Sensitive data identification is a vital strategy in any distributed system. However, in the case of non-appropriate utilization of the system, sensitive data security can be at risk. Therefore, sensitive data identification and its security validation are mandatory. The paper primarily focuses on novel sensitive data recognition methodologies. Further, the sensitivity score of the attributes distinguishes non-sensitive attributes, and domain expert plays an important role in this process. The designing of the security assurance Algo and their corresponding decision tables make the system more robust and reliable. The result section is validated with the help of graphical representation, which clearly makes the authenticity of the research work. In summary, the authors may say that the sensitive data identification and security assurance of the proposed system is automated and work optimally in a cloud-based system.

In the existing epoch, the cloud-IoT integrated distributive computing is earning very high attractiveness because of its immense characteristics which can be divided into two categories namely essential and common characteristics. The essential characteristics of cloud-IoT computing are demand dependent like broad network access, self-service, resource pooling, and speedy elastic nature. The common characteristics of cloud-IoT computing are homogeneity, massive scale, virtualization, resilient computing, low cost software availability, service orientation, geographic independent computation, and advanced safety availability. The cloud-IoT dependent internetworked distributive computation is internet based computation environment in which infrastructure, application software, and various similar / dissimilar platforms are accessible in the cloud and the end users (businessman, developers) have the right to use it as the client. Cloud is a step from Utility Computing and several industries / companies are frequently using cloud based systems in their day-to-day work. Therefore, safety issues and challenges of cloud computing cannot be avoided in the current era. Hence, the researchers must develop high order authentication protocols for preventing the safety threats of cloud based data communication systems..
The proposed CCMP (Counter Mode with Cipher Block Chaining Message Authentication Code Protocol) based management of cloud-IoT integrated information is a two phase authenticated encoding (AE) mechanism. The first phase is worn for executing privacy computations, and the second phase is used for computing validation and truthfulness. Here, both the cycles use same encoding technique. It is well known to us that the CCM/CCMP is an amalgamation of two forms namely AES counter form and CBC- MAC (cipher-block-chain message authentication code) protocol form. The counter form is worn to carry out encoding which guarantees data privacy whereas CBC-MAC is worn to attain data legitimacy and reliability. In this investigation work the author has investigated and critically analyzed the CCMP dependent safe Cloud-IoT integrated distributive mechanism for data / information management. The proposed approach further improves the overall security and performance of cloud-IoT integrated computing networks. Further, the author has solved the challenges of cloud-IoT computing by studying and analyzing major cloud-IoT computing safety concerns, and safety threats which are expected in future generation cloud computing systems. In this paper, the author has proposed CCMP & CBC-HMAC (Cipher-Block-Chain key Hash-Message-Authentication-Code) encoding protocol can be efficiently used for providing information safety and preventing various attacks when the data is being transferred between the Cloud and a local network. The prevention mechanism for unauthorized access of data within the cloud is also presented whose performance is highly satisfactory. A secure and flexible framework to support self-organize and self register of consumer’s information in to the cloud network is designed and tested. The testing results of proposed analysis provides us very clear evidences that the PRF of CCMP is a superior and secure in contrast to that of CBC-HMAC.

Identification of people among each other has always been a tough and challenging task for the researchers. There are many techniques which are used for identifying a person but biometric technique is the standard one which allows us for online identification of individuals on the basis of their physiological and behavioral features. The veins based systems include finger veins, face veins, palm veins, head veins, heart veins, iris, palatal veins of the rogue etc. The multi-veins based systems use the veins of different physiological traits for identifying a person.
This paper illustrates an overview of veins based personal identification systems. The performance of different single and multi-veins based identification systems are analyzed in this paper. The features like reliability, security, accuracy, robustness and long term stability along with the strengths and weaknesses of various veins based biometric approaches were taken into considerations while analyzing the results of existing research papers published so far. At last the future research directions in the field of veins based identification systems have also been outlined.

With the advent of new thumbprint identification techniques, accurate personal identification is now easy and cheaper with approximately zero false acceptance rates. This paper focuses on developing an advance feature for thumbprint based identification systems with the help of soft computing and 2D transformation which makes the technique more flexible and Fidel. The thumbprint images of individuals were scanned with the help of H3 T&A terminal for collecting self generated datasets. The thumbprints of self generated and standard datasets were trained to form a refined set which includes linear and angular displacements of thumbprint images. The new obtained features of refined datasets were stored in the database for further identification.
In the proposed technique, the minutiae coordinates and orientation angles of the thumbprint of a person to be identified are computed and merged together for comparison. The minutia coordinates and orientation angles of a person are compared with the minutiae trained set values stored in the database at different linear and angular rotations for identity verification. The proposed technique was tested on fifty persons self generated and standard datasets of FVC2002, FVC2004 and CASIA databases. In the experimentation and result analysis we observed that the proposed technique accurately identifies a person on the basis of minutiae features of a thumbprint with low FNMR (False Non-Match Rate) values.

Biometric system is an alternative way to the traditional identity verification methods. This research article provides an overview of recently / currently used single and multiple biometrics based personal identification systems which are based on human physiological (such as fingerprint, hand geometry, head recognition, iris, retina, face recognition, DNA recognition, palm prints, heartbeat, finger veins, footprints and palates) and behavioral (such as body language, facial expression, signature verification and speech recognition) characteristics. 
This paper focuses on RGB based palatal pattern analysis of persons and the proposed technique uses RGB values with silhouette computes of palatal patterns for identifying a person. We have tested our proposed technique for palatal patterns of 50 persons including males & females and it is observed that RGB values based silhouette technique are accurately identifying the persons on the basis of their palatal patterns. For each person seven palatal images were taken. Out of these seven palatal images, four images were used for training dataset and last three palatal patterns were used for identifying the persons. The proposed technique is reliable & secure and it is a foolproof method which is clearly differentiating the persons on the basis of their palatal patterns.

Face veins based personal identification is a challenging task in the field of identity verification of a person. It is because many other techniques are not identifying the uniqueness of a person in the universe. This research paper finds the uniqueness of a person on the basis of face veins based technique. In this paper five different persons face veins images have been used with different rotation angles (left/right 900 to 2700 and 3150). For each person, eight different images at different rotations were used and for each of these images the same minimum cost minutiae tree (MCMT) is obtained. Here, Prim’s or Kruskal’s algorithm is used for finding the MCMT from a minutiae graph.
The MCMT is traversed in pre-order to generate the unique string of vertices and edge lengths. We deviated the edge lengths of each MCMT by five pixels in positive and negative directions for robustness testing.
It is observed in our experiments that the traversed string which consists of vertices and edge lengths of MCMT is unique for each person and this unique sequence is correctly identifying a person with an accuracy of above 95%. Further, we have compared the performance of our proposed technique with other standard techniques and it is observed that the proposed technique is giving the promising result.

Identical twins identification is a challenging task because they share the same DNA sequence. This research paper presents minutiae coordinates and orientation angles fusion based technique for thumbprint identification of identical twins. Six different thumbprint images of identical twins were taken at a fixed time interval using H3 T&A terminal. The minutiae coordinates and orientation angles of these thumbprints were fused to form a union set. The union set values were stored in the smartcard memory for further identification.
The minutiae coordinates and orientation angles of a thumbprint of the person to be identified are computed and fused together for online identification. The fused minutiae are compared with the minutiae union set values stored in the smartcard memory for identity verification. The proposed method was tested on a self generated identical twin dataset and 50 identical twins of standard FVC04 and FVC06 datasets. We observed in experiments that the proposed method is accurately differentiating the identical twins of self generated and FVC datasets.

The twins are classified into two categories namely fraternal and identical twins. Fraternal twins differ in face structures and DNA sequences but, identical twins have the same face structure and share same DNA sequence. Therefore, it is difficult to identify identical twins on the basis of their faces and DNA sequences. In this research paper, we have introduced a new approach for identifying identical twins on the basis of minutiae coordinates, orientation angles, and minutiae distances of their thumbprint images. 
We tested the proposed method on thumbprint images of an identical twin pair generated by using Incept H3 T&A Terminal and fifty pairs of identical twins of FVC04, and FVC06 datasets. We have found that the proposed approach is superior, and robust in comparison to existing techniques in terms of accuracy, efficiency, and storage space.

Biometric systems are alternates to the traditional identification systems. This paper provides an overview of single feature and multiple features based biometric systems, including the performance of physiological characteristics (such as fingerprint, hand geometry, head recognition, iris, retina, face recognition, DNA recognition, palm prints, heartbeat, finger veins, palates etc) and behavioral characteristics (such as body language, facial expression, signature verification, speech recognition, Gait Signature etc.).
The fingerprints, iris image, and DNA features based multimodal systems and their performances are analyzed in terms of security, reliability, accuracy, and long-term stability. The strengths and weaknesses of various multiple features based biometric approaches published so far are analyzed. The directions of future research work for robust personal identification is outlined.