Description:
RFID is a revolutionary remote technology which has many useful implications. Large scale implementation of RFID is seeking 100% information privacy and untraceability, for users and organizations, which is suitable for low cost RFID tag (Class1). To protect users and organization we are proposing an enhanced RFID mutual authentication scheme. In this protocol we use authentication based on shared unique parameters as a method to protect privacy. This protocol will be capable of handling forward and backward security, rouge reader better than existing protocols. In our new scheme we involved RFID reader's hardware ID in addition to other shared secret information which uses hash to protect users and industries privacy. Moreover, we used LAMED as our PRNG (Pseudorandom Number Generator) which is faster and take less computational power
Description:
The use of Multimedia Wireless Sensor Networks (MWSNs) is becoming common nowadays with a rapid growth in communication facilities. Similar to any other WSNs, these networks face various challenges while providing security, trust and privacy for user data. Provisioning of the aforementioned services become an uphill task especially while dealing with real-time streaming data. These networks operates with resource-constrained sensor nodes for days, months and even years depending on the nature of an application. The resource-constrained nature of these networks makes it difficult for the nodes to tackle real-time data in mission-critical applications such as military surveillance, forest fire monitoring, health-care and industrial automation. For a secured MWSN, the transmission and processing of streaming data needs to be explored deeply. The conventional data authentication schemes are not suitable for MWSNs due to the limitations imposed on sensor nodes in terms of battery power, computation, available bandwidth and storage. In this paper, we propose a novel quality-driven clustering-based technique for authenticating streaming data in MWSNs. Nodes with maximum energy are selected as Cluster Heads (CHs). The CHs collect data from member nodes and forward it to the Base Station (BS), thus preventing member nodes with low energy from dying soon and increasing life span of the underlying network. The proposed approach not only authenticates the streaming data but also maintains the quality of transmitted data. The proposed data authentication scheme coupled with an Error Concealment technique provides an energy-efficient and distortion-free real-time data streaming. The proposed scheme is compared with an unsupervised resources scenario. The simulation results demonstrate better network lifetime along with 21.34 dB gain in Peak Signal-to-Noise Ratio (PSNR) of received video data streams.