Hierarchical Group Based Mutual Authentication and Key Agreement for Machine Type Communication in LTE and Future 5G Networks

In view of the exponential growth in the volume of wireless data communication among heterogeneous devices ranging from smart phones to tiny sensors across a wide range of applications, 3GPP LTE-A has standardized Machine Type Communication (MTC) which allows communication between entities without any human intervention. The future 5G cellular networks also envisage massive deployment of MTC Devices (MTCDs) which will increase the total number of connected devices hundredfold. This poses a huge challenge to the traditional cellular system processes, especially the traditional Mutual Authentication and Key Agreement (AKA) mechanism currently used in LTE systems, as the signaling load caused by the increasingly large number of devices may have an adverse effect on the regular Human to Human (H2H) traffic. A solution in the literature has been the use of group based architecture which, while addressing the authentication traffic, has their share of issues. This paper introduces Hierarchical Group based Mutual Authentication and Key Agreement (HGMAKA) protocol to address those issues and also enables the small cell heterogeneous architecture in line with 5G networks to support MTC services. The aggregate Message Authentication Code based approach has been shown to be lightweight and significantly efficient in terms of resource usage compared to the existing protocols, while being robust to authentication message failures, and scalable to heterogeneous network architectures

Behaviour of the Foreign Exchange Rates of BRICS: Is it Chaotic?

The article focuses on the behaviour of foreign exchange rates of BRICS countries in reference to US dollar with special emphasis on examining presence of nonlinear dependence and deterministic chaos. The findings did not indicate random walk behaviour in the returns for all exchange rates and performance of GARCH as well as EGARCH models are reasonably good in capturing the conditional volatility. Further evidences suggest existence of nonlinear dependence and we compute Maximal Lyapunov Exponent and Correlation Dimension test with multiple surrogate series which confirms the chaotic nature of the exchange rates for all countries under study except for South Africa. The findings support short run predictability in exchange rates while long run predictions are unlikely to be successful. The chaotic nature of the foreign exchange market calls for newer intervention mechanism by the Central Bank of the respective countries to limit the exchange rate volatility

Multidimensional Liquidity: Evidences from Indian Stock Market

Various dimensions of liquidity including breadth, depth, resiliency, tightness, immediacy are examined using BSE 500 and NIFTY 500 indices from Indian Equity market. Liquidity dynamics of the stock markets were examined using trading volume, trading probability, spread, Market Efficiency coefficient, and turnover rate as they gauge different dimensions of market liquidity. We provide evidences on the order of importance of these liquidity measures in Indian stock market using machine learning tools like Artificial Neural Network (ANN) and Random Forest (RF). Findings reveal that liquidity variables collectively explains the movements of stock markets. Both these machine learning tools performs satisfactorily in terms of mean absolute percentage error. We also evidenced lower level of liquidity in Bombay Stock Exchange (BSE) than National Stock Exchange (NSE) and findings supports the liquidity enhancement program recently initiated by BSE