Biblio

Wireless Sensor Network is the combination of small devices called sensor nodes, gateways and software. These nodes use wireless medium for transmission and are capable to sense and transmit the data to other nodes. Generally, WSN composed of two types of nodes i.e. generic nodes and gateway nodes. Generic nodes having the ability to sense while gateway nodes are used to route that information. IoT now extended to IoET (internet of Everything) to cover all electronics exist around, like a body sensor networks, VANET's, smart grid stations, smartphone, PDA's, autonomous cars, refrigerators and smart toasters that can communicate and share information using existing network technologies. The sensor nodes in WSN have very limited transmission range as well as limited processing speed, storage capacities and low battery power. Despite a wide range of applications using WSN, its resource constrained nature given birth to a number severe security attacks e.g. Selective Forwarding attack, Jamming-attack, Sinkhole attack, Wormhole attack, Sybil attack, hello Flood attacks, Grey Hole, and the most dangerous BlackHole Attacks. Attackers can easily exploit these vulnerabilities to compromise the WSN network.

Mobile ad hoc networks (MANET) is a type of networks that consists of autonomous nodes connecting directly without a top-down network architecture or central controller. Absence of base stations in MANET force the nodes to rely on their adjacent nodes in transmitting messages. The dynamic nature of MANET makes the relationship between nodes untrusted due to mobility of nodes. A malicious node may start denial of service attack at network layer to discard the packets instead of forwarding them to destination which is known as black hole attack. In this paper a secure and trust based approach based on ad hoc on demand distance vector (STAODV) has been proposed to improve the security of AODV routing protocol. The approach isolates the malicious nodes that try to attack the network depending on their previous information. A trust level is attached to each participating node to detect the level of trust of that node. Each incoming packet will be examined to prevent the black hole attack.

With the integration of computing, communication, and physical processes, the modern power grid is becoming a large and complex cyber physical power system (CPPS). This trend is intended to modernize and improve the efficiency of the power grid, yet it makes the CPPS vulnerable to potential cascading failures caused by cyber-attacks, e.g., the attacks that are originated by the cyber network of CPPS. To prevent these risks, it is essential to analyze how cyber-attacks can be conducted against the CPPS and how they can affect the power systems. In light of that General Packet Radio Service (GPRS) has been widely used in CPPS, this paper provides a case study by examining possible cyber-attacks against the cyber-physical power systems with GPRS-based SCADA system. We analyze the vulnerabilities of GPRS-based SCADA systems and focus on DoS attacks and message spoofing attacks. Furthermore, we show the consequence of these attacks against power systems by a simulation using the IEEE 9-node system, and the results show the validity of cascading failures propagated through the systems under our proposed attacks.

Wearable Internet-of-Things (WIoT) environments have demonstrated great potential in a broad range of applications in healthcare and well-being. Security is essential for WIoT environments. Lack of security in WIoTs not only harms user privacy, but may also harm the user's safety. Though devices in the WIoT can be attacked in many ways, in this paper we focus on adversaries who mount what we call sensor-hijacking attacks, which prevent the constituent medical devices from accurately collecting and reporting the user's health state (e.g., reporting old or wrong physiological measurements). In this paper we outline some of our experiences in implementing a data-driven security solution for detecting sensor-hijacking attack on a secure wearable internet-of-things (WIoT) base station called the Amulet. Given the limited capabilities (computation, memory, battery power) of the Amulet platform, implementing such a security solution is quite challenging and presents several trade-offs with respect to detection accuracy and resources requirements. We conclude the paper with a list of insights into what capabilities constrained WIoT platforms should provide developers so as to make the inclusion of data-driven security primitives in such systems.

Unmanned Aerial Vehicles (UAVs) are autonomous aircraft that, when equipped with wireless communication interfaces, can share data among themselves when in communication range. Compared to single UAVs, using multiple UAVs as a collaborative swarm is considerably more effective for target tracking, reconnaissance, and surveillance missions because of their capacity to tackle complex problems synergistically. Success rates in target detection and tracking depend on map coverage performance, which in turn relies on network connectivity between UAVs to propagate surveillance results to avoid revisiting already observed areas. In this paper, we consider the problem of optimizing three objectives for a swarm of UAVs: (a) target detection and tracking, (b) map coverage, and (c) network connectivity. Our approach, Dual-Pheromone Clustering Hybrid Approach (DPCHA), incorporates a multi-hop clustering and a dual-pheromone ant-colony model to optimize these three objectives. Clustering keeps stable overlay networks, while attractive and repulsive pheromones mark areas of detected targets and visited areas. Additionally, DPCHA introduces a disappearing target model for dealing with temporarily invisible targets. Extensive simulations show that DPCHA produces significant improvements in the assessment of coverage fairness, cluster stability, and connection volatility. We compared our approach with a pure dual- pheromone approach and a no-base model, which removes the base station from the model. Results show an approximately 50% improvement in map coverage compared to the pure dual-pheromone approach.

Reliable detection of intrusion is the basis of safety in cognitive radio networks (CRNs). So far, few scholars applied intrusion detection systems (IDSs) to combat intrusion against CRNs. In order to improve the performance of intrusion detection in CRNs, a distributed intrusion detection scheme has been proposed. In this paper, a method base on Dempster-Shafer's (D-S) evidence theory to detect intrusion in CRNs is put forward, in which the detection data and credibility of different local IDS Agent is combined by D-S in the cooperative detection center, so that different local detection decisions are taken into consideration in the final decision. The effectiveness of the proposed scheme is verified by simulation, and the results reflect a noticeable performance improvement between the proposed scheme and the traditional method.

Link quality protocols employ link quality estimators to collect statistics on the wireless link either independently or cooperatively among the sensor nodes. Furthermore, link quality routing protocols for wireless sensor networks may modify an estimator to meet their needs. Link quality estimators are vulnerable against malicious attacks that can exploit them. A malicious node may share false information with its neighboring sensor nodes to affect the computations of their estimation. Consequently, malicious node may behave maliciously such that its neighbors gather incorrect statistics about their wireless links. This paper aims to detect malicious nodes that manipulate the link quality estimator of the routing protocol. In order to accomplish this task, MINTROUTE and CTP routing protocols are selected and updated with intrusion detection schemes (IDSs) for further investigations with other factors. It is proved that these two routing protocols under scrutiny possess inherent susceptibilities, that are capable of interrupting the link quality calculations. Malicious nodes that abuse such vulnerabilities can be registered through operational detection mechanisms. The overall performance of the new LQR protocol with IDSs features is experimented, validated and represented via the detection rates and false alarm rates.

A major issue to secure wireless sensor networks is key distribution. Current key distribution schemes are not fully adapted to the tiny, low-cost, and fragile sensors with limited computation capability, reduced memory size, and battery-based power supply. This paper investigates the design of an efficient key distribution and management scheme for wireless sensor networks. The proposed scheme can ensure the generation and distribution of different encryption keys intended to secure individual and group communications. This is performed based on elliptic curve public key encryption using Diffie-Hellman like key exchange and secret sharing techniques that are applied at different levels of the network topology. This scheme is more efficient and less complex than existing approaches, due to the reduced communication and processing overheads required to accomplish key exchange. Furthermore, few keys with reduced sizes are managed in sensor nodes which optimizes memory usage, and enhances scalability to large size networks.

Key management is the core to ensure the communication security of wireless sensor network. How to establish efficient key management in wireless sensor networks (WSN) is a challenging problem for the constrained energy, memory, and computational capabilities of the sensor nodes. Previous research on sensor network security mainly considers homogeneous sensor networks with symmetric key cryptography. Recent researches have shown that using asymmetric key cryptography in heterogeneous sensor networks (HSN) can improve network performance, such as connectivity, resilience, etc. Considering the advantages and disadvantages of symmetric key cryptography and asymmetric key cryptography, the paper propose an efficient and hybrid key management method for heterogeneous wireless sensor network, cluster heads and base stations use public key encryption method based on elliptic curve cryptography (ECC), while using symmetric encryption method between adjacent nodes in the cluster. The analysis and simulation results show that the proposed key management method can provide better security, prefect scalability and connectivity with saving on storage space.

Wireless Sensor Networks (WSNs) are used in many applications in military, environmental, and health-related areas. These applications often include the monitoring of sensitive information such as enemy movement on the battlefield or the location of personnel in a building. Security is important in WSNs. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the use of insecure wireless communication channels. These constraints make security in WSNs a challenge. In this paper, we try to explore security issue in WSN. First, the constraints, security requirements and attacks with their corresponding countermeasures in WSNs are explained. Individual sensor nodes are subject to compromised security. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a Gray hole by compromised nodes. If these two kinds of attacks occur simultaneously in a network, some of the existing methods fail to defend against those attacks. The Ad-hoc On Demand Distance (AODV) Vector scheme for detecting Gray-Hole attack and Statistical En-Route Filtering is used for detecting false report. For increasing security level, the Elliptic Curve Cryptography (ECC) algorithm is used. Simulations results obtain so far reduces energy consumption and also provide greater network security to some extent.

We consider the problem of cross-layer resource allocation with information-theoretic secrecy for uplink transmissions in time-varying cellular wireless networks. Particularly, each node in an uplink cellular network injects two types of traffic, confidential and open at rates chosen in order to maximize a global utility function while keeping the data queues stable and meeting a constraint on the secrecy outage probability. The transmitting node only knows the distribution of channel gains. Our scheme is based on Hybrid Automatic Repeat Request (HARQ) transmission with incremental redundancy. We prove that our scheme achieves a utility, arbitrarily close to the maximum achievable. Numerical experiments are performed to verify the analytical results and to show the efficacy of the dynamic control algorithm.
 

With the growing demand for increased spectral efficiencies, there has been renewed interest in enabling full-duplex communications. However, existing approaches to enable full-duplex require a clean-slate approach to address the key challenge in full-duplex, namely self-interference suppression. This serves as a big deterrent to enabling full-duplex in existing cellular networks. Towards our vision of enabling full-duplex in legacy cellular, specifically LTE networks, with no modifications to existing hardware at BS and client as well as technology specific industry standards, we present the design of our experimental system FD-LTE, that incorporates a combination of passive SI cancellation schemes, with legacy LTE half-duplex BS and client devices. We build a prototype of FD-LTE, integrate it with LTE's evolved packet core and conduct over-the-air experiments to explore the feasibility and potential for full-duplex with legacy LTE networks. We report promising experimental results from FD-LTE, which currently applies to scenarios with limited ranges that is typical of small cells.
 

With the urban traffic planning and management development, it is a highly considerable issue to analyze and estimate the original-destination data in the city. Traditional method to acquire the OD information usually uses household survey, which is inefficient and expensive. In this paper, the new methodology proposed that using mobile phone data to analyze the mechanism of trip generation, trip attraction and the OD information. The mobile phone data acquisition is introduced. A pilot study is implemented on Beijing by using the new method. And, much important traffic information can be extracted from the mobile phone data. We use the K-means clustering algorithm to divide the traffic zone. The attribution of traffic zone is identified using the mobile phone data. Then the OD distribution and the commuting travel are analyzed. At last, an experiment is done to verify availability of the mobile phone data, that analyzing the "Traffic tide phenomenon" in Beijing. The results of the experiments in this paper show a great correspondence to the actual situation. The validated results reveal the mobile phone data has tremendous potential on OD analysis.
 

Wireless Sensor Network has a wide range of applications including environmental monitoring and data gathering in hostile environments. This kind of network is easily leaned to different external and internal attacks because of its open nature. Sink node is a receiving and collection point that gathers data from the sensor nodes present in the network. Thus, it forms bridge between sensors and the user. A complete sensor network can be made useless if this sink node is attacked. To ensure continuous usage, it is very important to preserve the location privacy of sink nodes. A very good approach for securing location privacy of sink node is proposed in this paper. The proposed scheme tries to modify the traditional Blast technique by adding shortest path algorithm and an efficient clustering mechanism in the network and tries to minimize the energy consumption and packet delay.

For wireless sensor networks deployed to monitor and report real events, event source-location privacy (SLP) is a critical security property. Previous work has proposed schemes based on fake packet injection such as FitProbRate and TFS, to realize event source anonymity for sensor networks under a challenging attack model where a global attacker is able to monitor the traffic in the entire network. Although these schemes can well protect the SLP, there exists imbalance in traffic or delay. In this paper, we propose an Optimal-cluster-based Source Anonymity Protocol (OSAP), which can achieve a tradeoff between network traffic and real event report latency through adjusting the transmission rate and the radius of unequal clusters, to reduce the network traffic. The simulation results demonstrate that OSAP can significantly reduce the network traffic and the delay meets the system requirement.

Wireless Sensor Networks (WSNs) are deployed to monitor the assets (endangered species) and report the locations of these assets to the Base Station (BS) also known as Sink. The hunter (adversary) attacks the network at one or two hops away from the Sink, eavesdrops the wireless communication links and traces back to the location of the asset to capture them. The existing solutions proposed to preserve the privacy of the assets lack in energy efficiency as they rely on random walk routing technique and fake packet injection technique so as to obfuscate the hunter from locating the assets. In this paper we present an energy efficient privacy preserved routing algorithm where the event (i.e., asset) detected nodes called as source nodes report the events' location information to the Base Station using phantom source (also known as phantom node) concept and a-angle anonymity concept. Routing is done using existing greedy routing protocol. Comparison through simulations shows that our solution reduces the energy consumption and delay while maintaining the same level of privacy as that of two existing popular techniques.