IEEE Transactions on Pattern Analysis and Machine Intelligence

A cryptographic paradigm to detect and mitigate blackhole attack in VANET environments

Security is a key factor in today’s fast communicating world. Many cryptographic algorithms are tested and put into use efficiently. Random numbers are used in diverse forms like nonces, secret key, initialization vector, etc. They find place in encryption, digital signature, hashing algorithms. A deterministic algorithms takes an intial seed value as input and produces pseudo random numbers with falsely induced randomness. This research work extensively surveys large set of state-of-the-art PRNGs and categorizes them based on methodology used to produce them. We compared their statistical results obtained from various statistical test tools like NIST SP 800-22, TestU01. Finally, security analyses of various PRNGs were done quantitatively for their key space, key sensitivity, entropy, speed of bit generation, linear complexity. At last, we concluded the results with some future directions for researchers to carry out their research in improving the PRNGs.

https://iopscience.iop.org/article/10.1088/1757-899X/1055/1/012076/pdf

Investigation of Strength and Security of Pseudo Random Number Generators

Optimal emplacement of sensors by orbit-electron theory in wireless sensor networks

The urge to transmit especially biomedical data rapidly is essential to save human life. Every user demands for high speed communication with no delay. But the network suffers from huge delay which degrades the performance of the network and it also dissatisfies the user expectation. To meet the user needs, the proposed work mainly focuses on increasing the speed and minimizing the delay in communication using Internet applied in Things (IoT) and Wireless Multimedia Sensor Networks. It can be achieved by avoiding over allocation of resources in the network i.e., resource level balancing and planning the transmission. These two have greater impact in upgrading the performance of network. This paper introduces a unique methodology for Wireless Multimedia Sensor Networks and end-device assisted system. The transmission time can reduced by using the concept of probability estimation for crashing the interpretative path. It extends the battery level of the motes by enhancing the pace and minimizing the energy level during transmission process. The Crashing Interpretative path protocol is simulated against other literature method. The simulation results shows that the CCP provides better efficiency in terms of transmission time, the lifetime of sensors for biomedical data transmission. This methodology is greatly helpful to save precious human life.

Optimizing Wireless Multimedia Sensor Networks Path Selection using Resource Levelling Technique in Transmitting Endoscopy Biomedical data

Cloud based computing is a skill which provide communications for large scale storage of data, along with its refine and assigning. The security and retreat become main concern for uploading sensitive data without any information leak. This can be achieved by the cloud servers by integrating the encryption techniques into it, which becomes a major objection to guide the efficient keyword based questions and the encrypted data of the matching results. The searching can be an interrogation technique which is either based on a single keyword or multi-keyword as input. In this paper, a fresh algorithm known as Multi-Keyword Interrogation Scheme (MKIS) algorithm is recommended. It lessens the maintenance overhead to a greater scope when the keyword dictionary expansion occurs dynamically. The experimental results show that MKIS presents excellent performance when compared with the existing schemes. The proposed technique is presented in 2 aspects: many-keyword graded the look to attain exact look for output and meaning-based explore to maintain synonym questions. Search Terms— Cloud based computing, Multi-keyword interrogation, Data encryption, Security preserving, semantic grilling.

Efficient Semantic Interrogation Scheme over Cryptographic Data in Cloud

The field of data analytics dealt with various methods to analyze the available data and help us to drawn into a point of conclusion about that information. Machine will learn the behavior based on the algorithms applied on those data and provide an appropriate conclusion. When these kinds of data analytic metrics applied to medical diagnosis various symptoms obtained from the patients and then the disease could be detected effectively. When certain optimization methods are applied on the data, the overall efficiency of the system will be improved considerably. To meet the challenges in diagnosing breast cancer based on clinical record sources, different symptoms in descriptions, clinical symptoms, a novel method, which consists of choosing the suitable features, multi-class functions, and multi-label parameters, has been proposed. The proposed work will be implemented as two steps such as discriminative symptoms selection and multi-syndrome learning. Public Breast Cancer Wisconsin (Diagnostic) Data Set has been taken for implementation. The breast cancer data set utilized for this work comprises 699 tumour samples. In that 458(65.5 %) samples belong to Benevolent (non-cancer) tumours and 241(34.5%) belongs to malevolent(cancer) tumours. The overall verisimilitude is 95.23% which will be improved to a greater extent when compared to the existing schemes.

A Multi-syndrome Pathology for Breast Cancer through Intelligent Learning

In future, the wireless networks communication are expected to provide increased speed and minimized delay. Due to tremendous increase in mobile users, we are in need to satisfy their demands. To improve the performance of wireless sensor networks resource leveling and scheduling the transmission plays a vital role in terms of transmission speed and delay. In this paper, a novel methodology is proposed for distant transmissions like wireless relay networks and device-to-device assisted system. We focus on the resource leveling and transmission scheduling issues to reduce the transmission time based on the stochastic probability process to crash the critical path. This method extends the lifetime of the sensors, by increasing the transmission speed and energy level of transmission. The proposed protocol CCP (Crashing Critical Path) proves its efficiency with other literature methods by extensive simulations regarding transmission time, delay factors and the lifetime of sensors.

Reconstruction of Path using Resource Leveling Technique in Wireless Sensor Networks

Achieving efficient security solutions for wireless sensor networks (WSN) is a daring challenge due to vulnerable nature of wireless medium. Routing is a major threat to security. An adversary can inject bogus routing to en-route nodes causing false decision and drain the sensors energy in the network system. To identify and prune the adversaries, pruning route modifiers (PRM) algorithm based on the collaborative authentication system has been proposed. The algorithm considers the random deployment of sensor nodes. Based on the collaborative authentication scheme, the PRM algorithm can save energy by pruning the malicious nodes at early stage. The simulation results and theoretical analysis reveals that PRM algorithm is effective in terms of efficient and secure routing. This algorithm reduces the consumption of energy by pruning and establishes the shortest path that leads to efficient network and enables security.

C. N. Vanitha

Papers

Efficient Semantic Interrogation Scheme over Cryptographic Data in Cloud

Optimizing Wireless Multimedia Sensor Networks Path Selection using Resource Levelling Technique in Transmitting Endoscopy Biomedical data

A Multi-syndrome Pathology for Breast Cancer through Intelligent Learning

Reconstruction of Path using Resource Leveling Technique in Wireless Sensor Networks

Pruning Route Modifiers in Wireless Sensor Networks