Introduction Wireless sensor networks have become an increasingly viable and effective form of

1. Abstract: Wireless sensor networks is growing rapidly over the few decades. Due to its flexibility, wireless sensor networks has been in practice in many areas. Among various wireless networks, Mobile Ad hoc networks has been one of the unique network. Unlike other network architectures, MANETs have no central architecture; every node is free to work both as a transmitter and receiver. Every single node can communicate freely with every other node which is in their communication range. Otherwise, it depends on neighboring nodes to relay messages. Due to this nature, MANETs are used in many missionary applications like health care, military use and emergency recovery. However the wide distribution of MANETs makes it vulnerable to malicious attacks. Hence it is necessary to design a secure system for MANETs. In this paper we implement a secure system named Enhanced Adaptive Acknowledgement especially for MANETs. To ensure higher security and reduce the network overhead, we use a different approach called hybrid cryptography in our proposed scheme. Enhanced Adaptive Acknowledgment detects higher malicious attackers without greatly disturbing the network performances. We compare the differences within the Enhanced Adaptive Acknowledgment before and after introducing the Hybrid cryptography approach

Jing, Q., Vasilakos, A., Wan, J., Lu, J., Qiu, D.: Security of the internet of things: perspectives and challenges. Wirel. Netw.20(8), 2481–2501 (2014). doi:10.1007/s11276-014-0761-7

Abstract -- Internet of Things is rapidly gaining popularity in the recent days. The availability of different variety of sensors and wireless technologies is responsible for the existence of the Internet of Things. The Internet of things finds a large number of applications in numerous fields such as Energy sector, Healthcare, Transportation, Business field and Agriculture. This paper mainly concentrates on the challenges and security issues of the Internet of things. In addition to that the paper provides solutions to these issues with the help of a construction of secure IoT

The Internet of Things is a is a term used to describe the interconnectivity of many devices which are able to dynamically interact with one another, and through the use of sensors, are able to achieve user programmed goals autonomously or remotely. This interconnectivity is a relatively recent development that is expanding rapidly as it is predicted to be the largest device market in the world, by 2019, doubling the smartphone market (Greenough, 2014). Major developments in the internet of things can be seen presently in smart medical technologies, smart home systems and transport system advancements; all of which are a result of robotic systems and sensors. The possibilities that arise from the integration of wireless connectivity between devices are extensive, however the danger associated with reliance on these products must assess how easily they can be hacked or used maliciously; as an organisation’s security and safety could rely on the IoT system

Abstract: In Cyber-Physical Networked Systems (CPNS), the antagonist can inject false measurements into the controller through compromised sensor nodes, which not only threaten the security of the system, but also consume network resources. To deal with this issue, a number of en-route filtering schemes have been designed for wireless sensor networks. However, these schemes either lack resilience to the number of compromised nodes or depend on the statically configured routes and node localization, which are not suitable for CPNS. In this research, we propose a system, which can filter false inoculated data effectively and achieve a high resilience to the number of compromised nodes without relying on static routes and node localization. This adopts polynomials instead of Message Authentication Codes (MACs) for endorsing measurement reports to achieve resilience to attacks. Each node stores two types of polynomials: authentication polynomial and check polynomial, derived from the primitive polynomial, and used for recommending and verifying the measurement reports. Through extensive theoretical analysis and experiments, our data shows that our system will achieves better filtering capacity and resilience to the large number of compromised nodes in appraisal to the existing schemes. The Polynomial based Compromise Resilient En-route Scheme against False Data Attacks Networked Systems done by using OM Net Simulator.

A wireless sensor network (WSN) consists of spatially distributed autonomous sensors. Those are accustomed monitor physical or maybe environmental conditions. The Conditions are temperature, sound, pressure, etc. They to boot hand in glove pass their information through the network to a main location. The modern networks are bidirectional, that to boot sanctioning management of sensory activities. The planning and development of wireless device networks were motivated by military applications like parcel investigation. Now, these networks are used in many industries and consumer applications, like method observance and management, machine health observance, and lots of lots of. The WSN is made of "nodes" - from many of too many voluminous or even thousands, wherever every node is connected to at least one (or usually several) sensors. Every such device network node has typically many parts: a radio transceiver with an enclosed associate degree antenna or association to Associate in Nursing external antenna, a micro-controller, associated qualification electronic circuit for interfacing with the sensors associate degreed an energy supply, usually device or qualification embedded form of energy gathering. Vampire attack is printed as a result of the composition and transmission of message that causes many energy to be consumed by the network than if an honest node(unaffected node) transmitted a message of identical size to identical

Backward secrecy: a joining sensor ought not have the capacity to peruse any already transmitted message. The various threats and attacks in WSN can be classified into [4] following three categories as shown in figure-5.

Machine learning inspires many practical solutions that maximize many resource utilization and prolong the lifespan of a network. As wireless sensors network (WSNs) monitor dynamic environment that rapidly changes over time such behavior is either caused by the external factor or by initiated by the system designers. A comparative guide is provided to aid WSN designers to develop suitable machine learning solutions for appropriate application challenges. The security properties of sensors must be known before deploying the intelligent systems on critical infrastructure. This paper provides some steps for generating a comprehensive security model for sensors network as sensors network is not a traditional computing device hence existing security models are not applicable.

Keywords— ID-based digital signature, secure data transmission protocol, Cluster-based WSNs, Fuzzy Approach, Minimum Energy Consumption

A wireless sensor network (WSN) is a collection of large number of sensor nodes and at least one base station. The sensor node is an autonomous small device that consists of mainly four units that are sensing, information gathering, processing and communication. In wireless sensor network there of many issues that are much affects in communication, processing and in deployments. The main issue is its coverage and connectivity problem. Most of the times communications does not prohibited properly amongst sensors and base station due lacking of ranges problem. Full coverage and connectivity means that every location in the field is covered by at least one node and

computation and communication capabilities. The basic components [1] of a node are a sensor unit, an

Abstract-Key management is one of the most important issues of any secure communication with the increasing demand for the security in wireless sensor networks (WSNs) it is important to introduce the secure and reliable key management in the WSNs.Data confidentiality and authenticity are critical in WSNs. Key management objective is to secure and keep up secure connections between sensor nodes at network formation and running stages.

To accomplish availability and reliability network routing protocols should be prevailing compared to jamming attacks. The trustworthiness of distributing data packets from end to end using multi-hop intermediary nodes is a noteworthy problem in the mobile Adhoc network. Due to the intrinsically self-motivated nature of

The remote sensor system is framed by vast number of sensor hubs. Sensor hubs may be homogeneous or heterogeneous. These systems are much conveyed and comprise of numerous number of less cost, less power, less memory and self-arranging sensor hubs. The sensor hubs have the capacity of detecting the temperature, weight, vibration, movement, mugginess, and sound as in and so on. Because of a requirement for heartiness of checking, remote sensor systems (WSN) are normally excess. Information from various sensors is totaled at an aggregator hub which then advances to the base station just the total qualities. Existing framework just concentrate on recognition of Attack in the system. This paper locations investigation of Attack Prevention furthermore gives a thought to how to conquer the issues.

Abstract—Mobile Ad-hoc Network (MANET) is a kind of wireless network. A Wireless ad-hoc network is a temporary network with no network infrastructure. The nodes communicate with each other, they co-operate by forwarding data packets to other nodes in the network. Thus the nodes find a path to the destination node using routing protocols. Due to the security vulnerabilities of the routing protocols, wireless ad-hoc networks are unprotected to attacks of the malicious nodes. One of these attacks is the Sinkhole Attack. Sinkhole attack is a kind of routing attack in MANET. A sinkhole node tries to attract all the network packets to it-self from all neighboring nodes. This paper focuses on to detect and prevent sinkhole node. By using a hybrid detection technique which combines the advantages of both reactive and proactive routing Protocol to detect the black hole