validating the watermark. More specifically, the proposed technique visualizes the sensory data gathered from the whole network at a certain time snapshot as an image, in which every sensor node is viewed as a pixel with its sensory reading representing the pixels intensity. Since senor data is represented as an ‘‘image” digital watermarking can be applied to this image. In order to balance the energy consumption among sensor nodes, a direct spread spectrum sequence (DSSS) based watermarking technique is used. While each sensor node appends a part of the whole watermark into its sensory data, verification of watermark which requires an extensive computational resource is left to the sink. The proposed scheme adopts the existing image compression schemes as the aggregation functions to reduce network load while retaining the desired details of the data. Moreover, using a DSSS based watermarking scheme, the proposed technique is enabled to survive a certain degree of distortion and therefore naturally support data aggregation presents the comparison of secure data aggregation schemes with respect to wireless sensor networksecurity requirements. As seen from almost all secure data aggregation protocols ensure data integrity and DSP. Protocols in [16,20,17] focus solely on aggregation of encrypted data and do not provide data integrity and source authentication support. However, these protocols can be modified easily to support data integrity and source authentication. Table 1 also shows that some of the secure data aggregation protocols () do not support data confidentiality which is essential for mission critical wireless sensor network applications. Therefore, these protocols should be used only in applications in which the transmitted data is not secret. Among the protocols that provide data confidentiality, the protocols proposed in  can offer end- to-end data confidentiality.
number of networks has been proposed with onion routing technique and some networks have been implemented. Onion routing , is a technique where message are covered in multiple encryption layers, forming an encryption like onion. In this scheme delivering message to destination by a no of intermediate onion nodes or routers, each intermediate router and node is responsible to decrypt one layer, and forward the packet or message to next router or node. A common process of an onion routing scheme is classify a collection of nodes that relay users of the system traffic. Users of this scheme then randomly select a path over the onion routers network and form a circuit, a sequence of nodes which will route traffic. After formed the circuit, each nodes in the circuit shares symmetric to user, that key will be used to encrypt future onion layers. In this proposed system we present onion routing protocol and Advanced Encryption technique. In that First network is constructed with n no of nodes . After that nodes in the network can request data packet to other nodes. We can simulate nodes in the networks are moving because of the nodes mobility property. All nodes are maintained to forward data packet to other nodes. In this proposed scheme, discovering the shortest path is first process, and sends the packets to other node. When nodes come for registering into to the network, they get id and other information . In this multi hop route forwarding is used to identify shortest path detection and Advanced Encryption Standard algorithm is used to achieve encryption process. Data is encrypted using Advanced Encryption Standard (AES) technique with primary key of all intermediate nodes. The wholesome is forwarded to first node, where the first decryption will be done by that node decryption key. In this proposed system, source node transmits the encrypted data packet to intermediate.
Node compromise attack is a serious threat in success of wireless sensor networks. Many methods - have been used to detect node compromise attack. Roughly speaking, these techniques can be categorized into two classes: detection in the second stage ; and detection in third stage -. Detection in the second stage in , Song et al. make the first attempt to detect node compromise in the second stage. Their motivation is that for some applications, an adversary may not be able to precisely deploy the compromised sensors back into their original positions. Then, the detection of location change will become an indication of a potential node compromise. Detection in the third stage. In  to handle the MAC layer misbehavior, Kyasanur and Vaidya propose modifications to IEEE 802.11 MAC protocol to simplify misbehavior detection. Once the sensor nodes are compromised, they could launch falsedata injection attack. Thus several en-route filtering schemes   have been proposed to drop the falsedata en-route before they reach the sink. Nevertheless, these schemes only mitigate the threats. Thus in , ye et al. propose a probabilistic nested marking scheme to locate colluding compromised nodes in falsedata injection attacks. Recently several software-based attestation schemes   for node compromise detection in sensor networks also have been proposed. However, they are not readily applied into regular sensor networks due to several limitations . In , Yang et al. present two distributed schemes towards making software based attestation more practical. In these schemes, neighbors of a suspicious node collaborate in the attestation process to make a joint decision. Different from the above previously reported schemes, this proposed scheme attempts to detect the node compromise attack in the first stage.
Wireless sensor network is a distributed and collection of sensor nodes which senses event in an environment. The sensed events are transmitted to base station for the further processing. The unique characteristics of wireless sensor networks are self organizing and in-network and collaborative processing. Self organizing is a behavior of WSN where regardless of how many nodes disconnect, still an Ad.hoc connection is established from the remaining nodes. The another unique characteristics of WSN is in-network and collaborate processing where nodes collaborate which each other to transmit the secured data to source to destination using store and forward approach. Due to the resource constraints nature of WSN, providing energy efficient secured routing is a major concern. The main aim of energy efficient routing is to distance the optimal routing path so that energy speed on both transmission and reception of the both data packets and control packets. Apart from energy optimization providing secure routing is a major concern. The nodes in wsn are vulnerable to various security attacks   which are caused through injection of malicious data along with payload or data packets
Wireless Sensor Network (WSN) includes a number of battery powered sensor nodes, endowed with physical sensing capabili- ties, limited processing and memory, and short range radio com- munication. This sensor networks are used in numerous appli- cation domain. The sensing nodes have a sensing device that acquires data from the physical environment. It also has a pro- cessing subsystem for local data processing and storage and a wireless communication module. This is one kind of distributed wireless sensor networks not only energy but also processing constraints. In todays advanced world most of the low power hardware architecture and also most communication protocols are expressed the use of WSNs in various high data intensive applications. In wireless sensing and networking technologies, these types of progression for variant applications are obviously the key enablers for the effective integration of physical as well as cyber worlds. As an application, we can use wireless sen- sor network in the medical domain, which can develop the ar- rangements  as well as the management of healthcare services. The resource constrained devices are small enough as a wireless medical sensor, its also capable of collecting variant physiologi- cal parameters, like; Heart Rate (HR), Pulse, Oxygen Saturation (SpO2), Respiration and Blood Pressure (BP). These types of sensed data can provide a number of information which are valu- able for doctors, nurse and also for particular care givers. These help them to determine the overall medical condition of the sub- ject. Now-a-days for a long period of time, hospital monitoring is very costly. So there has a stable option, which is to keep the non-emergency subjects in the patents home and make a process to continue monitoring using variant medical sensor . There
The node joinig procedure is combination of symmetric and asymetric key combination process in following way.Here symmetric key is use as session key to encrypt the confidential message for that Advance Encryption standard (AES) algorithm is ase . AES require less execution time and low energy consumption wheres asymmetric key cryptography is use for user authentication and session key distribution process so hence Rivest, Shamir and Adleman cryptoghraphy algorithm( RSA) is use for asymmetric key cryptoghraphy .finally IP pf new node with be generated and will check for duplication.The first node in the network will be responsible for setting the global settings of the spontaneous network (SSID, session key). However, each node must configure its own data (including the first node): IP, data, port, and user data. This information will help the node to become part of the network. After this data are saving in the first node, it changes to standby mode , . The second node first configures its user data and security. Then, the greeting process starts. It authenticates with the first node. Our protocol relies on a sub layer protocol. The connection is created through a short-range link technology, to provide selection of nodes and ease of detection, and visual contact with the user of the node. Moreover, minimal involvement of the user is required to configure the device mainly to establish trust. This technology also borders the scope and the consumption of involved nodes. Each new node authenticates with any node in the network .
As a result of the low cost nature of WSNs, sensor nodes are (mostly) not tamper-resistant and can be easily compromised by an adversary. The entire information (e.g., keying material) stored on the nodes can therefore be misused by the adversary to act as authorized nodes in the network. As a result an adversary can perform insider attacks such as falsedata injection, e.g., indicating a non- existing event to cause false alarms, or Path-based Denial of Service (PDoS) attacks. In a PDoS attack, an adversary overwhelms sensor nodes by flooding a multihop end-to-end communication path with either replayed or injected false messages to waste the scarce energy resources.
Abstract - Mobile ad hoc network (MANET) is a collection of mobile nodes that communicate with each other without any fixed infrastructure or a central network authority. Dynamic source routing (DSR) is a broadly accepted network routing protocol for mobile ad hoc network (MANET).Black hole is a malicious node that always gives the false route replay(RREP) for any route request(RREQ) without having specified path to the destination node and drops all the received packets. In this paper we proposed Schema is based on Prior Receive-Reply algorithm is used to identify the malicious node in DSR protocol. Schema is divided into two phases, Detection of malicious node before route establishment and Avoid Communication with malicious nodes during data forwarding. The simulation is carried on NS-2 and the simulation results are analyzed on various network performance metrics such as packet send and received, packet dropped, and Average Network throughput, end-to-end delay and packet delivery ratio.
Using the test environment in SNACk chip, it is possible to test two encryption cores with different key lengths at different supply voltages and different operating frequencies. The same key and the plaintexts were sent to each encryption module The activity of the post signoff timing simulation for each encryption module was captured for the whole encryption period. Then, the activity data were used to do power estimation in PrimeTime with FDSOI 28-nm technology libraries provided by ST. The technology librarie were characterized for the supply voltage from 0.6 to 1.3 V for different working conditions. Figs. 10 and 11 show the leakage power and the dynamic power of different encryption modes at 10 MHz withthe supply voltage ranging from 0.6 up to 1.3 V at different corners at 125 °C. It is obvious that the worst case in terms of power consumption is the fast corner. Furthermore, it is clear that there are different leakage powers at different corners, while dynamic powers stay unchanged across different corners. The leakage powers increase significantly when we increase the supply voltage especially in the fast corner. Within the same algorithm, the leakage power has minor differences for different key sizes; however, the leakage power of AES module is fro 2.5 to 3 times the leakage power of PRESENT module.
Countermeasures: The simplest defense against HELLO flood attacks is to verify the bi directionality of a link before taking meaningful action based on a message received over that link. However, this countermeasure is less effective when an adversary has a highly sensitive receiver as well as a powerful transmitter. One possible solution to this problem is for every node to authenticate each of its neighbors with an identity verification protocolusing a trusted base station. If the protocol sends messages in both directions over the link between the nodes, HELLO floods are prevented when the adversary only has a powerful transmitter because the protocol verifies the bidirectionality of the link. Although this does not prevent a compromised node with a sensitive receiver and a powerful transmitter from authenticating itself to a large number of nodes in the network, an observant base station may be able to detect a HELLO flood is imminent. VI. S ENSOR N ETWORK S ECURITY ISSUE AT T RANSPORT
Right when the estimations are somehow supplanted or changed by an attacker, they supervise malicious data mixtures. The aggressor may utilize the implanted data to move an occasion reaction, for example, flight by temperance of flame, when occasion is not happened, or cover the event of a true blue occasion, for example, the trigger for an intrusion alert. Arranged means for taking control on the estimations are likely. A broad number of the reviews in the securing in order to compose address physical and framework layer perils the reliability of the estimations amidst their transmission. However strikes may trade off the estimations even some time starting late they are transported. For example, an aggressor may modify with a sensor in the region and stack programming that reports wrong estimations. Probability is that the attacker controls condition through using for case a lightweight to trigger a fire alarm.
Ant colony optimization routing algorithm is for wireless sensor network routing optimization . The basic idea is the basic ant colony algorithm ant is divided into two or more populations, using multiple ant colony parallel executive search task, through the interaction between different ant pheromone and the end-to-end delay, node load and access efficiency as the path heuristic value, and then periodically replace the optimal solution of pheromone updates, to ensure the diversity of solutions, robust optimization and routing implementation of cyber source. BP neural network, the transfer function of neurons is S type function, output for continuous quantity . It can be achieved from any nonlinear mapping from input to output. BP neural network is based on neural network model, the error back propagation thought, through error between the network output and the desired output, the network error guiding network layer neuron threshold correction direction, so that the network output and the expected output as close as possible, the network output error is minimized.
Secondly PANA and Open PANA both relays in external open source libraries for EAP implementation to provide multiple authentication mechanisms. In Open Source implementation while CPANA integrates EAP implementation with the PANA source code itself and only implements one EAP method (EAP-PSK), optimizing the overall processing. Third, There is interaction of PANA with an external RADIUS server based on FreeRADIUS for adding the flexibility same as of OpenPANA depleting available ports in the PAA. But this will be reduced the overall performance & produces a bottleneck. At last, the FreeRADIUS supports an experimental implementation of the EAP-PSK method that adds one unnecessary exchange before starting EAP-PSK. This exchange can be negligible in a more optimized implementation of EAP-PSK & would imply a reduction of ~2 ms in the overall authentication time. When we summarized it is as follows, the major issue of CPANA are related to the lack of implemented features, such as an AAA client in the CPANA-PAA or support for non-EAP-piggyback. PaC-initiated re-authentication, or IPv6. But on the other side PANA has opted for many features which includes an authentication flexibility, integration with existing AAA infrastructures, and multiple-user support at the cost of a more complex implementation as compared with CPANA and OpenPANA. This can proves that PANA implementation support a large set of features for testing PANA than CPANA and OpenPANA ,EAP, and RADIUS. For evaluation of PANA protocol we have used a PC Core duo 2.16 GHZ with 3 GBytes RAM used for (re) authentication.
In this project, we proposed a new security model to address three important active attacks namely cloning attack, MITM attack and Replay attack. We used the concept of zero knowledge protocol which ensures non-transmission of crucial information between the prover and verifier. The proposed model uses social finger print based on s-disjunct code together with ZKP to detect clone attacks and avoid MITM and replay attack. We analysed various attack scenarios, cryptographic strength and performance of the proposed model.
The sensor network suffers from many impactions. It suffers from low battery power, small amount of memory to store the data and computation capabilities. So selection of right cryptography technique is also very significant, that techniques which will work well with its constraints and produce desirable result. For this we have two techniques in cryptography one is symmetric key and other is asymmetric. 
wireless sensor network (WSN) are growing day by day. A WSN contains many sensor nodes of the order of hundreds or even thousands. They are tiny in size having limited energy and communication range. Besides this, they suffer from limited sensing, computational and transmission capabilities. In a wirelessnetwork information is transferred from a source (sensor nodes) to a sink (base station). The base station can be placed inside or outside the monitoring area. The sensor nodes are scattered over a huge geographical area randomly [1- 3] . The nodes in a wirelessnetwork can either communicate among themselves or to a base station. These nodes are sophisticated having intra and inter communication capabilities. In a wirelessnetwork the nodes play different roles as per the necessity of communication. A node can provide an interfacing between sources and sink thereby reducing the energy consumption by providing an energy efficient path to route the data from the source to the sink . These nodes are called gateways. Gateway nodes selection is essential to prevent the death of the nodes due to excessive energy consumption. Relay nodes (routers) are used to expand the coverage area and to provide backup routes in case of failure of nodes and data traffic.
Evaluating the Effects of Cryptography Algorithms on power consumption for wireless devices has done by D. S. Abdul. Elminaam et.al.(2009) presents a performance evaluation of selected symmetric encryption algorithms on power consumption for wireless devices. Several points can be concluded from the Experimental results. First; in the case of changing packet size with and with out transmission of datausing different architectures and different WLANs protocols, it was concluded that Blowfish has better performance than other common encryption algorithms used, followed by RC6. Second; in case of changing data type such as audio and video files, it is found the result as the same as in text and document. In the case of image instead of text, it was found that RC2, RC6 and Blowfish has disadvantage over other algorithms in terms of time consumption. He is found that 3DES still has low performance compared to algorithm DES. Third point .
In physical layer, there may be several threats to the wireless sensor network, due to the no tamper-resistant WSN nodes and the broadcasting nature of wireless transmission. Security threats to WSN are always added than traditional networks. Types of attacks in the physical layer include physical layer jamming and the subversion of a node.
Collection phase: Once a vehicle observes an event, that vehicle begins broadcasting alerts about the event and starts to collect other vehicles’ alerts pertaining to the event. Specifically, a witness vehicle broadcasts a triple ( , σ, cert), where is an event description, σ is a signature on , and cert is a public-key certificate. To reduce communication overhead in the Collection phase, a witness only keeps a synopsis, a subset of alerts providing a rough estimate of number of alerts (ñ). The witness vehicles exchange synopses with each other using the Message Exchange Protocol. The Collection phase is finished when the threshold-based validation algorithm determines that the vehicle has collected sufficient alerts to generate an event proof (a synopsis showing ñ ≥ τ ), or when the event expires. If ñ ≥ τ , the witnesses transit to the Distribution phase to spread the snopsis.
In the seventies, the United States military organization for operational requirements developed wireless packet network, after decades of development and evolution. Wireless packet networks gradually became today's wireless self-organized network. Compared with the traditional network, the wireless self-organizing network with distributed, self-organizing, rapid deployment, low cost, etc. Nowadays the technology is not just a single application in military operations, it has been widely applied in social life practice, such as: sudden disaster communications, mobile office, etc. But because wireless self-organizing network development time is shorter, the imperfection of the related technology, wireless self-organizing network is faced with a lot of technical research In this paper, the wireless self-organized network comprehensively expounded, systematically introduces its technical characteristics, the present situation of the network structure, application and related research, etc.