International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 A Review on Biometric Encryption System in Cloud Computing Mehreen A, Xiufeng Liu, Sheraz Arshad, Nosheen Nazir, Mubeen Fatima Riphah International University, Faisalabad, Pakistan National University of Science and Technology, Islamabad, Pakistan Abstract This Review paper is about the security of bio metric templates in cloud databases. Biometrics is proved to be the best authentication method. However, the main concern is the security of the biometric template, the process to extract and stored in the database within the same database along with many other. Many techniques and methods have already been proposed to secure templates, but everything comes with its pros and cons, this paper provides a critical overview of these issues and solutions. Key words; Cloud Computing, Biometrics, Cloud Databases, Cryptography, Quantum Cryptography, Cognitive Cryptography, DNA Storages 1. Introduction Basic Objective of this review paper is to safely store and retrieve the biometric templates inside the Cloud Data bases. Cloud Computing is an IT paradigm that enables access to one common pool of configured systems and provide higherlevel of services with minimal effort. Cloud security is a data set of policies, technologies and rules to protect data, applications, and the infrastructure of cloud computing. Mostly enterprise use cloud to store and maintain large data. Cloud security has become a concern for both cloud users and providers. Traditionally authentication like key generation, passwords, mostly encryption mechanism has failed making data insecure from intruders and black hat hacker. Biometrics is the technical term for calculating and measuring different body parts by relating metrics to human characteristics. Biometrics authentication is used to control realistic identification and is unique for every person or individual. With increase demand of security, I recommend at using biometrics for the authentication process at cloud level. Biometrics is a combination of feature extractor, sensors and matching parts or modules which implements recognition algorithms on particular biometric pattern. The sensor works by scanning the biometric trait and give output in digital form. The check and control is done to ensure that the output sample is reliable and safe for feature extraction and matching modules Now, authentication and verification are considered as the most important goals to be fulfilled for the physical world (the world to live in) or the virtual world (Internet). Different techniques exist to authenticate and verify the user such as passwords, smart cards, pins, and other authentication tokens which include biometrics like finger prints, a retina, iris, facial expressions, voice, signatures and face. Among all the authentication techniques present because of the uniqueness biometrics is considered as the most reliable authenticators. Biometric cryptosystem, as the name suggest, take the original template and give out the encrypted template which reveals the least amount/zero percent of information about the original template. Due to this characteristic, the security of such systems is said to be high. 10 International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 11 Fig. 1: Basic Biometric process. The above diagram is depicting the basic authentication process of template extraction, matching and storing. Consist of four basic steps: • Sensors : To detect biometric • Signal processing: Clear feature extraction • Pattern Matching: Closely matched to the original template. • Decisions: True or false match • These steps are used to extract and store the biometrics free of noise and signal losses. It should be complete and secure to be stored in the database by discarding unclear and ambiguous or clone templates. Biometrics are used to prevent third party attacks, unauthorized means and provide valuable confidence among the individuals. Authentication and verification are considered as the most important goals to be fulfilled for the physical world (the world to live in) or the virtual world (Internet). Different techniques exist to authenticate and verify the user such as passwords, smart cards, pins, and other authentication tokens which include biometrics like finger prints, a retina, iris, facial expressions, voice, signatures and face. Among all the authentication techniques present because of the uniqueness biometrics is considered as the most reliable authenticators. Biometric cryptosystem, as the name suggest, take the original template and give out the encrypted template which reveals the least amount/zero percent of information about the original template. Due to this characteristic, the security of such systems is said to be high. To prevent our biometric templates we use various techniques to save in a secure manner and detect error if any. Techniques for error-correcting code are § fuzzy vault scheme (Integers) § fuzzy commitment scheme (bits of string) Usage of keys include A key-binding biometric cryptosystem is a secret key and the biometric data is connected with a reference template to generate helper data. Helper data is the public data to store the biometric template by removing variations and hiding the original template. International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 12 A key-generation biometric cryptosystem, the key is generated from the biometric itself and don't need any extra cryptographic key to secure the template. There is no issue of the key security yet generation of a stable cryptographic key in the presence of intra-class variations exists. The Quantization process has also been employed in the various key generating techniques to remove the intra-class variations during the key extraction process. This paper is being classified as Section II and III dedicates for related work Section IV provides us a proposed solution for this paper and Section V concludes the effort of this review paper Table 1: Biometric Issues and Future work S No. Year Proposed Algorithms Pros Future Work 1 2018 Novel Biometric Inspired Homomorph ic Encryption Algorithm (Bihea) Encrypts the user information at run-time Real test with distributed computing 2 2018 Biometricsas -a-Service (BaaS) continuous innovation is encouraged Execution and rendering micro payments to the correspondi ng developer Need of Optimal matching algorithm selection 3 2018 Advanced Minutiae Base Algorithm (AMBA) +Advance Encryption Standard (AES) algorithm Usage of multi model authenticati on with one biometric technique Need to use scheme with more than one biometric technique. 4 2018 Multimodal authenticati on system Using biometrics for the edge centric cloud Need to generate the secret key to enhance the security 5 2018 Splitting and distributing secret parts using cognitive cryptograph y techniques Manage strategic information Semantic interpretation of personal traits using non-standard bio metric specifications 6 2018 BEBA (Biometric encoding and Biometric authenticati on) Blowfish has been used in data protection and key safety managemen one time passwords and level of encryption can be enhanced International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 13 t 7 2017 effective security patch to Cloud BI secure against enrollmentlevel

attackers Ca be made efficient for random value 8 2017 Biometric data Encryption and Matching algorithms High level of privacy Protection Can be tested with matrix value items 9 2017 Bio-hashing Multi-cloudserver with Biometrics + ECC. Can be evaluated for simulation in real-world environment 10 2017 Biometric Authenticati on Reduces threat and load on resources Secure Privacy for biometric authentication is required 3. Literature Review This section of Literature Survey is related to some important modules, algorithms and facts of Biometric Authentication on the basis of author analysis. The author has introduced a novel biometric inspired homomorphic encryption algorithm (BIHEA) for securing data transmission of files in cloud at the hybrid level. Algorithm encrypts all the user data by providing unique one-time password and help against phishing and shoulder surfing. (Bala et al, 2018) The author proposed a Biometrics-as-a-Service (BaaS) framework to perform biometric matching in cloud devices for providing privacy and security. The author used Linux-based virtual machine environment for fake logging and data theft to authenticate the cloud. (Talreja et al, 2018) In this paper the author introduced a biometric authentication with encryption and compression of data. For providing security Advanced Encryption Standards algorithm is used generate the secret key with its feature extraction from fingerprint biometrics using algorithm named as Advanced Minutiae Base Algorithm (AMBA). In the end the secret value is encrypted with generated biometric key using Advanced Encryption Standard (AES) Algorithm. (chand et al, 2018) In this paper, author use multi model authentication using one biometric technique. He proposed a model based on Advanced Minutiae Base Algorithm (AMBA) and Advance Encryption Standard (AES) algorithm, which reduces the computational load on the cloud and securing identity of the person by disclosing or decrypting with the relevant / same secret key. (ali et al, 2018) The author discussed cognitive cryptography to secure data by splitting it among different groups of trustees. Most of the safety problems are associated with authentication and information protection with respect to cloud security alliance (CSA). (Ogiela et al, 2018) The author introduced a new protocol, BEBA (Biometric encoding and Biometric authentication) to overcome all the security problems in cloud surroundings. In BEBA protocol, identity verification has been combined with template protection in conjunction with completely different and powerful (RC4, RSA, AES and 3DES) encryption algorithms for accumulated safety. Blowfish has been used in data protection and key safety management. (ArunPrakash et al, 2018) The author proposed the security of Cloud Biometric identification and proved how vulnerable it could be against enrollment-level attackers. The security assumption of Cloud BI does not capture attacks, like unauthentic user on to databases. He designed the attack model and showed how an attacker enrolls and exploits in order to recover authentic finger code. (Hahn et al, 2017) The author proposed a cloud identification model for outsourcing storage by utilizing matric and perturbed terms. First, the correctness of biometric identification International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 14 is achieved. Secondly, privacy and efficiency of the biometric identification scheme is guaranteed against Level II and Level III attacks. (zhang et al, 2017) The author proposed bio hashing and elliptic curve cryptography for the multi-server cloud for securing cloud biometric authentication and also allowing ECCbased protocols from Diffie-Hellman. (kumara et al,2017) The author proposed enrolment and verification process in Bio AaaS reduces the threat of data theft and reduces the load on resources. The template is then stored and encrypted using Reverse Circle Cipher algorithm and Pearson's formula. If the value comes closer to 1 than the two templates are considered same and the user is considered authenticated and allowed log in credentials to the cloud. (Gawade et al, 2017) According to the above table Major problems lies in • Exact matching of templates. • A Real time implementation of data due to software and hardware cost. • Security concerns while storing and extracting the templates • Moving template from device to the database • Generation of secret keys • Middle man Attacks And Future goals may be concerned with • Maintaining standards • Securing Biometrics while Ageing ,Illness or Injury • Controlling Environmental conditions, proper user training and usability factors. • Increasing security level • Increasing storage level As big data owners are willing to preserve privacy by making use of user data in the form of biometric information by encrypting to the cloud databases to enroll and identify users by decrypting. Apart from various problems and solutions disused in this review paper, in the future, more complex architecture and the beneficial statistical evidences should be studied. Let us have a look on its pros and cons; in the pros mode it's hard to fake because of uniqueness. It provides convenience while applying passwords. It's stable and changes very little in whole life. It provides strong authentication and accountability. Templates are non-transferable, less time consuming and more security required for identification may be less than five seconds. On the other side Authenticity of a biometric is captured and mapped to specific identity. Lack of accuracy and privacy in retrieving data and saving can lead to system failure. Error in biometric device i.e. false rejects and false accepts. High cost in maintaining, integrating the systems up and running and also storing and saving biometrics. It's not for physically disabled persons. 4. Proposed Solution Depending on the need Biometric is all about person verification and identity. Matching a sample against a single stored template is called verification. Searching a sample against many stored templates in the database is called identification. International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 15 Different biometric templates include following biometric systems: Facial recognition DNA Voice recognition Hand Geometry Signature recognition Finger Print Retinal scanning Iris recognition All the above mentioned system is individually easy, accurate and somehow reliable, but short coming are due to high cost and security. In spite of the fact, with previous problems disused in literature review section while moving, storing and extracting templates to and from cloud data bases, I think with use of the hybrid of Cognitive and Quantum cryptography approach we can resolve this security issues. Let us see the basic concepts of both approaches. Cognitive Cryptography Cognitive cryptography is used by splitting it and distributing the divided parts among selected groups of secret or concerned trustees for securing information. The process is concerned with concealing data by distributing secret parts or shadows with the use of cognitive techniques describing the personal information contained in each biometric template. It's very innovative and useful tool for securing data. Pros: Used for data retrieval, data storage and data transfer in a secured manner. Cons: Efficiency hinders because of level of security provided, computational speed, key size, cost and the algorithm. Solution: Choosing the accurate bit for keys length in encryption and decryption data. Symmetric key algorithm can be used because of its high computational speed and low key size. (Ogiela et al, 2018) Quantum cryptography Quantum cryptography is used for secret communications. Its basic goals are the CIA triad – Confidentiality, Integrity, and Availability. The Quantum Key Distribution is used for producing random key for communication between sender and a receiver. Key distribution assures no third party is involved. Quantum key Protocols or algorithms • BB84 • B92 • EPR. These protocols communicate by interchanging qubits using quantum channel by applying sequence of key bits. Cloud Computing service providers include big players like Google, Microsoft, Apple, Amazon and many other. The data transfer occurs at network level and storage level where allocation of resources and scheduling is provided by the cloud vendors. Also, help by preventing the breakthrough in malicious programs increasing cloud security. Every day hackers are trying to hack into some cloud even Apple and Dropbox being compromised, 10 cloud securities has become a new area of concern for researchers as well. Proposed Algorithm Hybrid of Cognitive and Quantum Cryptography By Hybrid of cognitive and quantum cryptography advantages of both cryptography techniques are merged. There by achieving our basic goal of safely encrypting, storing, decrypting and extracting the required template from data bases. Consist of following steps: 1. Sensors : To detect biometric 2. Signal processing : Clear feature extraction 3. Cryptography approach: • Quantum cryptography: To generate a secret key International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 16 • Cognitive cryptography: To Distribute template into sub templates 4. Template Storage: Store at different cloud databases or different parts of the same data base 5. Apply Cognitive Cryptography : To gather distributed parts of concerned template 6. Merger: Merge the distributed parts as one template 7. Pattern Matching: Closely matched to original template by using quantum secret key to avoid middle man attacks or data losses 8. Decisions: Is it true or false match. Figure 2.The Proposed Bio metric Process Problem The major drawback I think in this proposed solution can be of larger space and storage. The issue in qu bits and man in the middle attack is the second problem. There is a need to distribute, store and extract the biometric templates. Qu bit problem is related to automatic flip flop in the number of bits, here 1 become 0 and 0 become 1. Time consumption can also be increased but CIA goals are going to be fully accomplished. Solution The template is secure and safe to be retrieved later for usage. However, for avoiding issues of larger space and storages, templates can be stored in DNA Storages inside the cloud. Figure 3.Working of DNA storage inside the Cloud DNA is durable and long lasting, three basic steps Encoding: To convert template into 0 1 format Storing: To store in DNA databases International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 17 Sequencing: To Retrieve stored template. DNA uses long sequences of smaller molecules, called nucleotides – A for adenine, C for cytosine, T for thymine and G for guanine and creating sequences of 0s and 1s to store all type of data including picture, text, books, video and movies. Smaller chunks are made while storing data and on the retrieval, indicator is used to ensure the completeness. After the creation of DNA strand data is stored them in cold and blocks water and light to keep them dry. Time consuming and relatively slow even to take small information stored on a particular DNA, user have to go through all the data present on that DNA container. Two major reasons to use DNA Storages inside the cloud for safe and secure means of storing and retrieving the data 1. Traditional methods to store data might not be able to store the large amount of Big data 2. A single strand of DNA has quite a long life about millions of years to store that data safely. Similarly, to avoid qu bits attack, lattice based cryptography can be used. Instead of bits the geometric objects will be used to send and store data. They are powerful and resistant to quantum attacks. Lattice based cryptography can be used to construct cryptographic primitives and boundaries Also help in hiding the data identity. For example, during auctions or data mining, during voting's and negotiations. Table 2: Biometric main Problems and Solutions Area Problem Solution Biometric Templates Storage Cloud Data Bases Cloud Data Bases Insecure Cryptography Cryptography Key distribution Quantum Cryptography Quantum Cryptography Size, traffic, and delay of data Qu bits Hybrid of QC algorithms and Pair Hand protocol or Lattice based Cryptography Hybrid of QC algorithms and Pair Hand protocol Heavy computation cost Cognitive Cryptography Cognitive Cryptography Complex computing power Hybrid of cognitive and quantum cryptography Hybrid of cognitive and quantum cryptography High storage required for storing distributed templates Hybrid of QC+CC=DNA Storages DNA Storages Time Consuming Portability Expensive Still in working how to overcome the limitations of DNA Storages This review article critically analyzes the existing methods of storing biometric templates onto DNA to store massive amounts of data. 5. Conclusion Short comings of DNA storage can be removed with some efficient algorithm like Genetic Algorithm for searching and scheduling requested data from the DNA data bases. Short comings of quantum cryptography can be reduced by using lattice based cryptography thus securing our templates more efficiently. As users are increasing day by day identification of a biometric template also requires more resources to compute, store, extract and scan records of a database to find best possible match. International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 18 This Review paper proposed a new cloud computing environment, which suggests future work by applying hybrid of Cognitive and Quantum key distribution while storing biometric templates in cloud DNA data base. International journal of Computer Science & Network Solutions http://www.ijcsns.com March.2018 -Volume 6.No.1 ISSN 2345-3397 19 References i. Bala, Y., & Malik, A. (2018). Biometric Inspired Homomorphic Encryption Algorithm for Secured Cloud Computing. In Nature Inspired Computing (pp. 13-21). Springer, Singapore. ii. Talreja, V., Ferrett, T., Valenti, M. C., & Ross, A. (2018, January). Biometrics-as-a-service: A framework to promote innovative biometric recognition in the cloud. In Consumer Electronics (ICCE), 2018 IEEE International Conference on(pp. 16 ). IEEE. iii. Chand, K. S., & Rani, B. K. (2018). Biometric Authentication using SaaS in Cloud Computing. iv. Ali, Z., Hossain, M. S., Muhammad, G., Ullah, I., Abachi, H., & Alamri, A. (2018). Edge-centric multimodal authentication system using encrypted biometric templates. Future Generation Computer Systems. v. Ogiela, M. R., & Ogiela, L.(2018) Cognitive cryptography techniques for intelligent information management. International Journal of Information Management, 40, 21-27. vi. Tadapaneni, N. R. (2017). Different Types of Cloud Service Models. Available at SSRN 3614630. vii. Hahn, C., Shin, H., & Hur, J. (2017, July). Cloud-based biometrics processing for privacy-preserving identification. In Ubiquitous and Future Networks (ICUFN), 2017 Ninth International Conference on (pp. 595-600). IEEE. viii. Zhang, C., Zhu, L., & Xu, C. (2017). PTBI: An efficient privacy-preserving biometric identification based on perturbed term in the cloud. Information Sciences, 409, 56-67. ix. Kumari, S., Li, X., Wu, F., Das, A. K., Choo, K. K. R., & Shen, J. (2017). Design of a provably secure biometrics-based multicloud -server authentication scheme. Future Generation Computer Systems, 68, 320-330. x. Gawade, S., Bharti, A., Raj, A., & Madane, S. (2017). Biometric Authentication using Software as a Service in Cloud Computing. International Journal Of Engineering And Computer Science, 6(3). xi. ArunPrakash, R., Jayasankar, T., & Vinothkumar, K. (2018). Biometric Encoding and Biometric Authentication (beba) Protocol for Secure Cloud in M-Commerce Environment. Appl. Math, 12(1), 255-263. xii. Panimalar, A., Dharani, N., Aiswarya, R., & Shailesh, P. (2017). Cloud Data Security Using Elliptic Curve Cryptography. Author's Profile Mehreen Ansar received the B.S. degrees in Computer Engineering from Bahauddin Zikariya University, Multan in 2012 and doing Master degree from Riphah International University, Faisalabad 2017 to 2019, respectively. Her BS project was based on Server Clustering, done with Windows Server 2008 and Linux. She is working as a web developer since 2012. Her domain lies in networking and security. Her main areas of research are Server Clustering; Cryptography, Cryptography protocols in Cloud Computing, Biometrics, and Cloud Migration. Mubeen Fatima was born in Faisalabad; Punjab, Pakistan in 1993.She received the BS degree in Software Engineering from National University of Sciences and Technology (NUST), Islamabad in 2015. She is currently student of MS in Information Security from National University of Sciences and technology (NUST), Islamabad. The MS degree will be complete in 2019. She is working as a SAP Trainer in SEIMENS, Islamabad. Her domain lies in networking and security. Her main areas of research are Cryptography, IOT, Machine Learning and Artificial Intelligence.