Current Search:  Wireless Network Security (x)

View All Items

  • CSV Spreadsheet
(1 - 3 of 3)
Networking and security solutions for VANET initial deployment stage
Title
Networking and security solutions for VANET initial deployment stage.
Creator
Aslam, Baber, Zou, Changchun, Turgut, Damla, Bassiouni, Mostafa, Wang, Chung-Ching, University of Central Florida
Abstract / Description
Vehicular ad hoc network (VANET) is a special case of mobile networks, where vehicles equipped with computing/communicating devices (called (")smart vehicles(")) are the mobile wireless nodes. However, the movement pattern of these mobile wireless nodes is no more random, as in case of mobile networks, rather it is restricted to roads and streets. Vehicular networks have hybrid architecture; it is a combination of both infrastructure and infrastructure-less architectures. The direct vehicle...
Show moreVehicular ad hoc network (VANET) is a special case of mobile networks, where vehicles equipped with computing/communicating devices (called (")smart vehicles(")) are the mobile wireless nodes. However, the movement pattern of these mobile wireless nodes is no more random, as in case of mobile networks, rather it is restricted to roads and streets. Vehicular networks have hybrid architecture; it is a combination of both infrastructure and infrastructure-less architectures. The direct vehicle to vehicle (V2V) communication is infrastructure-less or ad hoc in nature. Here the vehicles traveling within communication range of each other form an ad hoc network. On the other hand, the vehicle to infrastructure (V2I) communication has infrastructure architecture where vehicles connect to access points deployed along roads. These access points are known as road side units (RSUs) and vehicles communicate with other vehicles/wired nodes through these RSUs. To provide various services to vehicles, RSUs are generally connected to each other and to the Internet. The direct RSU to RSU communication is also referred as I2I communication. The success of VANET depends on the existence of pervasive roadside infrastructure and sufficient number of smart vehicles. Most VANET applications and services are based on either one or both of these requirements. A fully matured VANET will have pervasive roadside network and enough vehicle density to enable VANET applications. However, the initial deployment stage of VANET will be characterized by the lack of pervasive roadside infrastructure and low market penetration of smart vehicles. It will be economically infeasible to initially install a pervasive and fully networked roadside infrastructure, which could result in the failure of applications and services that depend on V2I or I2I communications. Further, low market penetration means there are insufficient number of smart vehicles to enable V2V communication, which could result in failure of services and applications that depend on V2V communications. Non-availability of pervasive connectivity to certification authorities and dynamic locations of each vehicle will make it difficult and expensive to implement security solutions that are based on some central certificate management authority. Non-availability of pervasive connectivity will also affect the backend connectivity of vehicles to the Internet or the rest of the world. Due to economic considerations, the installation of roadside infrastructure will take a long time and will be incremental thus resulting in a heterogeneous infrastructure with non-consistent capabilities. Similarly, smart vehicles will also have varying degree of capabilities. This will result in failure of applications and services that have very strict requirements on V2I or V2V communications. We have proposed several solutions to overcome the challenges described above that will be faced during the initial deployment stage of VANET. Specifically, we have proposed: 1) a VANET architecture that can provide services with limited number of heterogeneous roadside units and smart vehicles with varying capabilities, 2) a backend connectivity solution that provides connectivity between the Internet and smart vehicles without requiring pervasive roadside infrastructure or large number of smart vehicles, 3) a security architecture that does not depend on pervasive roadside infrastructure or a fully connected V2V network and fulfills all the security requirements, and 4) optimization solutions for placement of a limited number of RSUs within a given area to provide best possible service to smart vehicles. The optimal placement solutions cover both urban areas and highways environments.
Show less
Date Issued
2012
Identifier
CFE0004186, ucf:48993
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004186
Energy Efficient and Secure Wireless Sensor Networks Design
Title
Energy Efficient and Secure Wireless Sensor Networks Design.
Creator
Attiah, Afraa, Zou, Changchun, Chatterjee, Mainak, Wang, Jun, Yuksel, Murat, Wang, Chung-Ching, University of Central Florida
Abstract / Description
ABSTRACTWireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense,process, communicate, and transmit information to a destination, and they are expected to have significantimpact on the efficiency of many applications in various fields. The resource constraintsuch as limited battery power, is the greatest challenge in WSNs design as it affects the lifetimeand performance of the network. An energy efficient, secure, and trustworthy system is vital whena WSN...
Show moreABSTRACTWireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense,process, communicate, and transmit information to a destination, and they are expected to have significantimpact on the efficiency of many applications in various fields. The resource constraintsuch as limited battery power, is the greatest challenge in WSNs design as it affects the lifetimeand performance of the network. An energy efficient, secure, and trustworthy system is vital whena WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energyefficient and secure while at the same time maintaining the desired level of quality of service.Inspired by these challenges, this dissertation is dedicated to exploiting optimization and gametheoretic approaches/solutions to handle several important issues in WSN communication, includingenergy efficiency, latency, congestion, dynamic traffic load, and security. We present severalnovel mechanisms to improve the security and energy efficiency of WSNs. Two new schemes areproposed for the network layer stack to achieve the following: (a) to enhance energy efficiencythrough optimized sleep intervals, that also considers the underlying dynamic traffic load and (b)to develop the routing protocol in order to handle wasted energy, congestion, and clustering. Wealso propose efficient routing and energy-efficient clustering algorithms based on optimization andgame theory. Furthermore, we propose a dynamic game theoretic framework (i.e., hyper defense)to analyze the interactions between attacker and defender as a non-cooperative security game thatconsiders the resource limitation. All the proposed schemes are validated by extensive experimentalanalyses, obtained by running simulations depicting various situations in WSNs in orderto represent real-world scenarios as realistically as possible. The results show that the proposedschemes achieve high performance in different terms, such as network lifetime, compared with thestate-of-the-art schemes.
Show less
Date Issued
2018
Identifier
CFE0006971, ucf:51672
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006971
Quantifying Trust and Reputation for Defense against Adversaries in Multi-Channel Dynamic Spectrum Access Networks
Title
Quantifying Trust and Reputation for Defense against Adversaries in Multi-Channel Dynamic Spectrum Access Networks.
Creator
Bhattacharjee, Shameek, Chatterjee, Mainak, Guha, Ratan, Zou, Changchun, Turgut, Damla, Catbas, Necati, University of Central Florida
Abstract / Description
Dynamic spectrum access enabled by cognitive radio networks are envisioned to drivethe next generation wireless networks that can increase spectrum utility by opportunisticallyaccessing unused spectrum. Due to the policy constraint that there could be no interferenceto the primary (licensed) users, secondary cognitive radios have to continuously sense forprimary transmissions. Typically, sensing reports from multiple cognitive radios are fusedas stand-alone observations are prone to errors...
Show moreDynamic spectrum access enabled by cognitive radio networks are envisioned to drivethe next generation wireless networks that can increase spectrum utility by opportunisticallyaccessing unused spectrum. Due to the policy constraint that there could be no interferenceto the primary (licensed) users, secondary cognitive radios have to continuously sense forprimary transmissions. Typically, sensing reports from multiple cognitive radios are fusedas stand-alone observations are prone to errors due to wireless channel characteristics. Suchdependence on cooperative spectrum sensing is vulnerable to attacks such as SecondarySpectrum Data Falsification (SSDF) attacks when multiple malicious or selfish radios falsifythe spectrum reports. Hence, there is a need to quantify the trustworthiness of radios thatshare spectrum sensing reports and devise malicious node identification and robust fusionschemes that would lead to correct inference about spectrum usage.In this work, we propose an anomaly monitoring technique that can effectively cap-ture anomalies in the spectrum sensing reports shared by individual cognitive radios duringcooperative spectrum sensing in a multi-channel distributed network. Such anomalies areused as evidence to compute the trustworthiness of a radio by its neighbours. The proposedanomaly monitoring technique works for any density of malicious nodes and for any physicalenvironment. We propose an optimistic trust heuristic for a system with a normal risk attitude and show that it can be approximated as a beta distribution. For a more conservativesystem, we propose a multinomial Dirichlet distribution based conservative trust framework,where Josang's Belief model is used to resolve any uncertainty in information that mightarise during anomaly monitoring. Using a machine learning approach, we identify maliciousnodes with a high degree of certainty regardless of their aggressiveness and variations intro-duced by the pathloss environment. We also propose extensions to the anomaly monitoringtechnique that facilitate learning about strategies employed by malicious nodes and alsoutilize the misleading information they provide. We also devise strategies to defend against a collaborative SSDF attack that islaunched by a coalition of selfish nodes. Since, defense against such collaborative attacks isdifficult with popularly used voting based inference models or node centric isolation techniques, we propose a channel centric Bayesian inference approach that indicates how much the collective decision on a channels occupancy inference can be trusted. Based on the measured observations over time, we estimate the parameters of the hypothesis of anomalous andnon-anomalous events using a multinomial Bayesian based inference. We quantitatively define the trustworthiness of a channel inference as the difference between the posterior beliefsassociated with anomalous and non-anomalous events. The posterior beliefs are updated based on a weighted average of the prior information on the belief itself and the recently observed data.Subsequently, we propose robust fusion models which utilize the trusts of the nodes to improve the accuracy of the cooperative spectrum sensing decisions. In particular, we propose three fusion models: (i) optimistic trust based fusion, (ii) conservative trust based fusion, and (iii) inversion based fusion. The former two approaches exclude untrustworthy sensing reports for fusion, while the last approach utilizes misleading information. Allschemes are analyzed under various attack strategies. We propose an asymmetric weightedmoving average based trust management scheme that quickly identifies on-off SSDF attacks and prevents quick trust redemption when such nodes revert back to temporal honest behavior. We also provide insights on what attack strategies are more effective from the adversaries' perspective.Through extensive simulation experiments we show that the trust models are effective in identifying malicious nodes with a high degree of certainty under variety of network and radio conditions. We show high true negative detection rates even when multiple malicious nodes launch collaborative attacks which is an improvement over existing voting based exclusion and entropy divergence techniques. We also show that we are able to improve the accuracy of fusion decisions compared to other popular fusion techniques. Trust based fusion schemes show worst case decision error rates of 5% while inversion based fusion show 4% as opposed majority voting schemes that have 18% error rate. We also show that the proposed channel centric Bayesian inference based trust model is able to distinguish between attacked and non-attacked channels for both static and dynamic collaborative attacks. We are also able to show that attacked channels have significantly lower trust values than channels that are not(-) a metric that can be used by nodes to rank the quality of inference on channels.
Show less
Date Issued
2015
Identifier
CFE0005764, ucf:50081
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005764