Environmental Benefits of Enhanced Hecc- Elgamal Cryptosystem for Security in Cloud Data Storage Using Soft Computing Techniques

T. Devi, R. Ganesan

Ekoloji, 2019, Issue 107, Pages: 665-677, Article No: e107029


Download Full Text (PDF)


Cloud services is used by many organizations and it has captured a major segment of the competitive market today. The green, or eco-friendly, aspect of the cloud is one of the most multifaceted advantages of cloud computing. The environmental advantages of cloud services include: reducing a firm’s carbon footprint, data center efficiency, dematerialization, saving green, educed electricity use and so on. Even with its unprecedented growth, the question of security is also of paramount concern among the users of cloud services. There is a huge demand for new protocols and tools in order to enhance and assess the security strength of its service. Notwithstanding the present methods used for encrypting the files in cloud they are not highly efficient. Hence this enhanced technique is proposed to overcome all these challenges and improve the environmental benefits. In this method, initially the authentication of the user is verified. Once the authentication of the user is verified successfully dual encryption is performed on the cloud stored files using ElGamal cryptosystem and Hyper Elliptical Curve Cryptography (HECC). The aim for using the proposed system is for analysis of security which can be enhanced through the technique of sharing many keys amongst the two parties. Integer selection is an important attribute which defines the proper security to the cloud storage. For ensuring high security, this integer selection is performed by utilizing BAT algorithm. After the encryption, the suggested technique uses the HECC algorithm. In HECC, key generation is done by point addition and point doubling based elliptic curve cryptography. The dual encryption in this method provides efficient security to the cloud data. The proposed technique performance is evaluated in reference with environmental protection, storage cost, computation cost and execution time and is implemented in JAVA. The experimental results show the efficacy of the system as it utilizes only less time for both encryption and decryption of sensitive data.


environmental benefits, cloud services, ElGamal cryptosystem, Hyper Elliptical Curve Cryptography, BAT algorithm, point addition, point doubling and elliptic curve cryptography


  • Ali M, Khan SU, Vasilakos AV (2015) Security in cloud computing: Opportunities and challenges. Information Sciences, 305: 357-383.
  • Al-Sharif, F. M (2017) Correlation between serum alanine aminotransferase activity and immunologic response and body mass index in obese patients with chronic hepatitis B virus infection. European Journal of General Medicine, 14(2), 34-37. doi: 10.29333/ejgm/81879
  • Batista BG, Gomes Ferreira CH, Marim Segura DC, Leite Filho DM, Maciel Peixoto ML (2016) A QoS-driven approach for cloud computing addressing attributes of performance and security. Future Generation Computer Systems, 68: 260-274.
  • Chang V, Kuo Y-H, Ramachandran M (2016) Cloud computing adoption framework: A security framework for business clouds. Future Generation Computer Systems, 57: 24-41.
  • Eryılmaz D, Ece A (2016) Evaluation of Follow-up Results in Children with Henoch-Schönlein Purpura. J Clin Exp Invest, 7(4):269-77. doi: 10.5799/jcei.328558
  • Gupta PC (2014) Evaluation of Antifertility Potential of Ficusbengalensis (Linn.) in Male Albino Mice. International Journal of Pharmacy Research & Technology, 4: 05-09.
  • Hussain SA, Fatima M, Saeed A, Raza I, Khurram Shahzad R (2016) Multilevel classification of security concerns in cloud computing. Applied Computing and Informatics: 1-9.
  • Jouini M, Arfa Rabai LB (2016) Comparative Study of Information Security Risk Assessment Models for Cloud Computing systems. Procedia Computer Science, 83: 1084-1089.
  • Khan N, Al-Yasiri A (2016) Identifying cloud security threats to strengthen cloud computing adoption framework. Procedia Computer Science, 94: 485-490.
  • Manogaran G, Thota C, Kumar MV (2016) Meta Cloud Data Storage architecture for Big Data security in cloud computing. Procedia Computer Science, 87: 128-133.
  • Ramachandran M (2016) Software security requirements management as an emerging cloud computing service. International Journal of Information Management, 36(4): 580-590.
  • Rao RV, Selvamani K (2015) Data security challenges and its solutions in cloud computing. Procedia Computer Science, 48: 204-209.
  • Rasheed H (2014) Data and infrastructure security auditing in cloud computing environments. International Journal of Information Management, 34(3): 364-368.
  • Rohini S, Sharanya M, Vidhya A, Viji S, Poornima P (2017) Proximity Coupled Microstrip Antenna for Bluetooth, WIMAX and WLAN Applications. International Journal of Communication and Computer Technologies, 5: 48-52.
  • Shaikh R, Sasikumar M (2015a) Data classification for achieving security in cloud computing. Procedia computer science, 45: 493-498.
  • Shaikh R, Sasikumar M (2015b) Trust model for measuring security strength of cloud computing service. Procedia Computer Science, 45: 380-389.
  • Singh AP, Pasupuleti SK (2016a) Optimized Public Auditing and Data Dynamics for Data Storage Security in Cloud Computing. Procedia Computer Science, 93: 751-759.
  • Singh S, Jeong Y-S, Park JH (2016b) A survey on cloud computing security: Issues, threats, and solutions. Journal of Network and Computer Applications, 75: 200-222.
  • Sookhak M, Gani A, Khan MK, Buyya R (2016) Dynamic remote data auditing for securing big data storage in cloud computing. Information Sciences, 380: 101-116.
  • VenkateswaraRao N, Venkateswarlu Ch (2017) Hybrid ABC optimization based interference cancellation in MIMO-OFDM. 2017 2nd International Conference on Communication and Electronics Systems (ICCES).
  • Vurukonda N, Rao BT (2016) A study on data storage security issues in cloud computing. Procedia Computer Science, 92: 128-135.
  • Wei L, Zhu H, Cao Z, Dong X, Jia W, Chen Y, Vasilakos AV (2014) Security and privacy for storage and computation in cloud computing. Information Sciences, 258: 371-386.
  • Yang LT, Huang G, Feng J, Xu L (2016) Parallel GNFS algorithm integrated with parallel block Wiedemann algorithm for RSA security in cloud computing. Information Sciences: 1-27.
  • Zhang Y, Chen X, Li J, Wong DS, Li H, You I (2016) Ensuring attribute privacy protection and fast decryption for outsourced data security in mobile cloud computing. Information Sciences, 379: 42-61.
  • Zhao J, Wang L, Tao J, Chen J, Sun W, Ranjan R, Kołodziej J, Streit A, Georgakopoulos D (2014) A security framework in G-Hadoop for big data computing across distributed Cloud data centres. Journal of Computer and System Sciences, 80(5): 994-1007.