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Digital communication developed into an imperative element of infrastructure now-a-days. Many applications that operate infrastructure systems are internet-centered. Because of the nontrivial risks of information/data leakage, communication in the systems ought to be secured. Many techniques like cryptography are being employed on a large scale to furtively transmit information. But in the data transmission procedure, attaining the high data security along with high system efficiency is a difficult task. To trounce these difficulties, an efficient data transmission scheme utilizing improved advanced encryption standard with Butterfly Effect (IAES-BE) is proposed. The IAES-BE does the encryption procedure to thwart the data as of the attackers. The adaptive flower pollination algorithm (A-FPA) is employed for the key generation that augments the key’s complexity. After that, the generated key is implemented to the IAES-BE for encrypting the input plain-text as ciphertext. Next, the ciphertext is decrypted through revising the IAES-BE. Thereby, the original data will be attained and safely transmitted to the receiver. Centered on the investigational outcomes, the proposed work offered superior performance to the remaining data transmission methods.

Big data require cloud that provides dynamically expanding data storage accessed through the Internet. The outsourcing data in the cloud for storing makes the user data management easier and reduces the cost of maintaining data. Still organizations are not confident to store their data in the cloud, because of security and privacy concerns. However, existing encryption methods are able to protect data confidentiality, but it has some drawbacks of access patterns can also leak sensitive information. The proposed system uses an Elliptic curve with Diffie–Hellman (ECDH) algorithm for encryption and decryption of data to improve the data security in the cloud. This algorithm reduced the computational complexity and encrypted data efficiently. In experimental analysis, the performance of proposed ECDH is calculated using evaluation parameters such as encryption time, decryption time, computation overhead and key generation time. The proposed ECDH algorithm has approximately 70% better performance in terms of encryption time than existing methods such as RSA, MRSA and MRSAC.

Enabling a security and privacy preservation for the cloud data is one of the demanding and crucial tasks in recent days. Because, the privacy of the sensitive data should be safeguard from the unauthorized access for improving its security. So, various key generation, encryption and decryption mechanisms are developed in the traditional works for privacy preservation in cloud. Still, it remains with the issues such as increased computational complexity, time consumption, and reduced security. Also, the traditional works use the symmetric key cryptography based. Thus, this paper aims to develop a new privacy preservation mechanism by implementing a fully homomorphic–elliptic curve cryptography (FH-ECC) algorithm. The data owner encrypts the original data by converting it into the cipher format with the use of ECC algorithm, and applies the FH operations on the encrypted data before storing it on the cloud. When the user gives the data request to the cloud, the Cloud Service Provider verifies the access control policy of the user for enabling the restricted access on the data. If the access policy is verified, the encrypted data is provided to the user, from that the cipher text is extracted. Then, the ECC decryption and FH operations are applied to generate the original text. Based on the several analysis, the research work is evaluated with the help of different performance measures such as execution time, encryption time, and decryption time. In addition the effectiveness of the novel FHE technique is justified by the comparative analysis made with the traditional techniques.

Recently, most physical-layer based security strategies for Internet of thing tackle the two fundamental issues—authentication and communication key generation. However, the cost of such schemes is often high because of advanced hardware for wireless physical-layer characteristic extraction. In this paper, a lightweight authenticated secret key extraction is proposed based on the frequency-selectivity of multipath fading channels. To perform location-based device authentication and fast secret key extraction, we exploit the received signal strength of multi freqencies. The performance of our proposed method is evaluated with CC1101 IoT nodes, which verifies the feasibility of security strategy on ordinary low cost devices and in static environment.

In cloud storage, without any complexity, the nearby information stockpiling and support, the clients can indirectly keep up their information and appreciate the on-request superb applications and administrations from a shared pool of configurable computing resources. Nevertheless, the data integrity protection in cloud computing becomes a tedious task, because the client doesn’t have physical possession of the outsourced data, especially for the users with the restricted computing resources. The essential component of the cloud services is that, the clients’ information will be prepared remotely in obscure machines, where the clients have no rights on it. In order to rectify this issue, a novel highly centralized cloud information accountability with bat key generation algorithm (CCIA-BKGA) framework is suggested to maintain the concrete usage of the users’ data in the cloud. It will encircle the logging mechanism together with users’ data and policies. Before initiating the imploding processing the cloud server, first it required to convert the general information & sensitive information into an extensible markup language file format and get saved inside file. After that, Java ARchive (JAR) label setting has to be done which will be completed at the side of the data owner, then the label attributes will work according to the following functionality such as signature key value, and unique identifier. Use the JAR programmable has the capacity for both to produce a dynamic and traveling object, and to guarantee that any entrance to clients’ information will trigger verification and robotized logging facilities for local in the JARs. CCIA-BKGA structure is platform-independent and profoundly decentralized, it doesn’t request any obsessive validation or capacity framework set up and furthermore it gives the broad exploratory examinations which clarify the proficiency and adequacy of the proposed CCIA-BKGA system and existing methodologies.

Security is a major concern in mobile ad hoc network (MANET) that ensure packet authentication and integrity. A data transmitted from source to destination node has to be protected from the active and passive attacks. Certificate based secure routing scheme are developed precisely to ensure authentication with certificate mechanism. However, this paper uses fuzzy enhanced secure multicast routing (FSMR) scheme ensure better security in network and data. To estimate the presence of misbehaving nodes, FSMR is established based on normal and abnormal behaviors from the statistical data. Certificateless routing is used in the proposed system and it authenticates the data from the concept of key generation, signcryption and unsigncryption. Packets are routed and validated without the knowledge of certificate routing. The evaluation on proposed system proves that the proposed system has better data packet authentication with lesser energy consumption. Further, the proposed system attains better performance in terms of authenticity, data integrity, network lifetime, average delay and maximum throughput.

Advances made in the wearable and biosensor has attracted the applicability and usability of the healthcare applications. The biosensors collect the human physiological data from a remote area using wireless communication medium. Different form of security implications have to be exhibited in wireless body area networks (WBAN). This paper researches on enhancing the network layer and application layer of the WBAN in healthcare environment. The objective of the each phase is to enhance the data accuracy of the collected data with minimized delay. In the first phase, we have constructed attack model for Sybil, sinkhole and wormhole attacks and detected those attacks under different constraints. Secondly, an efficient packet transmission model which helps to transmit the sensed data based on their emergency using weighted product model. After devising network layer, a lightweight security scheme, an improved elliptic curve cryptography (ECC) that permits the data access for the authorized users. Experimental analysis is carried out for each phase under pre-defined simulation parameters which explores better results. The framed attack model detects the three eminent attacks in terms of false positive rate and false negative rate which helps the data controller for message transmission process. Likewise, we have also achieved 97% packet delivery ratio with 0.8 ms packet dropping ratio for better packet transmission model than the existing TOPSIS model. Time taken for key generation and secret key exchange using our proposed ECC achieved 2.4 and 0.96 ms. The overall system proves that our research model achieves scalable and fairness medical sensor networks system.

Wireless body area networks (WBANs) based ubiquitous and fully automated healthcare systems provide a platform to share medical information. Energy efficiency and communication security will increase the confidence of the users in adopting such remote healthcare systems. Key agreement and authentication schemes play an important role in the security of remote healthcare systems. The nodes in a WBAN exchange information in order to complete the key agreement and authentication process. In the literature, numerous schemes have used heavy mathematical calculations or overloaded with excessive information exchange. This paper presents a bloom filter-based key agreement scheme using k-mean clustering for WBANs. The key agreement and authentication is performed in clustered environment using k-mean clustering. This makes the scheme more robust and energy efficient. The keys are generated from the EKG values of the human body. The proposed mechanism is energy efficient and secure, due to its more efficient key generation and less memory utilizations for remote healthcare systems. Moreover, the proposed scheme is analyzed and compared with a state-of-the-art scheme in terms of energy consumption, memory utilizations, processing complexity, and false positive rate (FPR). The results show that the proposed scheme outperform significantly the other scheme by consuming less energy and efficient memory utilization, while achieving a very low FPR and linear running complexity.

As the applications of mobile and ubiquitous technologies have become more extensive, the communication security issues of those applications are emerging as the most important concern. Therefore, studies are active in relation with various techniques and system applications for individual security elements. In this paper, we proposed a new technique which uses the voice features in order to generate mobile one time passwords (OTPs) and generated safe and variable and safe passwords for one time use, using voice information of biometrics, which is used for powerful personal authentication optionally. Also, we performed the availability analysis on homomorphic variability of voice feature points using dendrogram and distribution of 15 users' voice skip sampling of feature points for the proposed password generation method. And we have described the application cases of the proposed mobile-OTP using skip sampling of voice signal.