Imran Rashid

Privacy Preservation in e-Healthcare Environments: State of the Art and Future Directions

e-Healthcare promises to be the next big wave in healthcare. It offers all the advantages and benefits imaginable by both the patient and the user. However, current e-Healthcare systems are not yet fully developed and mature, and thus lack the degree of confidentiality, integrity, privacy, and user trust necessary to be widely implemented. Two primary aspects of any operational healthcare enterprise are the quality of healthcare services and patient trust over the healthcare enterprise. Trust is intertwined with issues like confidentiality, integrity, accountability, authenticity, identity, and data management, to name a few. Privacy remains one of the biggest obstacles to ensuring the success of e-Healthcare solutions in winning patient trust as it indirectly covers most security concerns. Addressing privacy concerns requires addressing security issues like access control, authentication, non-repudiation, and accountability, without which end-to-end privacy cannot be ensured. Achieving privacy from the point of data collection in wireless sensor networks, to incorporating the Internet of Things, to communication links, and to data storage and access, is a huge undertaking and requires extensive work. Privacy requirements are further compounded by the fact that the data handled in an enterprise are of an extremely personal and private nature, and its mismanagement, either intentionally or unintentionally, could seriously hurt both the patient and future prospects of an e-Healthcare enterprise. Research carried out in order to address privacy concerns is not homogenous in nature. It focuses on the failure of certain parts of the e-Healthcare enterprise to fully address all aspects of privacy. In the middle of this ongoing research and implementation, a gradual shift has occurred, moving e-Healthcare enterprise controls away from an organizational level toward the level of patients. This is intended to give patients more control and authority over decision making regarding their protected health information/electronic health record. A lot of works and efforts are necessary in order to better assess the feasibility of this major shift in e-Healthcare enterprises. Existing research can be naturally divided on the basis of techniques used. These include data anonymization/pseudonymization and access control mechanisms primarily for stored data privacy. This, however, results in giving a back seat to certain privacy requirements (accountability, integrity, non-repudiation, and identity management). This paper reviews research carried out in this regard and explores whether this research offers any possible solutions to either patient privacy requirements for e-Healthcare or possibilities for addressing the (technical as well as psychological) privacy concerns of the users.

Security and management framework for an organization operating in cloud environment

Cloud computing has attained tremendous popularity recently, leading to its fast and rapid deployment. However, privacy and security concerns have also increased in the same ratio. The adoption of cloud model has revealed new dimensions of attack, demanding major reconsideration and reevaluation of traditional security mechanisms. If an organization is operating in cloud environment without adopting essential security measures, it may face catastrophic consequences including loss of valuable data, financial damages, or reputation loss etc. Any organization in cloud architecture faces severe security threats and challenges for which a comprehensive security framework is needed. Certain frameworks exist in literature which focus deeply on specific cloud security issues; however, there is a dire need of comprehensive framework encompassing both security-related and management-related issues. This paper initially reviews security challenges and threats to data/applications in cloud environment. Furthermore, a comprehensive security and management framework is proposed for an organization operating in cloud environment. Proposed framework has been implemented in virtualized cloud environment to validate the efficacy of certain features of the model. The data center has been setup in virtualized environment through virtual machines on VMware ESXi-6 hypervisor layer. VMware vCloud-6 has been installed on top of it for provision of services to the users. The proposed framework is a set of guidelines that will adequately secure the organization’s data and applications. The framework incorporates a layered security architecture to achieve utmost level of security for nullifying the impact of threats.

Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance

Machine-to-machine (M2M) communication is an emerging paradigm in which trillions of intelligent devices are expected to communicate without or with small human intervention. The increasing M2M devices have severe impact on long-term evolution (LTE) data traffics. Moreover, the behavior of M2M traffic also differs from traditional mobile traffic. In future, logistics and transportations are considered to be the main M2M application areas. These applications disparately demand more efficient M2M traffic modeling to reduce end-to-end (E2E) delay between various interconnected machines. This paper investigates several traffic models and highlights the impact of M2M traffic in logistics and transportation on LTE data traffic. We evaluate the overall LTE network performance in terms of E2E delays for file transfer, voice, and video users.

A Q Learning and Fuzzy Q Learning Approach for Optimization of Interference Constellations in Femto---Macro Cellular Architecture in Downlink

The reduction in the cost and enhancement in the network coverage and capacity are the main objectives in the establishment of mobile networks. These objectives were the key force behind the idea of femtocells deployment. But, there are many technical issues for the femtocells deployment with already existing macro network. Cross-tier interference is one of the main challenge that must have to be resolved for smooth operation of macro–femto network. This paper gives self-optimizing and self-healing technique that utilizes Q-learning and fuzzy Q-learning algorithm for the objectives of enhancement in the network capacity and spectral efficiency. In our proposed scheme, each macro base station acts as an agent which interacts with its local environment (all the femtocells and mobile stations under its coverage area), gathers the information and takes the suitable actions correspondingly. For the objective of controlling cross-tier interference, macrousers are rescheduled in such an intelligent way that performance of the femtousers, located on the overlapped spectral portion, is not degraded. The simulation results confirm our proposed approach to improve the network capacity and spectral efficiency as well as sharp convergence, which designates its capability to meet the self organizing network requirements set by 3GPP.

Analysis of phase transition using deterministic matrix in Compressed Sensing

Phase transition, an important property in Compressed Sensing (CS), is the sparsity undersampling tradeoff. It serves as a performance criterion for a particular recovery algorithm. The phase transition of well-known algorithms including Basis Pursuit (BP), Orthogonal Matching Pursuit (OMP) and Approximate Message Passing (AMP) have been considered in this paper, by employing sensing matrix that is deterministic in nature. The phase boundary separating the successful and unsuccessful recovery of sparse signal is already defined in different papers by sensing matrix having random Gaussian entries. The random matrices satisfy the RIP condition for sensing matrices. While the deterministic sensing matrix used in this work satisfies the condition of coherence. The phase transition obtained using the deterministic setting shows an improvement for OMP, but is almost the same for the other two algorithms. Generally, AMP and BP are considered superior to OMP for the parameter of phase transition. While for the random case, the curve for OMP is lower than that of BP and AMP. However, the new curve obtained by deterministic sensing matrix for OMP is even higher than that of the other two algorithms. Hence, sensing matrix with lower coherence improves phase transition for OMP. Thus OMP algorithm when using deterministic matrix is superior to AMP and BP as opposed to previous research.

Analysis of block coherence based on deterministic matrices

In block compressed sensing, the retrieval of block sparse signals i.e., sparse signal having nonzero entries in the form of blocks or clusters from an under determined system of linear equations is of main interest. The successful recovery of such signals depends on the sensing matrix. Therefore, it is desired to generate a sensing matrix with optimum block coherence for guaranteed recovery. The two coherence metrics i.e., block coherence and sub-coherence are important to analyze when considering the optimally designed sensing matrix. The implication of the outcome presented lies in the fact that exploitation of block sparsity with certain conditions results in successful recovery for a higher sparsity level than treating the signal as conventionally sparse. Moreover, deterministic matrix constructions based on optimum coherence allows for an increased number of blocks as compared to random matrix constructions consequently offering better reconstruction.

Modified random pairing for throughput optimization in VMIMO Femtocell environment

Long Term Evolution-Advanced (LTE-Advanced) and other advanced technologies like IEEE802.16e and IEEE802.11g base their physical layer transmission on multiple input multiple output (MIMO). The concept of multiple antennas at both receiver and transmitter ends is attributed with advantages of spatial multiplexing and diversity, however, the Implementation on small size UEs has its own limitations. Hence a concept of virtual multiple input multiple output (VMIMO) has evolved to accommodate higher throughput for LTE-Advanced system. This paper formulates a scheme that provides maximum uplink throughput in LTE-ADVANCED environment keeping minimum level of fairness within grouped user equipment (UEs) in VMIMO. Groups/Pairs are formed from single antenna UEs to obtain multiplexing gain. Round Robin (RR), Proportional Fair (PF) and Random Pairing (RP) are Conventional pairing scheme. Fairness is prime consideration in RR and PF but RP ignores both fairness and throughput. In this paper, a Modified Random Pair (M-RP) has been introduced that maximizes throughput 2.10%, 2.07% & 2.02% in Lower group VMIMO and .96%, .96% & .95% Higher group VMIMO from RP, RR and PF respectively while keeping minimum level of fairness in the legal UEs within Femtocell scenario.

Validation of MUF and FOT parameters for plain, mountainous and sea region

In this paper, the validation of different International High Frequency (HF) prediction models for HF communication in plain, mountainous and sea regions of Pakistan are studied. An analytical study for the behavior of Ionospheric parameters, Maximum Usable Frequency (MUF) and Frequency of Optimum Traffic (FOT) has been performed between transmitter station Lahore City and many different receiver stations which are distributed randomly over Pakistani territory. The Ionospheric parameters are calculated using Ionospheric Communications Enhanced Profile Analysis & Circuit (ICEPAC) and REC 533 communication models for all seasons (Summer, Winter, Autumn and Spring) of the year 2013 of the solar cycle 24. Before this study no single model was followed properly for HF communication frequency prediction to meet the requirements of this complex geographical location containing plain, mountainous and sea regions. A comparison of practical and theoretical results shows that ICEPAC model results shows best fitting to plain, mountainous and sea regions of Pakistan as compared to REC 533.

Effect of discrete constellations on duality between the Gaussian Multiple Access and the Gaussian Broadcast Channel

The Gaussian Multiple Access Channel (G-MAC) and the Gaussian Broadcast Channel (G-BC) are known to be duals of each other for Gaussian alphabets and their capacity regions are closely related. In this paper, we investigate the duality between the G-MAC and the G-BC when the sources use discrete constellations. Considering the two-user G-MAC and the G-BC and assuming uncoded Pulse Amplitude Modulation (PAM), we show that a rate pair achieved in the G-MAC can be translated to a rate pair in the dual G-BC, such that the equal sum power constraint be satisfied. Due to the similarity of the rate expressions to Shannons capacity formula, for an appropriate choice of Signal to Noise Ratio (SNR) gap, we show that when finite constellations are used for transmission, rate regions of these two channels also have a dual relationship (the known for Gaussian alphabets). Thus the rate region of the G-BC can be characterized from the rate region of the dual G-MAC and vice versa.

A novel code attestation scheme against Sybil Attack in Wireless Sensor Networks

Wireless Sensor Networks (WSN) due to their distributed nature are vulnerable to various external and insider attacks. Classic cryptographic measures do protect against external attacks to some extent but they fail to defend against insider attacks involving node compromise. A compromised node can be used to launch various attacks of which Sybil Attack is the most prominent. In this paper we carryout a detailed review and analysis of various defenses proposed against Sybil Attack. We identify their strengths and weaknesses and also propose a novel One Way Code Attestation Protocol (OWCAP) for wireless sensors networks, which is an economical and a secure code attestation scheme that protects not only against Sybil Attack but also against majority of the insider attacks.