Wireless Sensor Networks serve as the most attractive field for many researchers. But it consists of many micro devices called sensor nodes which are powered by batteries. They are widely employed in many applications such as environmental monitoring, earthquake detection, etc where replacement of batteries is not practical. Therefore they should be managed carefully to minimize the consumption of energy. Sensor node is a device that includes three basic components:

• Sensing subsystem
• Processing subsystem
• Wireless communication system

Key

In cryptography, a key is a variable value that is applied using an algorithm to a string or block of unencrypted text to produce encrypted text, or to decrypt encrypted text. The length of the key is a factor in considering how difficult it will be to decrypt the text in a given message.

Private Key

In cryptography, a private or secret key is an encryption/decryption key known only to the party or parties that exchange secret messages. In traditional secret key cryptography, a key would be shared by the communicators so that each could encrypt and decrypt messages. The risk in this system is that if either party loses the key or it is stolen, the system is broken. A more recent alternative is to use a combination of public and private keys. In this system, a public key is used together with a private key.

Public Key

A public key may be placed in an open access directory for decryption of the digital signature of the sender; the public key of the message recipient encrypts the sender's message. Public Key Infrastructure (PKI) produces public and private keys. The open access public key may also be e-mailed to trusted contacts and users. Pretty Good Privacy (PGP) is a popular form of public key cryptography. Public PGP keys are housed in a public key server directory to allow public key sharing. PGP server directory keys may be updated but not removed.

Pottie G.J and Kaiser W.J (2000) proposed that the opportunities for Wireless Integrated Network Sensors (WINS) depend on the development of scalable, low cost, sensor network architecture. This requires that sensor information be conveyed to the user at low bit rate with low power transceivers. Continuous sensor signal processing must be provided to enable constant monitoring of events in an environment. By coming to decisions on these events, short message packets suffice. Future applications of distributed embedded processors and sensors will require massive numbers of devices. Conventional methods for sensor networking would present impractical demands on cable installation and network bandwidth. Through processing at source, the burden on communication system components, networks, and human resources are drastically reduced. The physical considerations that lead to the design of densely distributed sensor networks, reviewed the advantages of layered and heterogeneous processing/networking architectures for these applications. The close intertwining of processing of networking is a central feature of systems that connect the physical and virtual worlds. Development platforms are now available that will more easily enable a broader community to engage in fundamental research in networking and new applications, advancing us towards truly pervasive computing.

Akan O and Akyildiz I (2005) proposed that WSN is event based systems that rely on the collective effort of several micro sensor nodes. Reliable event detection at the sink is based on collective in- formation provided by source nodes and not on any individual report. Hence, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. However, the absence of reliable transport altogether can seriously impair event detection. Hence, the WSN paradigm necessitates a collective event-to-sink reliability notion rather than the traditional end-to-end notion. Reliable transport in WSNs has not been studied from this perspective before. The notion of event-to-sink reliability is necessary for reliable transport of the event features in WSNs. This is due to the fact that the sink is only interested in the collective information of a number of source nodes and not in individual sensor reports. This is also the reason why traditional end-to-end reliability notions and transport solutions are inappropriate for WSN. Based on such a collective reliability notion, a new reliable transport scheme for WSN, the Event-Sink Reliable Transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection with minimum energy expenditure and congestion resolution functionality.

Uluagac S, Lee C, Beyah R, and Copeland J (2008) proposed that Wireless Sensor Networks (WSNs) are adhoc networks comprised mainly of small sensor nodes with limited resources, and can be used to monitor areas of interest. It proposes a solution for securing heterogeneous hierarchical WSNs with an arbitrary number of levels. This solution relies exclusively on symmetric key schemes, is highly distributed, and takes into account node interaction patterns that are specific to clustered WSNs. They proposed a solution for securing heterogeneous hierarchical WSNs with arbitrary number of levels. This project provides security for network setup and reconfiguration, as well as for the normal network operation traffic. This scheme sets up pair wise keys between a cluster head and each of its children (or group of children) using lightweight group key based mechanisms whenever possible, falling back on more expensive, BS-mediated mechanisms whenever necessary.

Existing system proposed a suite of secure time synchronization protocols [2] where different hop, group synchronization are addressed with a protection against pulse delay attacks. However, these protocols require the nodes to go through the phase of key discovery with their preloaded static keys among themselves. Moreover, the protocols Communicate with many messages to synchronize the sensor Network with security, It increases the communication costs of the network and making them not applicable for military-type scenarios where a more feasible communication pattern may be preferred. However, the drawback of this work stems from its statistical nature. In the work by Sun, the authors propose a secure time synchronization [2] protocol utilizing Global Positioning System (GPS) devices starting from source nodes. The proposed work requires a shared static key between the communicating nodes and assumes that the source nodes will be equipped with GPS devices, which is more costly due to periodic communication to GPS satellites and increased radio activity increases the opportunity for malicious threats. Also, GPS may not be effective for all sensor applications (e.g., underwater medium) as explained in the previous section. Additionally similar to, the nodes exchange many messages. A secure time synchronization [4] protocol for heterogeneous sensor networks with a novel adoption of Identity-Based Cryptography (IBC) and Pairing-Based Cryptography [6] (PBC) over elliptic curves is done but the work did not present any performance evaluation to provide clock precision values. Furthermore, two pertinent studies based on associating keys with time information available in sensor nodes were presented in papers.

A time synchronization protocol for Wireless Sensor Networks (WSNs) send separate synchronization messages and uses static pair wise key-based cryptographic mechanisms to ensure that the clocks [11] of each sensor device are securely globally synchronized (i.e., every device has the same clock value). An alternative approach, Secure SOurce-BAsed loose Synchronization (SOBAS) [9] protocol is used to securely synchronize the events in the network, without the transmission of synchronization control messages.

An effective technique to securely synchronize the data with source and sink node in the network has been proposed, without transmission of synchronization control messages separately. Here proposed system focus on ensuring that each source node gets synchronized with sink nodes, and also event ordering on a sink node can be achieved and nodes along the data delivery path such that, event reports generated by the sink are ordered properly. In SOBAS [9], source and destination nodes are synchronized loosely, so that the data is delivered accurately. Initially the source node requests the time based key management module to generate the key, when there is a need to transfer data between the source and destination node. Once the source gets the key it requests the neighbour nodes to send public key [3]. The neighbour node which has the key replies that key to the source node. Then the source node encrypts the data and send to the destination throw forwarder node. Then the forward node decrypts the data and checks whether the decrypted ID and the given ID is same. If it is same, then encrypt the data and sends to the next forward node. If it is not same, then mark that data packet as malicious and filters that packet using dynamic en-route filtering mechanism. SOBAS uses the full encryption [13] and selective encryption method to encrypt the data. In full encryption technique each and every forwarder node do the encryption and decryption process. The Selective encryptions allow only a certain fraction of the nodes along the path to do the encryption operations. After that the next forwarder node continues the same process until the packet reaches to the destination node. Cryptography [8] module is used to check whether the received data is malicious or not. SOBAS provides an effective [5] dynamic en route filtering mechanism, where the malicious data is filtered from the network. With SOBAS, synchronization is achieved at the sink as quickly, as accurately, and as surreptitiously as possible. Simulation results show that SOBAS is an energy efficient scheme under normal operation and attack from malicious nodes. In addition to being suitable for the applications where the centralized decision authority acts on the information collected from the network, the SOBAS approach to synchronization with dynamic en-route filtering [15] is also well suited for both WSNs and sensor-based applications where utmost silence is necessary, as SOBAS is not chatty.

• Time-based Key Management
• Implementing Cryptography Techniques
• Performing Filtering-Forward Scheme

The Time-based Key Management (TKM) [14] module generates dynamic key by using the local time and initial vector value. When a source node has data it sends to the sink due to either an external stimulation by the sink or a selfinitiated periodic report, it uses its local clock value as the key.

Two operational modes:

• Stateless mode
• Stateful mode

The stateful mode, a receiver sensor can have a table for each sender sensor, where individual offset values for each sender is recorded. The next time the sensor receives a packet from the same sender, it will have a tick window centred on the associated offset value for this sender. This makes the effort of the receiver easier when it tries to find the correct key for the sender.

In the stateful mode, a sensor also remembers a previously seen malicious node. It doesn't maintain the tick window table.

The Cryptography module addresses the security part of SOBAS. This module obtains the dynamic key from the Timebased Key Management (TKM) module and performs the necessary security service. It is also used to verify the key from the TKM.

If the key value received from the TKM module is not correct then a new key is obtained from the TKM module. This process continues until the correct key is found or the packet is marked as malicious to be discarded in the filtering-forwarding-scheme module when all attempts to find the correct key are exhausted within the tick window.

Finally the filtering-forward scheme module performs the function as shown in Figure 1. The system eliminates the data if the node failed to produce proper key. The FFS module filters the incoming packet out of the network if it is classified as a bad packet or malicious packet by the cryptography module or otherwise forwards it to the upstream nodes. In SOBAS, this module is also responsible for the synchronization process of the forwarder node with the source node along a data delivery path toward the sink with the Full-re encryption or Selective-re encryption modes of operation. At this module, the forwarder node gets the source's local clock value from the cryptography module and updates its local clock value accordingly.

Figure 1. Cryptography and Forwarding Filtering Module

Delay refers to the average time elapsed after a packet is sent and before it is received. Figure 2 shows, the selective-stateful encryption process is well suitable for SOBAS and the delay is decreased from 3 to 12 % when compared with full-stateful encryption, full-stateless encryption and selective-stateless encryption techniques.

Transmission energy refers to, energy taken for transmitting the data from source to destination. Figure 3 shows, the selective-stateful encryption process is well suitable for SOBAS and the transmission energy has decreased from 2.5 to 5% percentage when compared with full-stateful encryption, full-stateless encryption and selective-stateless encryption techniques.

Computational energy refers to, linear dependence of rate and energy. Figure 4 shows, the selective-stateful encryption process is well suitable for SOBAS and the computational energy is decreased from 2 to 12 % when compared with full-stateful encryption, full-stateless encryption and selective-stateless encryption techniques.

Figure 2. Nodes Vs Delay

Figure 3. Nodes Vs Transmission Energy

Figure 4. Nodes Vs Computational Energy

SOBAS nodes use their local time and initial vector values as one-time dynamic key to encrypt each message. In this way, SOBAS provides an effective dynamic en-route filtering mechanism, where the malicious data is filtered from the network. Loose synchronization in SOBAS, the data are sent to destination as quickly and accurately as possible. The SOBAS decreases the number of opportunities for malicious entities to eavesdrop, intercept packets by reducing the number of messages exchanged between the nodes. Thus, energy savings from the reduced transmission is used for the local security computation. Selective encryption approach to encrypt the data in SOBAS is well suitable to reduce the energy consumption. Future work includes studying further opportunities for increasing the unused key-trial attempts at a node, and addressing insider threats.