Top PDF Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

Trajectory Privacy Preservation in Mobile Wireless Sensor Networks

the optimal mechanism for TPP. Humbert et al. studied the problem of designing mix zones in the presence of local eavesdroppers [HMFH10]. The work proposed in [CO11, CA12] mainly focused on the incentive designs to provide the required trajectory privacy level for individual users as well as the desired granularity for service providers/mobile commerce companies. The above work attempted to ad- dress the optimal strategies for two competing entities, user-adversary or user-service provider. There is some other work that has been proposed to study the interactions between peer nodes. Researchers used game theory to model the cooperation behav- iors while taking the selfishness of autonomous nodes into consideration in the non- cooperative network environment [FMHP09, DMNRDSHSH11, KPM11]. In such networks, each node aims to maximize its own payoff while determining whether it cooperates TPP activities to gain (or assist other nodes to gain) trajectory privacy. To study the malice of compromised nodes, researchers have presented comprehen- sive analysis in intrusion detection games in mobile networks [WCK09, YCM06]. The previous work is of great inspiration in discussing the degree of trust in co- operation among peer nodes. However, solely considering selfishness or malice is insufficient for vulnerable networks composed of autonomous nodes.
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PRESERVATION OF PRIVACYAND SECURTITY FOR INFORMATION IN WIRELESS MEDICAL SENSOR NETWORKS

PRESERVATION OF PRIVACYAND SECURTITY FOR INFORMATION IN WIRELESS MEDICAL SENSOR NETWORKS

In [10], a novel key agreement scheme that allows neighbouring nodes in BANs to share a common key generated by electrocardiogram (ECG) signals. The improved Jules Sudan (IJS) algorithm is proposed to set up the key agreement for the message authentication. The ECG-IJS key agreement secures data communications over BANs without any key distribution overheads. In this the simulation and experimental results are presented, which demonstrate that the ECG-IJS scheme can achieve better security performance in terms of performance metrics such as false acceptance rate (FAR) and false rejection rate (FRR) than other existing approaches. Based on the IJS algorithm described earlier, propose an ECG-IJS key agreement to secure data communication in BANs. Thus privacy and authentication are preserved in energy efficient way.
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Security in mobile wireless sensor networks - A survey

Security in mobile wireless sensor networks - A survey

Dummy data injection. The basic idea of dummy data injection is to perturb traffic by sending fake packets. As a consequence, the traffic observed by adversary is added with “noise” so that it is not easy to quickly identify fake paths and eliminate them from consideration. In [28], a simple scheme, called Short-lived Fake Source Routing, was proposed to protect location privacy. Take communication overhead and energy consumption into account. On the one hand, the scheme enables each sensor to send fake packets with a pre-determined probability. On the other hand, upon receiving a fake packet, a sensor just discards it to prevent from further sending it to others. Although the scheme can perturb the local traffic observed by adversary, it is ineffective when it meets a global adversary that can monitor transmission rate of each sensor node and thus identify the sensors that only sends out dummy packets [29]. To solve the problem, one scheme was proposed in [29] that injects dummy packets globally and keeps the transmission of real packets the same as dummy packets against global adversaries who may monitor and analyze the traffic over the whole network. The main idea of [29] is that sensors send out network-wide dummy packets with intervals following a special distribution, such as constant or probabilistic. Thanks to the fact that sending packets follow a pre- determined distribution, the transmission delay of real packets can be reduced without allowing an adversary to identify the real traffic. However, this benefit is achieved at a cost of transmission power for sensors or in other words shorter network lifetime.
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Energy preservation in Wireless Sensor Networks through the Recognition of Trusted Node

Energy preservation in Wireless Sensor Networks through the Recognition of Trusted Node

In the paper [11] they are proposed a scheme to defend against sink hole attack using mobile agents. It proposes two algorithms, that is Agent navigation algorithm and data routing algorithm, every agent has its own brief case that contains the distance between nodes and counter contains the information about particular node as the one hop neighbour. Agent navigation algorithm, in this each node maintains a cache, the agents updates the information in the cache from its brief case. False path is avoided, Encryption and decryption process is avoided, does not require more energy. Overhead increases for larger network in this paper [12] they propose a bio-inspired trust and reputation model, based on ant colony system. They select the most trustworthy node through the most reputable path. The client sends the ants equal to number of senor nodes that finds the server and return to the client, it stores the pheromone traces. Every node has the trace of its neighbour. By using the most reputable path we can find the trustworthy node in that path. It is accurate and reliable, offers punishment and reward. It does not distinguish benevolent and fraudulent based on a certain service.
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An Accountable Access Control with Enhanced Privacy in Wireless Sensor Networks

An Accountable Access Control with Enhanced Privacy in Wireless Sensor Networks

Privacy issue has been widely explored moreover in all fields. Many techniques have been proposed for achieving privacy preservation in sensor network.[1][4] Yet, a large number of attacks are possible in WSN either internally or externally such as: Denial of Service, Sybil attacks, eaves dropping, attacks against privacy and so on. The earlier works were focused on communication security and data security, some techniques have been proposed to provide privacy over the data collection and transmission through WSN such as DP 2 AC and the ring signature.[4] These two techniques were able to hide the users identity henceforth guarantees privacy.[5] However, they are faced with some security weakness. It has been reported that DP 2 AC is not efficient in providing the token uniformly; it is not fine grained since each query command cannot be signed by the network user, therefore an intruder might get the access easily and gets authorized to modify the query command according to his wish.[6] Then comes the ring structure which makes both the computation complexity and makes anonymity strength depend on the size chosen and moreover, it is not designed with user authorizability.[8] Clearly, a practical access control should not restrict the user at any cause.
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Achieving Privacy and Integrity of Data Aggregation in Wireless Sensor Networks

Achieving Privacy and Integrity of Data Aggregation in Wireless Sensor Networks

We notice that both CPDA and SMART trade message overhead for privacy. However, sometimes message overhead is a big concern, especially in mobile and pervasive computing scenarios. So it is very natural to ask: “Can we further improve efficiency or reduce the message overhead of the proposed protocols, and how?” In our original design space, the metrics we used include computational overhead, accuracy, privacy preserving capability. For better efficiency what else can we trade off? What will happen if we explore one more dimension such as delay? For example, an effective way to reduce message overhead in data aggregation is to delay data aggregation until a series of data are collected at individual nodes. Then, these nodes use an efficient representation to express the data series, and aggregate the parameters of the representation. Finally, the base station can recover the original data series. In such a way, message overhead of data aggregation can be further reduced. For example, if we want to send integer 1, 2, 3, · · · , 99 to a receiver, we will prefer to send “positive integers less than 100” than 99 integers to save bandwidth.
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Relay Node Placement and Trajectory Computation of Mobile Data Collectors in Wireless Sensor Networks

Relay Node Placement and Trajectory Computation of Mobile Data Collectors in Wireless Sensor Networks

Sensor nodes are underlying building blocks of sensor networks. A typical sensor node, as shown in Figure 2.1, which is simplified from [24], is usually equipped with a sensing unit for measuring the intentional target (e.g. temperature, humidity, pressure and object- presence/absence etc.). After sensing its vicinity, the raw data generated by a sensing unit is generally in an analogous format which is not computer-readable; therefore, an analog-to-digital convertor (ADC) is normally required to transform the analog data into digital format which, in turn, is further processed by a processing unit. The resultant data from a processing unit is cached into the local memory and when it comes the turn for a sensor node to transmit, the cached data is sent out by the radio communication unit following a pre-established routing path to base station.
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Privacy Preserving Secure Data Aggregation for Wireless Sensor Networks

Privacy Preserving Secure Data Aggregation for Wireless Sensor Networks

In this section, we describe attempts prevalent in the literature, to implement one or the other ECC based privacy homomorphic algorithms in the resource-constrained environment. An Liu et al. [12] implement TinyECC as a configurable library for ECC operations in WSNs. However, in this attempt, the authors implement EC-DSA (integrity preservation), EC-DH (key exchange) and EC-IES (homomorphic encryption) and apparently highlight EC-IES, as the best suited homomorphic encryption algorithm. Osman Ugus et al. [13] implement EC-EG, but without using vital metrics of evaluation for WSNs viz. Storage utilization, energy consumption, encryption-decryption time. Osman Ugus et al. [13] again use only EC-EG privacy homomorphic algorithm. S. Peter et al. [9] theoretically evaluated four ECC based privacy homomorphic encryption algorithms, without any underlying implementation. Vivaksha Jariwala et al. [61] attempt comparative empirical evaluation, but using non-ECC based privacy homomorphic encryption algorithms. Xiaoyan Wang et al. [16], propose secure and efficient scheme for data aggregation in WSNs. The proposed approach uses Castelluccia-Mykletun-Tsudik [7] scheme for encryption. Castelluccia-Mykletun-Tsudik [7] is a symmetric key cryptography based scheme and suffers from the key management issues. Poornima et al. [17], follow a similar approach based on symmetric key cryptography where the same key is shared between the leaf node and the base station. Jacques M. et al. [14], propose a scheme for SDA using elliptic curve cryptography that achieves only confidentiality without integrity.
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Safeguarding Privacy in Wireless Sensor Networks
N Arundeep & B Ramesh

Safeguarding Privacy in Wireless Sensor Networks N Arundeep & B Ramesh

The Location Privacy Protection Act of 2012 was introduced by Senator Al Franken in order to regulate the transmission and sharing of user location data in USA. It is based on the individual's one time consent to participate in these services (Opt In). The bill specifies the collecting entities, the collectable data and its usage. The bill does not specify, however, the period of time that the data collecting entity can hold on to the user data (a limit of 24 hours seems appropriate since most of the services use the data for immediate searches, communications, etc.), and the bill does not include location data stored locally on the device (the user should be able to delete the contents of the location data document periodically just as he would delete a log document). The bill which was approved last month by the Senate Judiciary Committee, would also require mobile services to disclose the names of the advertising networks or other third parties with which they share consumers’ locations.
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A near optimal source location privacy scheme for wireless sensor networks

A near optimal source location privacy scheme for wireless sensor networks

Other techniques to provide SLP against local attackers include using space in MAC beacon frames to disseminate messages from the source to other areas in the network before being routed to the sink [15]. Coordinated jamming [16] which uses jamming to defeat localisation techniques. And, data mules [17, 18] where a mobile agent gathering messages near the source and moves near the sink before broadcasting them. The solutions discussed so far have focused on a local dis- tributed eavesdropping attacker and there are other capabilities which can be considered [19]. Attackers with a global view of the network are one such example. Techniques that provide privacy against them tend to take different approaches to local attackers. For example some techniques require that all nodes broadcast periodically according to some ruleset even if there is no message to send [20, 21]. Other traffic decorrelation techniques [22] have also been used.
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Privacy preserving and the detection of the packet networks when the attacks fail in the wireless sensor networks

Privacy preserving and the detection of the packet networks when the attacks fail in the wireless sensor networks

All the mobile nodes tend to have a unique id for its identification process, since the mobile nodes communicates with other nodes through its own network id. If any mobile node opted out of the network then the particular node should surrender its network id to the head node.

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Z-path trajectory mechanism for mobile beacon-assisted localization in wireless sensor networks

Z-path trajectory mechanism for mobile beacon-assisted localization in wireless sensor networks

A well studied deterministic trajectory for mobile beacon-assisted localization in a real environment is desired to ensure that all the unknown sensors receive sufficient numbers of non-collinear beacon messages for maximum localization precision and minimum energy cost. The existing designed trajectory mechanisms have some limitations which are briefly addressed here. First, accuracy, as the critical goal of localization techniques is not successfully obtained, especially in a real environment. A node is best localized if the trajectory is close to that node since the RSS is higher. But, this property is not sufficient to guarantee the precision of localization because the RSS is dominated by the environmental interference. The signal may also scattered by the obstacles and thus, increase the estimated error. Accordingly, a reliable channel and radio model is crucially demanded to improve the accuracy of localization, especially at the presence of obstacles. The obstruction in the sensing field cannot be tolerated by most of the trajectories even though the path is blocked by these obstacles. Second, the existing paths left the uncovered area by the mobile beacon in the network field which cause to a lower localization success. Next, collinear beacon messages are critical issue in the existing trajectories which demands further investigation. These useless messages not only impair the precision of the localization but also increase the time and energy consumption. The above limitations lead this research to address the problem of finding a trajectory mechanism traveled by the mobile beacon in order to localize the statically deployed unknown sensors in real environment with higher precision and lower energy consumption. Considering the stated problem, the research hypothesis can be expressed as follows:
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Integration of Wireless Sensor Networks and          Mobile Cloud- a Survey

Integration of Wireless Sensor Networks and Mobile Cloud- a Survey

Mobile devices such as smart phones, tablet pcs etc are become a crucial part of human life. The mobile users are experiencing different services from mobile applications for example Google apps, iphone apps etc are storing datas on remote servers through wireless networks. The most important feature of communication provided by these mobile devices are, it is not bounded by time and place. The quick progress of mobile computing (MC) has a strong role in the development of information technology (IT).

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Rendezvous Planning in Wireless Sensor Networks with Mobile Elements

Rendezvous Planning in Wireless Sensor Networks with Mobile Elements

Due to the communication devices on sensor nodes have limited battery capacity and transmission range, wireless sensor networks (WSNs) are considered to be energy constrained. In this paper, we propose a novel clustering algorithm called limiting member node clustering (LmC) algorithm to limit the number of member nodes for each cluster head by using a threshold value. The proposed clustering approach selects a cluster head based on a new cost function which considers the residual battery level, energy consumption and distance to the base station. In our experiments, we considered the transmission range of the base station in WSNs to improve the clustering performance. From experimental results, the proposed algorithm can efficiently achieve high number of successfully delivered packets as well as the longest network lifetime while give the shortest delay time and low energy consumption when compared with different existing algorithms.
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Mobile Wireless Sensor Networks: Architects for Pervasive Computing

Mobile Wireless Sensor Networks: Architects for Pervasive Computing

Mobile Wireless sensor networks (Figure 1) are believed to have more channel capacity as compared to static WSN. The capacity gain has been calculated in case of mobile sink within WSN and has come out to be 3-5 times more than static WSN, provided the number of mobile sinks increases linearly with the growth of sensor nodes [32]. The other advantage of mWSN is its better targeting. Because, mostly the sensors are deployed randomly, as opposed to precisely, therefore there is often a requirement to move the sensor node for better sight or for close proximity. Also mobility helps in better quality of communication between sensor nodes. In a sparse or disconnected network, this property is especially helpful to maintain efficient network connectivity. Another advantage comes in the form of data fidelity. It is well known that the probability of error increases with increasing number of hops that a data packet has to travel. If we reduce the number of hops, this immediately reduces the probability of error. This not only increase the quality of data received but further reduces the energy spent at the static nodes by reducing the retransmissions required due to errors. Based on communication type, two kinds of mobile wireless sensor network exist at present. One is known as the infrastructure network in which the mobile unit is connected with the nearest base station that is within its communication radius to contact; as in the current mobile telephone system. The other one is called infrastructure-less mobile network, also knows as ad hoc network. No fixed routers are needed and all mobile units are capable of movement and still being able to self-organize and establish communication in an arbitrary manner. In this chapter we discuss the evolution of mobile Wireless Sensor Network and some of its characteristics which make
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Efficient Node Discovery in Mobile Wireless Sensor Networks

Efficient Node Discovery in Mobile Wireless Sensor Networks

Energy efficient service discovery can be done using power efficient wake-up scheduling protocols, such as [1, 2]. These protocols allow for very energy efficient communication in static wireless sensor networks. They are not, however, able to exploit the fact that contact patterns might be regular and distributed in such a way that there are periods in which nodes do not encounters other nodes. Our approach works on top of existing wake-up scheduling protocols, allowing them to make better decisions as to when to and how frequently to perform service discovery. In [5] an adaptive node discovery approach is proposed for static sink nodes to track mobile objects: some learning techniques have been used there to drive the discovery, however the network of sensors for that paper was static not allowing for the variability inherent in a mobile sensor network. A variable inquiry rate has been used to collect Bluetooth traces in [6]. To save power the nodes were configured to sample the neighbourhood more frequently when no nodes are detected and then reduce the sampling rate if there are nodes around. Although an approach was used to actually collect traces, there was no evaluation quantifying an impact of this technique on the number of detected encounters.
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A Review of Efficient Coverage and Connectivity Preservation with Load Balance for Wireless Sensor Networks

A Review of Efficient Coverage and Connectivity Preservation with Load Balance for Wireless Sensor Networks

Abstract - One of the first objectives of wireless sensing element networks is to produce full coverage of a sensing field as long as possible. Several tasks—such as object tracking and battleground intrusion detection—require full coverage at any time. With the restricted energy of sensor nodes, organizing these nodes into a maximal number of subgroups (or referred to as set cover) capable of observance all discrete points of interest and so alternately activating them may be a prevalent way to give higher quality of surveillance. Additionally to maximising the amount of subgroups, the way to guarantee the connectivity of sensor nodes (i.e., there exist links between the base station (BS) and sensor nodes) is also significantly important while achieving full coverage. In this paper, thus, we tend to develop a completely unique maximum connected load-balancing cover tree (MCLCT) algorithmic rule to achieve full coverage further as BS- connectivity of every sensing node by dynamically forming load-balanced routing cover trees.
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An Efficient Clustering Technique for Mobile Wireless Sensor Networks

An Efficient Clustering Technique for Mobile Wireless Sensor Networks

A wireless sensor networks (WSNs) is a combination of sensor nodes that are small in size communicating untethered within short distances. Numbers of sensor nodes are connected wirelessly via infrared or radio waves, depending on the application involved [1]. Advances in micro-electro-mechanical systems (MEMS) technology, wireless technology, as well as digital electronics have enabled these sensor nodes to function with low cost, low power, and carry multifunction abilities [2]. They are commonly used for monitoring applications of environments where human access is limited [3]. These sensor nodes carry three (3) major roles including sensing, processing, and communicating.
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Security and Privacy Preservation in Mobile Crowdsensing

Security and Privacy Preservation in Mobile Crowdsensing

We have proposed a preliminary work to explore the potentials of exploiting blockchain to balance the fairness among mobile users and customers. In the future work, we further leverage the appealing properties, including distribution, opening, permanency, security, timing and pseudonymity, to extend the security, privacy and fairness in MCS. Specifi- cally, as a decentralized and distributed digital ledger, blockchain can be used to record transactions (e.g., contracts, reputation and crowdsensed data) of mobile users and cus- tomers across many nodes so that the record cannot be altered retroactively without the corruption of all subsequent blocks and the collusion of the network. It also allows the participants to verify and audit all the on-block transactions. Further, the blockchain is managed by network nodes and serves as a distributed timestamping server, such that all the transactions are recorded with permanent timestamps. The smart contract is not only an auto-executed protocol offering fairness to participants, but a computer program that digitally facilitate, verify, or enforce the negotiation or performance of a contract with intelligence. Although the blockchain is attractive in MCS, there are still fundamental problems to be solved, such as how to build a private blockchain using proof of stake for saving power consumption, while guaranteeing the distributed and decentralized system to have the desired features, even when various participants have their individual incentives; how to provide the verification, correctness and completeness of smart contracts for enforc- ing the desired behaviors and abandon the irrational results. To address these issues, we will explore new techniques to build incentives for decentralized applications and design new approaches for verifying the correct execution of smart contracts.
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Network Coding based Privacy Preservation Technique for Multi Hop Wireless Networks

Network Coding based Privacy Preservation Technique for Multi Hop Wireless Networks

We focus on the three fundamental information security issues in MWNs; efficient privacy preservation for source anonymity, which is critical to the information security of MWNs, the traffic explosion issue, which targets at preventing denial of service (DoS) and enhancing system availability. It is very challenging to efficiently thwart traffic analysis/flow tracing attacks and provide privacy protection in MWNs. Existing privacy-preserving solutions such as proxy based scheme[2], chaum’s mix based schemes[3], and onion based shemes [4], may either require a series of trusted forwarding proxies or result in these schemes are low degradation in practice. Limitations of these schemes is low network performance, unpredictable delay, high computation cost and message transmission delay. Different from previous schemes, our research investigates the privacy preservation. Network coding technique overcomes the limitation of the existing scemes [5]. To secure Network coding some solutions have been produced. Information based schemes [6] can detect polluted messages at sinks. Cryptography based solutions include homomorphic hashing [7], homomorphic signature [8]. Another secure network coding based on hash functions are proposed in [9]. These solutions incur high computation overhead. And they all mainly focus on detecting and filtering out polluted messages. Little attention has been paid to the privacy issues, especially to protect the encoded messages from tracking or traffic analysis.
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