International Institute of Information Technology, Hyderabad

About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Authentication & Internet security. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).

Block-CLAP: Blockchain-Assisted Certificateless Key Agreement Protocol for Internet of Vehicles in Smart Transportation

Abstract: In the Internet of Vehicles (IoV), numerous potential applications have come up with the use of the Internet of Things (IoT)-empowered smart devices. In IoV, vehicles, roads, street signs and traffic lights can accordingly adjust to changing conditions in order to assist drivers, and also to improve safety, ease congestion and pollution reduction. Since various entities in an IoV environment make communications over public channels, there are potential security threats. To deal with such serious threats, we design a new blockchain-assisted certificateless key agreement protocol for IoV in smart transportation context, called Block-CLAP. In Block-CLAP, through authentication key management, traffic-centric data reach to a cluster head $(CH)$ and then to its nearby road-side unit $(RSU)$ securely using the established secret keys. A cloud server $(CS)$ then securely collects the information from its attached $RSUs$ and create the transactions. Later, the transactions are formed into blocks by the $CS$ in a Peer-to-Peer (P2P) cloud servers network, and the blocks are verified and added through voting-based consensus algorithm in the blockchain. The detailed security analysis through formal, informal and formal security verification, and comparative study show that Block-CLAP provides superior security and has low communication and computational overheads as compared with other existing competing authentication schemes in the IoV environment. Finally, the blockchain-based implementation of Block-CLAP has been performed to measure computational time needed for a varied number of transactions per block and also for a varied number of blocks mined in the blockchain.

Postural time-series analysis using Empirical Mode Decomposition and second-order difference plots

Abstract: This paper presents a new method for analysis of center of pressure (COP) signals using Empirical Mode Decomposition (EMD). The EMD decomposes a COP signal into a finite set of band-limited signals termed as intrinsic mode functions (IMFs). Thereafter, a signal processing technique used in continuous chaotic modeling is used to investigate the difference between experimental conditions on the summed IMFs. This method is used to detect the degree of variability from a second-order difference plot, which is quantified using a Central Tendency Measure (CTM). Seventeen subjects were tested under eyes open (EO) and eyes closed (EC) conditions, with different vibration frequencies applied for the EC condition in order to provide additional sensory perturbation. This study has demonstrated an effective way to differentiate vibration frequencies by combining EMD and second-order difference (SOD) plots.

Study of characteristics of aperiodicity in Noh voices.

Abstract: The feasibility of representing the excitation source characteristics in expressive voice signals by an aperiodic sequence of impulses in the time domain is examined in this paper. In particular, the aperiodic components of excitation of expressive voices, like the Noh voice, are examined in some detail. The aperiodic component is extracted from the speech signal using a modified zero-frequency filtering method, and it is represented using a sequence of impulses with amplitudes corresponding to the relative strength of excitation around each impulse. The spectral characteristics of the aperiodic sequence show subharmonics and harmonics of the fundamental frequency corresponding to pitch. The effects of aperiodicity are examined using spectrograms and saliency plots of synthetic amplitude and duration (i.e., frequency) modulation of sequences of impulses.

Development of Point of Care Testing Device for Neurovascular Coupling From Simultaneous Recording of EEG and NIRS During Anodal Transcranial Direct Current Stimulation

Abstract: This paper presents a point of care testing device for neurovascular coupling (NVC) from simultaneous recording of electroencephalogram (EEG) and near infrared spectroscopy (NIRS) during anodal transcranial direct current stimulation (tDCS). Here, anodal tDCS modulated cortical neural activity leading to hemodynamic response can be used to identify the impaired cerebral microvessels functionality. The impairments in the cerebral microvessels functionality may lead to impairments in the cerebrovascular reactivity (CVR), where severely reduced CVR predicts the chances of transient ischemic attack and ipsilateral stroke. The neural and hemodynamic responses to anodal tDCS were studied through joint imaging with EEG and NIRS, where NIRS provided optical measurement of changes in tissue oxy-( $HbO2)$ and deoxy-( $Hb$ ) hemoglobin concentration and EEG captured alterations in the underlying neuronal current generators. Then, a cross-correlation method for the assessment of NVC underlying the site of anodal tDCS is presented. The feasibility studies on healthy subjects and stroke survivors showed detectable changes in the EEG and the NIRS responses to a 0.526 A/ $\mathrm{m}^{2}$ of anodal tDCS. The NIRS system was bench tested on 15 healthy subjects that showed a statistically significant (p $HbO2$ than the nonlesioned side in response to anodal tDCS. The EEG study on healthy subjects showed a statistically significant (p $HbO2$ response in one of the stroke survivors with white matter lesions. Therefore, it was concluded that the anodal tDCS can perturb the local neural and the vascular activity (via NVC) which can be used for assessing regional NVC functionality where confirmatory clinical studies are required.

Machine Learning for Accurate Force Calculations in Molecular Dynamics Simulations

Abstract: The computationally expensive nature of ab initio molecular dynamics simulations severely limits its ability to simulate large system sizes and long time scales, both of which are necessary to imit...