Differential Privacy Preserving in Big data Analytics for Body Area Networks

Body Area Networks (BANs), collects enormous data by wearable sensors which contain sensitive information such as physical condition, location information, and so on, which needs protection. Preservation of privacy in big data has emerged as an absolute prerequisite for exchanging private data in terms of data analysis, validation, and publishing. Previous methods and traditional methods like k-anonymity and other anonymization techniques have overlooked privacy protection issues resulting to privacy infringement. In this work, a differential privacy protection scheme for ‘big data in body area network’ is developed. Compared with previous methods, the proposed privacy protection scheme is best in terms of availability and reliability. Exploratory results demonstrate that, even when the attacker has full background knowledge, the proposed scheme can still provide enough interference to big sensitive data so as to preserve the privacy. Keywords: BAN’s, Privacy, Differential Privacy, Noisy response

Mutual Authentication in Body Area Networks (BANs) Using Multi-Biometric and Physiological Signal-Based Key Agreement

The development of wireless technology has had a major impact on the wireless body area networks (WBANs) especially in the medical field where a small wireless sensor is installed in, on, or around the patient’s body for real-time health monitoring and personalized medical treatment. However, the data is collected by the sensors and transmitted via wireless channels. This could make the channel vulnerable to being accessed and falsified by an unauthorized user and may put the lives of the patient at risk and might give a false alarm. Therefore, a secure authentication and data encryption scheme in BANs is needed in a device to establish the interaction. The asymmetric cryptosystems that function in BANs can cause a Man-in-the-Middle attack because the initial requirement in BAN requires the user to configure a master key or password. The impersonation attack may also involve BAN where other individual pretends to be the owner of the devices and lastly Eavesdropping attack where the attack eavesdrops on transmission to unlock devices. With the existing schemes, mutual authentication using the biometric features (fingerprint) and the physiological signal from the electrocardiogram database is used to make sure the authentication is more secure, reliable, and accurate. In this paper, we proposed a new multifactor authentication scheme on biometric authentication which is the retina scan. We proposed the retina scan because the retina of the human eye is unique, remains the same, and cannot be obtained from anywhere which makes it difficult to forge. We also added a new device which is a smart watch to receive a key agreement message from the fingerprint to double confirm the same identification. This is to make sure high security is obtained and offered simplicity, efficiency, and precision scheme for the authentication.

Design of low power SRAM- based ubiquitous sensor for wireless body area networks

Purpose Smart ubiquitous sensors have been deployed in wireless body area networks to improve digital health-care services. As the requirement for computing power has drastically increased in recent years, the design of low power static RAM-based ubiquitous sensors is highly required for wireless body area networks. However, SRAM cells are increasingly susceptible to soft errors due to short supply voltage. The main purpose of this paper is to design a low power SRAM- based ubiquitous sensor for healthcare applications. Design/methodology/approach In this work, bias temperature instabilities are identified as significant issues in SRAM design. A level shifter circuit is proposed to get rid of soft errors and bias temperature instability problems. Findings Bias Temperature Instabilities are focused on in recent SRAM design for minimizing degradation. When compared to the existing SRAM design, the proposed FinFET-based SRAM obtains better results in terms of latency, power and static noise margin. Body area networks in biomedical applications demand low power ubiquitous sensors to improve battery life. The proposed low power SRAM-based ubiquitous sensors are found to be suitable for portable health-care devices. Originality/value In wireless body area networks, the design of low power SRAM-based ubiquitous sensors are highly essential. This design is power efficient and it overcomes the effect of bias temperature instability.