Group Device Pairing based Secure Sensor Association and Key Management for Body Area Networks

  1.ABSTRACT :

                              Body Area Networks (BAN) is a key enabling technology in E-healthcare such as remote health monitoring. An important security issue during bootstrap phase of the BAN is to securely associate a group of sensor nodes to a patient, and generate necessary secret keys to protect the subsequent wireless communications. Due to the  ad hoc nature of the BAN

and the extreme resource constraints of sensor devices, providing secure, fast, efficient and user-friendly secure sensor association is a challenging task. In this paper, we propose a lightweight scheme for secure sensor association and key management in BAN. A group of sensor nodes, having no prior shared secrets before they meet, establish initial trust through group device pairing (GDP), which is an authenticated group key agreement protocol where the legitimacy of each member node can be visually verified by a human. Various kinds of secret keys can be generated on demand after deployment. The GDP supports batch deployment of sensor nodes to save setup time, does not rely on any additional hardware devices, and is mostly based on symmetric key cryptography, while allowing batch node addition and revocation. We implemented GDP on a sensor network testbed and evaluated its performance. Experimental results show that that GDP indeed achieves the expected design goals.

  2. EXISTING SYSTEM :

                                      A  wireless body area networks (BAN) have emerged as an enabling technique for E-healthcare systems, which will revolutionize the way of hospitalization . A BAN is composed of small wearable or implantable sensor nodes that are placed in, on or around a patient’s body, which are capable of sensing, storing, processing and transmitting data via wireless communications. In addition, a controller (a hand-held device like PDA or smart phone) is usually associated with the same patient, which collects, processes,

and transmits the sensor data to the upper tier of the network for healthcare records. In contrast to conventional sensor networks, a BAN deals with more important medical information which has more stringent requirements for security. Especially, secure BAN bootstrapping is essential since it secures the very first step. In this  we focus on the secure sensor association problem during BAN bootstrapping (before the BAN is actually deployed).

                                                                         A group of BAN devices should be correctly and securely associated to an intended patient. In particular, the sensor nodes must authenticate to each other and form a group with the controller. Secret keys which only belong to the intended group are generated, so as to protect the subsequent communications. Since the wireless communication is imperceivable by human, during this process it is desirable to let a user physically make sure that the devices ultimately forming a group includes and only includes the intended devices that s/he wants to associate (group demonstrative identification). Since the time spent in BAN bootstrapping is a critical concern in many applications (e.g., in EMS where 5 minutes may result in a difference between life and death), the protocol must be fast while being user-friendly, i.e., involving less human interactions. Moreover, overhead is another issue since the medical sensor nodes are extremely resource-constrained.

  3. PROPOSED SYSTEM :

                                   We propose a novel protocol, group device pairing (GDP), for secure sensor association and key management in BAN. A group of nodes and a controller that may have never met before and share no pre-shared secrets, form a group securely to associate to the correct patient. For each subgroup, GDP achieves authenticated group key agreement by simultaneously and manually compare the LED blinking patterns on all nodes, which can be done within 30 seconds with enough security strength in practical applications. GDP helps the user of BAN to visually make sure that the BAN consists only of those nodes that s/he wants to associate with the patient.

                                            We propose a novel scheme for secure sensor association and key management in BAN. First, we put forward GDP that associates a group of BAN devices with a patient. GDP leverages device pairing and group key agreement in an unique way, in that only one simultaneous comparison of synchronous LED blinking sequences is required

for a batch of at most 10 nodes, which lasts less than 30 seconds. GDP is fast, efficient, user-friendly, and also error-proof. Second, GDP enables efficient key management after network deployment. Multiple types of keys can be derived on-demand based on the group key. Also, dynamic operations, such as regular key updates, batch node addition and revocation are supported naturally by GDP. Our scheme is mostly based on symmetric key cryptography (SKC), thus

having low communication and computation overhead. Third, we implement GDP on a 10 node sensor network testbed to evaluate its performance. Experimental results show that group sensor association can be done within 30 seconds with low overhead, and is intuitive-to-use.

  4.HARDWARE REQUIREMENTS:

•         System                : Pentium IV 2.4 GHz.

•         Hard Disk            : 40 GB.

•         Floppy Drive       : 1.44 MB.

•         Monitor                : 15 VGA Colour.

•         Mouse                 : Logitech.

•         Ram                     : 256 MB.

   5.SOFTWARE REQUIREMENTS:

•         Operating System       : - Windows XP Professional.

•         Front End                               : - Asp .Net 2.0.

•         Coding Language       : - Visual C# .Net.