Priti Kumari, PhD

Body Area Network (BAN) has emerged as most promising technology for pervasive health care applications. Since BAN facilitates communication of very sensitive health data, information leakage in such networks can put human life at risk; and hence security inside BAN is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for… Show more

Body Area Network (BAN) has emerged as most promising technology for pervasive health care applications. Since BAN facilitates communication of very sensitive health data, information leakage in such networks can put human life at risk; and hence security inside BAN is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples. Show less

Sensors of a Body Sensor Network (BSN) transmit messages over a non-secure wireless channel. Messages are encrypted using a secret key to attain privacy. In this paper, we propose Secret-key Generation Protocol (SGenP), assuming that all sensors are capable of capturing physiological signals.
SGenP evades any pre-distribution of keying materials. SGenP consists of two sub-protocols: 1. Hash Message Authentication Code Feature Exchange (HMAC-FE) protocol and 2. Secret Key Construction (SKC)… Show more

Sensors of a Body Sensor Network (BSN) transmit messages over a non-secure wireless channel. Messages are encrypted using a secret key to attain privacy. In this paper, we propose Secret-key Generation Protocol (SGenP), assuming that all sensors are capable of capturing physiological signals.
SGenP evades any pre-distribution of keying materials. SGenP consists of two sub-protocols: 1. Hash Message Authentication Code Feature Exchange (HMAC-FE) protocol and 2. Secret Key Construction (SKC) protocol. HMAC-FE facilitates a secret feature exchange using a HMAC function. The HMAC
function works as a module, therefore with different HMAC functions, different levels of security (from Cryptographic to Information theoretic) can be achieved. Once a set of common features between two sensors is decided, SKC protocol outputs a secret key. SGenP offers some essential properties like plug-n-play, replaceability, scalability, flexibility and easy refreshment of keys. SGenP is compared with OPFKA and found that energy consumption due to communications is reduced by 89:2%. Show less

The usage of implantable sensors is imperative in Body Sensor Network. The challenges associated with its security are open research problems. Implantable sensors need a set of secret keys to communicate with other sensors or entities. Secret key generation and subsequent key exchange with other sensors
are significant power consuming tasks. Therefore, we propose a method based on pre-distribution of secret keys. The two major drawbacks, higher memory consumption and difficulties in the key… Show more

The usage of implantable sensors is imperative in Body Sensor Network. The challenges associated with its security are open research problems. Implantable sensors need a set of secret keys to communicate with other sensors or entities. Secret key generation and subsequent key exchange with other sensors
are significant power consuming tasks. Therefore, we propose a method based on pre-distribution of secret keys. The two major drawbacks, higher memory consumption and difficulties in the key refreshment of existing pre-distribution methods have been overcome in this paper. The key generation process has been shifted from implantable sensor to a trusted external device. The external device is paired with the sensor through inductive coupling and is used for powering the sensor and keys transfer. A variant of Diffie-Hellman key agreement with physiological values is used to facilitate secure transfer of keys. Formal security definitions of the proposed method have been presented. Show less

Health data is one of the most sensitive data available and its misuse can very easily endanger human lives. Ergo, each system and process in Body Sensor Network (BSN) which accesses this data needs to be secured well enough. In order to achieve this high security along with low energy consumption, a key management scheme named as Double Encryption has been proposed here. The proposed method uses two keys for encryption: a novel physiological feature based key and a preshared key between the… Show more

Health data is one of the most sensitive data available and its misuse can very easily endanger human lives. Ergo, each system and process in Body Sensor Network (BSN) which accesses this data needs to be secured well enough. In order to achieve this high security along with low energy consumption, a key management scheme named as Double Encryption has been proposed here. The proposed method uses two keys for encryption: a novel physiological feature based key and a preshared key between the communicating nodes. The feature and key generation, both are more economical than the existing algorithms in terms of computation, communication, storage, security and error. The features are exchanged with the help of simple addition and subtraction, instead of heavy computations like a vault or coffer creation, commitment, encryption or decryption. The another salient feature of the proposed algorithm is that if the key negotiation fails once, the protocol does not need to be restarted. The protocol is secure in various scenarios like Brute Force Attack, RCB (Remotely Capturing Biometric data) attack, Node Capture attack and Battery Depletion Attack. Show less

This paper proposes a centralized algorithm for cluster-head-selection in a mobile wireless sensor network. Before execution of algorithm in each round, Base station runs centralized localization algorithm whereby sensors update their locations to base station and accordingly Base station performs dynamic clustering. Afterwards Base station runs CA-MWSN for cluster-head-selection. The proposed algorithm uses three fuzzy inputs Residual energy, Expected Residual Energy and Mobility to find… Show more

This paper proposes a centralized algorithm for cluster-head-selection in a mobile wireless sensor network. Before execution of algorithm in each round, Base station runs centralized localization algorithm whereby sensors update their locations to base station and accordingly Base station performs dynamic clustering. Afterwards Base station runs CA-MWSN for cluster-head-selection. The proposed algorithm uses three fuzzy inputs Residual energy, Expected Residual Energy and Mobility to find Chance of the nodes to be elected as a Cluster-head. The node with highest Chance is declared as a Cluster-head for that particular cluster. Dynamic clustering provides uniform and significant distribution of energy in a non-uniform distribution of sensors. CA-MWSN guarantees completion of the round.
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This paper illustrates the successful application of fuzzy logic in wireless sensor networks. There are different disciplines which make use of fuzzy logic such as event forecasting, redundancy reduction, querying to sensor network database, deployment, clustering, MAC protocol etc. In this survey paper, clustering techniques with fuzzy logic are discussed which associates advantages of localized control, scalability and energy conservation. Finally, other factors which affect clustering along… Show more

This paper illustrates the successful application of fuzzy logic in wireless sensor networks. There are different disciplines which make use of fuzzy logic such as event forecasting, redundancy reduction, querying to sensor network database, deployment, clustering, MAC protocol etc. In this survey paper, clustering techniques with fuzzy logic are discussed which associates advantages of localized control, scalability and energy conservation. Finally, other factors which affect clustering along with efficient cluster head selection are considered. Show less

Wireless sensor networks have made the task of surveillance and detection easy up to greater extent. And mobile wireless sensor network is an advancement of wireless sensor network in a way to fulfil requirements of current surveillance techniques more appropriately. In this survey paper, we have considered an important part of mobile wireless sensor network i.e. clustering. So far proposed and implemented algorithms for clustering in mobile wireless sensor network is discussed here with the… Show more

Wireless sensor networks have made the task of surveillance and detection easy up to greater extent. And mobile wireless sensor network is an advancement of wireless sensor network in a way to fulfil requirements of current surveillance techniques more appropriately. In this survey paper, we have considered an important part of mobile wireless sensor network i.e. clustering. So far proposed and implemented algorithms for clustering in mobile wireless sensor network is discussed here with the consideration of LEACH as a basic algorithm for clustering in wireless sensor network. Show less

In this survey paper, various challenges to wireless sensor networks are considered and Clustering as a solution to one of them has been introduced. The wireless sensor network is divided into clusters in order to reduce energy consumption as well as to increase coverage area to larger extent. The various clustering schemes with different parameters and in different environments such as static and mobile are discussed. The fuzzy approach in cluster head selection has overcome uncertainty of… Show more

In this survey paper, various challenges to wireless sensor networks are considered and Clustering as a solution to one of them has been introduced. The wireless sensor network is divided into clusters in order to reduce energy consumption as well as to increase coverage area to larger extent. The various clustering schemes with different parameters and in different environments such as static and mobile are discussed. The fuzzy approach in cluster head selection has overcome uncertainty of wireless sensor network at different levels. Show less