Biblio
In the Internet of Things (IoT), it is feasible to interconnect networks of different devices and all these different devices, such as smartphones, sensor devices, and vehicles, are controlled according to a particular user. These different devices are delivered and accept the information on the network. This thing is to motivate us to do work on IoT and the devices used are sensor nodes. The validation of data delivery completely depends on the checks of count data forwarding in each node. In this research, we propose the Link Hop Value-based Intrusion Detection System (L-IDS) against the blackhole attack in the IoT with the assist of WSN. The sensor nodes are connected to other nodes through the wireless link and exchange data routing, as well as data packets. The LHV value is identified as the attacker's presence by integrating the data delivery in each hop. The LHV is always equivalent to the Actual Value (AV). The RPL routing protocol is used IPv6 to address the concept of routing. The Routing procedure is interrupted by an attacker by creating routing loops. The performance of the proposed L-IDS is compared to the RPL routing security scheme based on existing trust. The proposed L-IDS procedure is validating the presence of the attacker at every source to destination data delivery. and also disables the presence of the attacker in the network. Network performance provides better results in the existence of a security scheme and also fully represents the inoperative presence of black hole attackers in the network. Performance metrics show better results in the presence of expected IDS and improve network reliability.
Wireless Sensor Network (WSN) is often to consist of adhoc devices that have low power, limited memory and computational power. WSN is deployed in hostile environment, due to which attacker can inject false data easily. Due to distributed nature of WSN, adversary can easily inject the bogus data into the network because sensor nodes don't ensure data integrity and not have strong authentication mechanism. This paper reviews and analyze the performance of some of the existing false data filtering schemes and propose new scheme to identify the false data injected by adversary or compromised node. Proposed schemes shown better and efficiently filtrate the false data in comparison with existing schemes.
Software-defined wireless sensor cognitive radio network is one of the emerging technologies which is simple, agile, and flexible. The sensor network comprises of a sink node with high processing power. The sensed data is transferred to the sink node in a hop-by-hop basis by sensor nodes. The network is programmable, automated, agile, and flexible. The sensor nodes are equipped with cognitive radios, which sense available spectrum bands and transmit sensed data on available bands, which improves spectrum utilization. Unfortunately, the Software-defined wireless sensor cognitive radio network is prone to security issues. The sinkhole attack is the most common attack which can also be used to launch other attacks. We propose and evaluate the performance of Hop Count-Based Sinkhole Attack detection Algorithm (HCOBASAA) using probability of detection, probability of false negative, and probability of false positive as the performance metrics. On average HCOBASAA managed to yield 100%, 75%, and 70% probability of detection.
This paper presents CapeVM, a sensor node virtual machine aimed at delivering both high performance and a sandboxed execution environment that ensures malicious code cannot corrupt the VM's internal state or perform actions not allowed by the VM. CapeVM uses Ahead-of-Time compilation and introduces a range of optimisations to eliminate most of the overhead present in previous work on sensor node AOT compilers. A sandboxed execution environment is guaranteed by a set of checks. The structured nature of the VM's instruction set allows the VM to perform most checks at load time, reducing the need for expensive run-time checks compared to native code approaches. While some overhead from using a VM and adding sandbox checks cannot be avoided, CapeVM's optimisations reduce this overhead dramatically. We evaluate CapeVM using a set of IoT applications and show this results in a performance just 2.1x slower than unsandboxed native code. Thus, CapeVM combines the desirable properties ofexisting work on both sandboxed execution and virtual machines for sensor nodes, with significantly improved performance.
A significant segment of the Internet of Things (IoT) is the resource constrained Low Power and Lossy Networks (LLNs). The communication protocol used in LLNs is 6LOWPAN (IPv6 over Low-power Wireless Personal Area Network) which makes use of RPL (IPv6 Routing Protocol over Low power and Lossy network) as its routing protocol. In recent times, several security breaches in IoT networks occurred by targeting routers to instigate various DDoS (Distributed Denial of Service) attacks. Hence, routing security has become an important problem in securing the IoT environment. Though RPL meets all the routing requirements of LLNs, it is important to perform a holistic security assessment of RPL as it is susceptible to many security attacks. An important attribute of RPL is its rank property. The rank property defines the placement of sensor nodes in the RPL DODAG (Destination Oriented Directed Acyclic Graphs) based on an Objective Function. Examples of Objective Functions include Expected Transmission Count, Packet Delivery Rate etc. Rank property assists in routing path optimization, reducing control overhead and maintaining a loop free topology through rank based data path validation. In this paper, we investigate the vulnerabilities of the rank property of RPL by constructing an Attack Graph. For the construction of the Attack Graph we analyzed all the possible threats associated with rank property. Through our investigation we found that violation of protocols related to rank property results in several RPL attacks causing topological sub-optimization, topological isolation, resource consumption and traffic disruption. Routing security essentially comprises mechanisms to ensure correct implementation of the routing protocol. In this paper, we also present some observations which can be used to devise mechanisms to prevent the exploitation of the vulnerabilities of the rank property.
In typical Wireless Sensor Network (WSN) applications, the sensor nodes deployed are constrained both in computational and energy resources. For this reason, simple communication protocols are usually employed along with shortrange multi-hop topologies. In this paper, we challenge this notion and propose a structure that employs more robust (and naturally more complex) forward-error correction schemes in multi-hop extended star topologies. We demonstrate using simulation and real-world data based on popular WSN platforms that this approach can actually reduce the overall energy consumption of the nodes by significant margins (from 40 to 70%) compared to traditional WSN schemes that do not support sophisticated communication mechanisms and it is feasible to implement it economically without relying on expensive hardware.
Vehicular ad hoc network is based on MANET all the vehicle to vehicle and vehicle roadside are connected to the wireless sensor network. In this paper mainly discuss on the security in the VANET in the lightweight cloud environment. Moving vehicle on the roadside connected through the sensor nodes and to provide communication between the vehicles and directly connected to the centralized environment. We propose a new approach to share the information in the VANET networks in secure manner through cloud.
Most of Wireless Sensor Networks (WSNs) are usually deployed in hostile environments where the communications conditions are not stable and not reliable. Hence, there is a need to design an effective distributed schemes to enable the sensors cooperating in order to recover the sensed data. In this paper, we establish a novel cooperative data exchange (CDE) scheme using instantly decodable network coding (IDNC) across the sensor nodes. We model the problem using the cooperative game theory in partition form. We develop also a distributed merge-and-split algorithm in order to form dynamically coalitions that maximize their utilities in terms of both energy consumption and IDNC delay experienced by all sensors. Indeed, the proposed algorithm enables these sensors to self-organize into stable clustered network structure where all sensors do not have incentives to change the cluster he is part of. Simulation results show that our cooperative scheme allows nodes not only to reduce the energy consumption, but also the IDNC completion time.
We propose a real time authentication scheme for smart grids which improves upon existing schemes. Our scheme is useful in many situations in smart grid operations. The smart grid Control Center (CC) communicates with the sensor nodes installed in the transmission lines so as to utilize real time data for monitoring environmental conditions in order to determine optimum power transmission capacity. Again a smart grid Operation Center (OC) communicates with several Residential Area (RA) gateways (GW) that are in turn connected to the smart meters installed in the consumer premises so as to dynamically control the power supply to meet demand based on real time electricity use information. It is not only necessary to authenticate sensor nodes and other smart devices, but also protect the integrity of messages being communicated. Our scheme is based on batch signatures and are more efficient than existing schemes. Furthermore our scheme is based on stronger notion of security, whereby the batch of signatures verify only if all individual signatures are valid. The communication overhead is kept low by using short signatures for verification.
Fog computing provides a new architecture for the implementation of the Internet of Things (IoT), which can connect sensor nodes to the cloud using the edge of the network. This structure has improved the latency and energy consumption in the cloud. In this heterogeneous and distributed environment, resource allocation is very important. Hence, scheduling will be a challenge to increase productivity and allocate resources appropriately to the tasks. Programs that run in this environment should be protected from intruders. We consider three parameters as authentication, integrity, and confidentiality to maintain security in fog devices. These parameters have time and computational overhead. In the proposed approach, we schedule the modules for the run in fog devices by heuristic algorithms based on data mining technique. The objective function is included CPU utilization, bandwidth, and security overhead. We compare the proposed algorithm with several heuristic algorithms. The results show that our proposed algorithm improved the average energy consumption of 63.27%, cost 44.71% relative to the PSO, ACO, SA algorithms.
Wireless sensor networks are the most prominent set of recently made sensor nodes. They play a numerous role in many applications like environmental monitoring, agriculture, Structural and industrial monitoring, defense applications. In WSN routing is one of the absolutely requisite techniques. It enhance the network lifetime. This can be gives additional priority and system security by using bio inspired algorithm. The combination of bio inspired algorithms and routing algorithms create a way to easy data transmission and improves network lifetime. We present a new metaheuristic hybrid algorithm namely firefly algorithm with Localizability aided localization routing protocol for encircle monitoring in wireless area. This algorithm entirely covers the wireless sensor area by localization process and clumping the sensor nodes with the use of LAL (Localizability Aided Localization) users can minimize the time latency, packet drop and packet loss compared to traditional methods.
The base station (BS) is the main device in a wireless sensor network (WSN) and used to collect data from all the sensor nodes. The information of the whole network is stored in the BS and hence it is always targeted by the adversaries who want to interrupt the operation of the network. The nodes transmit their data to the BS using multi-hop technique and hence form an eminent traffic pattern that can be easily observed by a remote adversary. The presented research aims to increase the anonymity of the BS. The proposed scheme uses a mobile BS and ring nodes to complete the above mentioned objective. The simulation results show that the proposed scheme has superior outcomes as compared to the existing techniques.
Tactical wireless sensor networks (WSNs) are deployed over a region of interest for mission centric operations. The sink node in a tactical WSN is the aggregation point of data processing. Due to its essential role in the network, the sink node is a high priority target for an attacker who wishes to disable a tactical WSN. This paper focuses on the mitigation of sink-node vulnerability in a tactical WSN. Specifically, we study the issue of protecting the sink node through a technique known as k-anonymity. To achieve k-anonymity, we use a specific routing protocol designed to work within the constraints of WSN communication protocols, specifically IEEE 802.15.4. We use and modify the Lightweight Ad hoc On-Demand Next Generation (LOADng) reactive-routing protocol to achieve anonymity. This modified LOADng protocol prevents an attacker from identifying the sink node without adding significant complexity to the regular sensor nodes. We simulate the modified LOADng protocol using a custom-designed simulator in MATLAB. We demonstrate the effectiveness of our protocol and also show some of the performance tradeoffs that come with this method.
6LoWPAN networks involving wireless sensors consist of resource starving miniature sensor nodes. Since secured authentication of these resource-constrained sensors is one of the important considerations during communication, use of asymmetric key distribution scheme may not be the perfect choice to achieve secure authentication. Recent research shows that Lucky Thirteen attack has compromised Datagram Transport Layer Security (DTLS) with Cipher Block Chaining (CBC) mode for key establishment. Even though EAKES6Lo and S3K techniques for key establishment follow the symmetric key establishment method, they strongly rely on a remote server and trust anchor for secure key distribution. Our proposed Lightweight Authentication Protocol (LAUP) used a symmetric key method with no preshared keys and comprised of four flights to establish authentication and session key distribution between sensors and Edge Router in a 6LoWPAN environment. Each flight uses freshly derived keys from existing information such as PAN ID (Personal Area Network IDentification) and device identities. We formally verified our scheme using the Scyther security protocol verification tool for authentication properties such as Aliveness, Secrecy, Non-Injective Agreement and Non-Injective Synchronization. We simulated and evaluated the proposed LAUP protocol using COOJA simulator with ContikiOS and achieved less computational time and low power consumption compared to existing authentication protocols such as the EAKES6Lo and SAKES.
Wireless sensor network is a low cost network to solve many of the real world problems. These sensor nodes used to deploy in the hostile or unattended areas to sense and monitor the atmospheric situations such as motion, pressure, sound, temperature and vibration etc. The sensor nodes have low energy and low computing power, any security scheme for wireless sensor network must not be computationally complex and it should be efficient. In this paper we introduced a secure routing protocol for WSNs, which is able to prevent the network from DDoS attack. In our methodology we scan the infected nodes using the proposed algorithm and block that node from any further activities in the network. To protect the network we use intrusion prevention scheme, where specific nodes of the network acts as IPS node. These nodes operate in their radio range for the region of the network and scan the neighbors regularly. When the IPS node find a misbehavior node which is involves in frequent message passing other than UDP and TCP messages, IPS node blocks the infected node and also send the information to all genuine sender nodes to change their routes. All simulation work has been done using NS 2.35. After simulation the proposed scheme gives feasible results to protect the network against DDoS attack. The performance parameters have been improved after applying the security mechanism on an infected network.
This paper considers the physical layer security for the cluster-based cooperative wireless sensor networks (WSNs), where each node is equipped with a single antenna and sensor nodes cooperate at each cluster of the network to form a virtual multi-input multi-output (MIMO) communication architecture. We propose a joint cooperative beamforming and jamming scheme to enhance the security of the WSNs where a part of sensor nodes in Alice's cluster are deployed to transmit beamforming signals to Bob while a part of sensor nodes in Bob's cluster are utilized to jam Eve with artificial noise. The optimization of beamforming and jamming vectors to minimize total energy consumption satisfying the quality-of-service (QoS) constraints is a NP-hard problem. Fortunately, through reformulation, the problem is proved to be a quadratically constrained quadratic problem (QCQP) which can be solved by solving constraint integer programs (SCIP) algorithm. Finally, we give the simulation results of our proposed scheme.
Ensuring security in the military applications of IoT is a big challenge. The main reasons for this state of affairs is that the sensor nodes of the network are usually mobile, use wireless links, have a small processing power and have a little energy resources. The paper presents the solution for cryptographic protection of transmission between sensor nodes in the data link layer and for cryptographic protection of data stored in the sensor node resources. For this purpose, the Trusted Platform Module (TPM) was used. The proposed solution makes it possible to build secure and fault tolerant sensor network. The following aspects were presented in the paper: the model of such a network, applied security solutions, analysis of the security in the network and selected investigation results of such a network were presented.
The main challenge of ultra-reliable machine-to-machine (M2M) control applications is to meet the stringent timing and reliability requirements of control systems, despite the adverse properties of wireless communication for delay and packet errors, and limited battery resources of the sensor nodes. Since the transmission delay and energy consumption of a sensor node are determined by the transmission power and rate of that sensor node and the concurrently transmitting nodes, the transmission schedule should be optimized jointly with the transmission power and rate of the sensor nodes. Previously, it has been shown that the optimization of power control and rate adaptation for each node subset can be separately formulated, solved and then used in the scheduling algorithm in the optimal solution of the joint optimization of power control, rate adaptation and scheduling problem. However, the power control and rate adaptation problem has been only formulated and solved for continuous rate transmission model, in which Shannon's capacity formulation for an Additive White Gaussian Noise (AWGN) wireless channel is used in the calculation of the maximum achievable rate as a function of Signal-to-Interference-plus-Noise Ratio (SINR). In this paper, we formulate the power control and rate adaptation problem with the objective of minimizing the time required for the concurrent transmission of a set of sensor nodes while satisfying their transmission delay, reliability and energy consumption requirements based on the more realistic discrete rate transmission model, in which only a finite set of transmit rates are supported. We propose a polynomial time algorithm to solve this problem and prove the optimality of the proposed algorithm. We then combine it with the previously proposed scheduling algorithms and demonstrate its close to optimal performance via extensive simulations.