engineering, 51(9), 1066- 1077. https://doi.org/10.1016/j.optlaseng.2013.03.010

[4]. Kadir, A., Hamdulla, A., & Guo, W. Q. (2014). Color image encryption using skew tent map and hyper th chaotic system of 6 -order CNN. Optik, 125(5), 1671- 1675. https://doi.org/10.1016/j.ijleo.2013.09.040

[5]. Kanso, A., & Ghebleh, M. (2012). A novel image encryption algorithm based on a 3D chaotic map. Communications in Nonlinear Science and Numerical Simulation, 17(7), 2943-2959. https://doi.org/10.1016/j.c nsns.2011.11.030

[6]. Kaundal, A. K., & Verma, A. K. (2014). DNA based cryptography: A review. International Journal of Information and Computation Technology, 4(7), 693- 698.

[7]. Li, H., Huang, Q., Shen, J., Yang, G., & Susilo, W. (2019). Designated-server identity-based authenticated encryption with keyword search for encrypted emails. Information Sciences, 481, 330-343. https://doi.org/10. 1016/j.ins.2019.01.004

[8]. Lu, Y., Wang, G., Li, J., & Shen, J. (2017). Efficient designated server identity-based encryption with conjunctive keyword search. Annals of Telecommunications, 72(5-6), 359-370. https://doi.org/10.1007/s12243-017-05 74-7

[9]. Mazloom, S., & Eftekhari-Moghadam, A. M. (2009). Color image encryption based on coupled nonlinear chaotic map. Chaos, Solitons & Fractals, 42(3), 1745- 1754. https://doi.org/10.1016/j.chaos.2009.03.084

[10]. Noroozi, M., Karoubi, I., & Eslami, Z. (2018). Designing a secure designated server identity-based encryption with keyword search scheme: Still unsolved. Annals of Telecommunications, 73(11-12), 769-776. https://doi.org/10.1007/s12243-018-0653-4

[11]. Sidorenko, A. V., & Shishko, M. S. (2016). Encryption of Image using DNA-sequences, chaotic dinamics and hash functions. Doklady BGUIR (in Russian). 5, 42-47.

[12]. Wang, Q., Zhang, Q., & Zhou, C. (2009, October). A multilevel image encryption algorithm based on chaos and DNA coding. In 2009, Fourth International Conference on Bio-Inspired Computing (BICTA), (pp. 1-5). IEEE. https://doi.org/10.1109/BICTA.2009.5338154

[13]. Wang, X. F., Mu, Y., Chen, R., & Zhang, X. S. (2016). Secure channel free id-based searchable encryption for peer-to-peer group. Journal of Computer Science and Technology, 31(5), 1012-1027. https://doi.org/10.1007/s 11390-016-1676-9

[14]. Yin, C. (2019). Encoding DNA sequences by integer chaos game representation. Journal of Computational Biology, 26(2), 143-151. https://doi.org/10.1089/cmb.20 18.0173

[15]. Zhang, X., Shao, L., Zhao, Z., & Liang, Z. (2014). An image encryption scheme based on constructing large permutation with chaotic sequence. Computers & Electrical Engineering, 40(3), 931-941. https://doi.org/10. 1016/j.compeleceng.2013.08.008

Full Article (HTML)

Pdf

Research Paper

Acknowledgement based Topology Control using Hybrid Cryptography for MANETS

Thamizhmaran K.*

Department of ECE, Government College of Engineering, Bodinayakkanur, Theni, Tamilnadu, India.

Thamizhmaran, K. (2020). Acknowledgement based Topology Control using Hybrid Cryptography for MANETS. i-manager's Journal on Information Technology, 9(2), 36-44. https://doi.org/10.26634/jit.9.2.17852

Abstract

Mobile Ad hoc Network (MANET) is the significant technology among various wireless communication technologies where all the nodes are mobile and which can be connected to dynamically used wireless link in a random manner. They connect or disconnect from the active network any time and transfer packets in a single or a multicast mode. Nodes are connected by way of wireless links and form a random topology. This research paper focuses on, performance comparison of a new Intrusion Detection Systems (IDS), Secure-Enhanced Adaptive 3 Acknowledgement with hybrid cryptography's EA3ACK-MARS4 and EA3ACK-ECC specially designed for MANET. Furthermore, all the above mentioned protocols are compared based on several important performance metrics which are Packet Delivery Ratio (PDR), end-toend delay and average energy via one of the efficient networking routing protocol called Network Simulator 2 (Ns2). It is used to implement and test the suggested system under various size of topology with different constant sets of nodes as well as comparing the results with two different protocols.

References

[1]. Basabaa, A., Sheltami, T., & Shakshuki, E. (2014). Implementation of A3ACKs intrusion detection system under various mobility speeds. Procedia Computer Science, 32, 571-578.

[2]. Choi, J., Cha, S. H., Park, G., & Song, J. (2005). Malicious nodes detection in AODV-based mobile ad hoc networks. GESTS International Transactions on Computer Science and Engineering, 18(1), 49-55.

[3]. Johnson, D., Maltz, D., Hu, Y., & Jetcheva, J. (2002). The Dynamic Source Routing Protocol for Mobile Ad-hoc Networks [Internet Draft]. IETF MANET Working Group. Retrieved from https://tools.ietf.org/html/draft-ietf-manetdsr- 07

[4]. Li, C. (2011). Secure routing for wireless mesh networks. International Journal of Network Security,13(2), 109-120.

[5]. Liu, K., Deng, J., Varshney, P. K., & Balakrishnan, K. (2007). An acknowledgment-based approach for the detection of routing misbehavior in MANETs. IEEE Transactions on Mobile Computing, 6(5), 536-550.

[6]. Mathew, S., & Jacob, K. P. (2006, September). A novel fast hybrid cryptographic system: MARS4. In 2006 Annual IEEE India Conference (pp. 1-5). IEEE.

[7]. Perkins, C. E., & Belding-Royer, E. (2001). Quality of Service in Ad-hoc on-demand Distance Vector Routing [Internet Draft]. IETF MANET Working Group. Retrieved from https://tools.ietf.org/html/draft-perkins-manet-aodvqos-00

[8]. Prabu, K., & Subramani, A. (2014). Energy efficient routing in MANET through edge node selection using ESPR algorithm. International Journal of Mobile Network Design and Innovation, 5(3), 166-175.

[9]. Shakshuki, E. M., Kang, N., & Sheltami, T. R. (2012). EAACK: A secure intrusion-detection system for MANETs. IEEE Transactions on Industrial Electronics, 60(3), 1089- 1098.

[10]. Thamizhmaran, K. (2012). Secure routing protocol in MANET: A survey. International Journal of Advance Research in Technology, 3(3), 9-14.

[11]. Ukey, A. S. A., & Chawla, M. (2010). Detection of packet dropping attack using improved acknowledgement based scheme in MANET. International Journal of Computer Science Issues, 7(4).

i-manager's Journal on Information Technology (JIT)

Current Issue Vol. 12 Issue 4

Most Read

Most Cited

Volume 9 Issue 2 March - May 2020

Privacy Preservation in Big Data Application using Advanced Encryption Standard and Least Significant Bit Steganography

Abdulmalik Danlami Mohammed * , Oluwaseun A. Ojerinde **, Moses Folorunsho Victor ***, M. L. Agrawal****

*-**** Department of Computer Science, School of Information and Communication Technology, Federal University of Technology, Minna, Nigeria.

Mohammed, A. D., Ojerinde, O. A., Victor, M. F., and Kenneth, M. O. (2020). Privacy Preservation in Big Data Application using Advanced Encryption Standard and Least Significant Bit Steganography. i-manager's Journal on Information Technology, 9(2), 1-11. https://doi.org/10.26634/jit.9.2.17550

Abstract

References

Full Article (HTML)

Pdf

Comparitive Analysis between Two Security Models of NoSQL Database

M. Somasundara Rao * , K. Venkata Rao**, M. H. M. Krishna Prasad***

Rao, M. S., Rao, K. V., and Prasad, M. H. M. K. (2020). Comparitive Analysis between Two Security Models of NoSQL Database. i-manager's Journal on Information Technology, 9(2), 12-19. https://doi.org/10.26634/jit.9.2.17685

Abstract

References

Full Article (HTML)

Pdf

Dense Captioning of Images

Shreyas More * , Amrutesh Taral**, Bhavya Shah***, Sneh Joshi****, Kirankumari Sinha *****

* Department of Computer Science, Indian Institute of Technology, Kharagpur, West Bengal, India. **-***** Department of Information Technology, K J Somaiya College of Engineering, Mumbai, Maharashtra, India.

More, S., Taral, A., Shah, B., Joshi, S., and Sinha, K. (2020). Dense Captioning of Images. i-manager's Journal on Information Technology, 9(2), 20-26. https://doi.org/10.26634/jit.9.2.17308

Abstract

References

Full Article (HTML)

Pdf

Medical Image Encryption Technique using DNA Cryptography

Naga Raju C * , M. K. Gupta**

* Department of Computer Science and Engineering, Srinivasa Ramanujan Institute of Technology (Autonomous), Anantapur, Andhra Pradesh, India. ** Department of Computer Science and Engineering, YSR Engineering College of Yogi Vemana University, Proddatur, Andhra Pradesh, India.

Kumari, K. S., and Raju, C. N. (2020). Medical Image Encryption Technique using DNA Cryptography. i-manager's Journal on Information Technology, 9(2), 27-35. https://doi.org/10.26634/jit.9.2.17760

Abstract

References

Full Article (HTML)

Pdf

Acknowledgement based Topology Control using Hybrid Cryptography for MANETS

Thamizhmaran K.*

Department of ECE, Government College of Engineering, Bodinayakkanur, Theni, Tamilnadu, India.

Thamizhmaran, K. (2020). Acknowledgement based Topology Control using Hybrid Cryptography for MANETS. i-manager's Journal on Information Technology, 9(2), 36-44. https://doi.org/10.26634/jit.9.2.17852

Abstract

References

Full Article (HTML)

Pdf

Abdulmalik Danlami Mohammed * , Oluwaseun A. Ojerinde , Moses Folorunsho Victor *, M. L. Agrawal****

M. Somasundara Rao * , K. Venkata Rao, M. H. M. Krishna Prasad*

Shreyas More * , Amrutesh Taral, Bhavya Shah, Sneh Joshi, Kirankumari Sinha

* Department of Computer Science, Indian Institute of Technology, Kharagpur, West Bengal, India.

-*** Department of Information Technology, K J Somaiya College of Engineering, Mumbai, Maharashtra, India.

* Department of Computer Science and Engineering, Srinivasa Ramanujan Institute of Technology (Autonomous), Anantapur, Andhra Pradesh, India.

** Department of Computer Science and Engineering, YSR Engineering College of Yogi Vemana University, Proddatur, Andhra Pradesh, India.