Search

Unutilized spectra, i.e., spectrum holes, are opportunities that may be used for communication or adapting other services that use radio frequency (RF). Such opportunities can also represent an adversarial target, if his objective is to block the RF system from using such opportunities opened by spectrum holes. In this paper, we explore the challenge of finding spectrum holes in an adversarial environment. First , by means of a simple model, we show that an adversary’s attack designed to close spectrum holes can be more harmful for the spectrum holes than just random jamming. This calls for designing a scanning strategy to detect such an attack. Second , by applying a game-theoretical model, we design the optimal scanning strategy to detect such attacks. In particular, we show the efficiency of such a scanning strategy compared with uninformed random scanning. This efficiency is achieved by focusing scanning efforts on the bands that will be more likely under attack, and neglecting less promising bands. Beyond the benefits, though, such a strategy has also drawbacks since, if the adversary has a different objective, such as sneaking usage of the spectrum, he can sneak usage undetected by using the bands neglected by such specially tuned scanning. To deal with this problem, third , we suggest to combine this strategy with a strategy that maximizes detection probability in a learning algorithm that updates the beliefs about the adversary’s objective. The convergence of the combined algorithm is proven.

Journal of Cybersecurity and Privacy is critical to society at large, and its importance is growing daily. The rapid advancement in technology has caused a large-scale integration of computing, communication, and information technologies into virtually every aspect of our modern society[...]

Treatments consisting of mixtures of pharmacological agents have been shown to have superior effects to treatments involving single compounds. Given the vast amount of possible combinations involving multiple drugs and the restrictions in time and resources required to test all such combinations in vitro, mathematical methods are essential to model the interactive behavior of the drug mixture and the target, ultimately allowing one to better predict the outcome of the combination. In this review, we investigate various mathematical methods that model combination therapies. This survey includes the methods that focus on predicting the outcome of drug combinations with respect to synergism and antagonism, as well as the methods that explore the dynamics of combination therapy and its role in combating drug resistance. This comprehensive investigation of the mathematical methods includes models that employ pharmacodynamics equations, those that rely on signaling and how the underlying chemical networks are affected by the topological structure of the target proteins, and models that are based on stochastic models for evolutionary dynamics. Additionally, this article reviews computational methods including mathematical algorithms, machine learning, and search algorithms that can identify promising combinations of drug compounds. A description of existing data and software resources is provided that can support investigations in drug combination therapies. Finally, the article concludes with a summary of future directions for investigation by the research community.

Wireless networks are susceptible to malicious attacks, especially those involving jamming and eavesdropping. To maintain secure and reliable communication under such threats, different anti-adversary strategies have been proposed to mitigate the adversary impact. In this paper, we consider a sophisticated adversary with the dual capability of either eavesdropping passively or jamming any ongoing transmission, and investigate a new aspect to consider when designing an anti-adversary strategy: how uncertainty about whether the rival is rational or subjective could impact the strategies. To model such uncertainty, we formulate a Bayesian Prospect Theory (BPT) extension of the game between a user and an adversary who chooses between an eavesdropping attack and a jamming attack against the user. Meanwhile the user chooses against which of the threats to apply the corresponding best response strategy. Uniqueness of the BPT equilibrium strategies is proven and they are found in closed form.

Mobile ad hoc networks face many challenges when they are deployed, particularly problems associated with security and network failures arising from the dynamics of their network topologies. To address these issues, there have been many efforts to introduce security into the actual network protocols, most of which unfortunately struggle with the trade-off between security and network overhead. Consequently, it is often desirable to have a lightweight approach to introduce security and robustness, where one employs conventional and well-understood network protocols, and attempts to achieve the assurability of the network through higher-layer, overlay mechanisms. This paper explores a lightweight overlay tunneling scheme operating at the Internet protocol layer as a policy tool that can mitigate network failures and attacks directed at the network without involving the redesign of the underlying routing protocols. Moreover, two optimizations are proposed that lead to improved performance when additional information is available. Copyright © 2016 John Wiley & Sons, Ltd.

When an adversary illicitly uses spectrum that it is not authorized for, it does so with a purpose in mind, such as to download a file or perhaps engage in a real-time communication session. In this paper, we examine how the incorporation of knowledge related to an adversary’s purpose can improve the effectiveness of spectrum scanning protocols. First, we study the difference in the thief’s behavior when considering throughput and delay as the two primary QoS parameters he is concerned with. Through our analysis, we show that the detection probability of unlicensed access to spectrum resources depends on the application type. Knowledge of the application type can be incorporated to spectrum scanning to tune better it to detect the thief. To illustrate this, we examine two Bayesian games. In the first game, the scanner wants to minimize the time needed to detect the invader. In the second game, the scanner wants to maximize the detection probability at each time slot by adapting its belief regarding the adversary’s activity. In particular, it is shown in the minimizing detection time game that the equilibrium strategies are continuous with respect to priori knowledge of the invader’s activity. Meanwhile, for the maximizing detection probability game, the strategies can have a jump discontinuity. This phenomena can be explained as the difference between tactical and strategic decision making: tactical decision making allows short-term, unpredictable moves, while strategic decision making is inclined to predictable moves. Finally, since the bandwidth model used in this paper is general, the conclusion as well as the approach provided can be applied to a variety of different network protection problems.

In this paper, we suggest a new class of anti-jamming problems where the type of intelligence associated with a jamming attack is unknown. Specifically, we consider a problem where the nodes of a peer-to-peer network do not know whether the network is under attack by a random jammer (which might be considered as a natural background noise), or an intelligent one (i.e., the jammer who can adapt his strategy based on knowledge gained during attacks). The goal of the nodes is to identify the type of the attack based on knowledge obtained from the attack in previous time slots, and thereby to reduce the efficiency of the jamming attack. First, we model the problem as a Bayesian game for a single time slot attack, and reduce it to the solution of dual linear programming (LP) problems. Additionally, the convergence of the fictitious play algorithm for finding the equilibrium is established. Then, we develop the problem for a repeated jamming attack, where the nodes adapt their beliefs based on history of the previous attacks. In particular, we have shown that it is possible for the nodes in the network to always be able to identify the jammer’s type within a finite number of time slots.

There has recently been significant interest in applying the principles of information-theoretical security and signal processing to secure physical layer systems. Although the community has made progress in understanding how the physical layer can support confidentiality and authentication, it is important to realize that there are many important issues that must be addressed if physical layer security is ever to be adopted by real and practical security systems. In this article, I briefly review several different flavors of physical layer security (at least for wireless systems), and then identify aspects (a.k.a. weaknesses) where the foundation for physical layer security needs to be strengthened. I then highlight that the opportunities for applying physical layer security to real systems will be quite rich if the community can overcome these challenges. In the course of the article, I note new directions for the community to investigate, with the objective of keeping physical layer security research targeted at having a practical impact on real systems.

The reliable coordination of communication channels between two organizations is becoming an increasingly important problem as we move toward cognitive radio systems that support dynamic spectrum access. The benefit of such coordination is clear in scenarios when both participants are completely benign, but such benefits can be easily negated if one of the participants operates in a manner contrary to their channel assignment. In this paper, we develop and explore a maxmin transmission protocol for a primary user (PU) in a multiband wireless network, where the secondary user (SU) may be malicious and have an intent to cause interference. In this case, the threat that a SU may be an adversary changes the problem and places the PU in a dilemma: 1) if the SU is an adversary then to decrease the probability of interference it is better for the PU to select which channels it uses from a larger set of bands (i.e., possibly even including the bands reserved for the SU) and 2) if the SU turns out to be law obedient, then using a larger set of bands leads to an increased chance of being interfered with. Similarly, the SU also faces a dilemma if he is malicious: if the PU thinks that the SU is law obedient, then to increase the probability of jamming, the SU should target only the bands reserved for the PU; while, if the PU thinks that the SU is malicious, then by switching to the bands reserved for the SU, the probability of interference can be significantly or even totally reduced. Using game-theoretical tools, we formally explore these dilemmas and use the resulting analysis to explore the tradeoffs between different strategies in terms of payoffs to each user and knowledge of the SU’s characteristics.

The vast scale of the Internet of Things (IoT), combined with its heterogeneous nature involving many different types of devices and machines, could lead the IoT to be vulnerable to a variety of security threats and malicious attacks. Addressing the broad array of threats requires that different security mechanisms are deployed at appropriate locations within the broader IoT communication network. In this paper, we examine this problem by applying a resource allocation approach involving a game-theoretical framework to model: (a) an attack aimed to maximize total damage to the network, and (b) an attack aimed to compromise at least one of the devices. To evaluate the probability of a successful attack we apply a contest success function, and found the associated equilibrium strategies in closed form. Additionally, we note an interesting relationship between equilibrium strategies in security reinforcement games and OFDM transmission games under hostile jamming. A criteria is designed that allows one to determine whether an IoT controller’s resources is sufficient to protect all of the IoT devices it manages.

Many new "networkable" devices, which constitute the Internet of Things, are low energy and lightweight. These devices must devote most of their available energy and computation to executing core application functionality, making the task of affordably supporting security and privacy quite challenging.

Sharing of radio spectrum between different types of wireless systems (e.g., different service providers) is the foundation for making more efficient usage of spectrum. Cognitive radio technologies have spurred the design of spectrum servers that coordinate the sharing of spectrum between different wireless systems. These servers receive information regarding the needs of each system, and then provide instructions back to each system regarding the spectrum bands they may use. This sharing of information is complicated by the fact that these systems are often in competition with each other: each system desires to use as much of the spectrum as possible to support its users, and each system could learn and harm the bands of the other system. Three problems arise in such a spectrum-sharing problem: (1) how to maintain reliable performance for each system-shared resource (licensed spectrum); (2) whether to believe the resource requests announced by each agent; and (3) if they do not believe, how much effort should be devoted to inspecting spectrum so as to prevent possible malicious activity. Since this problem can arise for a variety of wireless systems, we present an abstract formulation in which the agents or spectrum server introduces obfuscation in the resource assignment to maintain reliability. We derive a closed form expression for the expected damage that can arise from possible malicious activity, and using this formula we find a tradeoff between the amount of extra decoys that must be used in order to support higher communication fidelity against potential interference, and the cost of maintaining this reliability. Then, we examine a scenario where a smart adversary may also use obfuscation itself, and formulate the scenario as a signaling game, which can be solved by applying a classical iterative forward-induction algorithm. For an important particular case, the game is solved in a closed form, which gives conditions for deciding whether an agent can be trusted, or whether its request should be inspected and how intensely it should be inspected.

The Internet of Things (IoT) is a recent trend that extends the boundary of the Internet to include a wide variety of computing devices. Connecting many stand-alone IoT systems through the Internet introduces many challenges, with security being front-and-center since much of the collected information will be exposed to a wide and often unknown audience. Unfortunately, due to the intrinsic capability limits of low-end IoT devices, which account for a majority of the IoT end hosts, many traditional security methods cannot be applied to secure IoT systems, which open a door for attacks and exploits directed both against IoT services and the broader Internet. This paper addresses this issue by introducing a unified IoT framework based on the MobilityFirst future Internet architecture that explicitly focuses on supporting security for the IoT. Our design integrates local IoT systems into the global Internet without losing usability, interoperability and security protection. Specifically, we introduced an IoT middleware layer that connects heterogeneous hardware in local IoT systems to the global MobilityFirst network. We propose an IoT name resolution service (IoT-NRS) as a core component of the middleware layer, and develop a lightweight keying protocol that establishes trust between an IoT device and the IoT-NRS.

Unutilized spectrum, i.e. spectrum holes, are opportunities that may be used for communication or other RF services. In this paper, we explore adversarial attacks that reduce the size of spectrum holes by showing their advantage compared to a random jammer. Using a game-theoretical approach, we design an optimal scanning strategy that provides an increased probability of detecting such an attack. The advantage of our strategy is achieved by focusing scanning efforts on bands that are more likely to be attacked, and neglecting the others. However, such focused scanning is a disadvantage since, if the adversary has a different objective, he can safely sneak usage of the bands neglected by such a specially-tuned spectrum scanner. To deal with this problem, we also derive the optimal scanning allocation that balances between applying the anti-spectrum holes attack scanning strategy and scanning the neglected bands so as to prevent the possibility of the adversary using those bands without being detected.

Wireless networks are vulnerable to many malicious attacks, like active interference, due to the shared and open-access nature of the wireless medium. One difficulty in dealing with interference attacks is the lack of knowledge about whether the attack will be present or not. In this paper, we investigate how the lack of knowledge of whether jamming will or will not be used against an OFDM communication impacts the anti-jamming strategy one should use. Our model can be applied more generally to jamming attacks with a fixed frequency where, at each time slot, it is unknown whether the interference will be used or not. We have derived the equilibrium strategy in waterfilling form, and shown that the obtained solution includes as boundary cases two classical solutions in OFDM transmission for the case where there is no adversary, and the case where the adversary attacks with certainty. Uniqueness of the equilibrium strategies is proven, and an algorithm for finding the parameters of the waterfilling equations is developed. The efficiency of the algorithm is illustrated by numerical examples.

The articles in this special section is designed to provide a venue for state-of-the-art research being doing in how signal and information processing is advancing the field of information privacy.

Dynamic spectrum access has been proposed as a means to share scarce radio resources, and requires devices to follow protocols that access spectrum resources in a proper, disciplined manner. For a cognitive radio network to achieve this goal, spectrum policies and the ability to enforce them are necessary. Detection of an unauthorized (anomalous) usage is one of the critical issues in spectrum etiquette enforcement. In this paper, we present a network structure for dynamic spectrum access and formulate the anomalous usage detection problem using statistical significance testing. The detection problem investigated considers two cases, namely, the authorized (primary) transmitter is (i) mobile and (ii) fixed. We propose a detection scheme for each case by exploiting the spatial pattern of received signal energy across a network of sensors. Analytical models are formulated when the distribution of the energy measurements is given and, due to the intractability of the general problem, we present an algorithm using machine learning techniques to solve the general case when the statistics of the energy measurements are unknown. Our simulation results show that our approaches can effectively detect unauthorized spectrum usage with a detection probability above 0.9 while keeping the false alarm rate less than 0.1 when only one unauthorized radio is present, and the detection probability is even higher for more unauthorized radios.

While conventional cryptographic security mechanisms are essential to the overall problem of securing wireless networks, they do not directly leverage the unique properties of the wireless domain to address security threats. The wireless medium is a powerful source of domain-specific information that can complement and enhance traditional security mechanisms. In this article we argue that new security paradigms which exploit physical layer properties of the wireless medium, such as the rapid spatial, spectral, and temporal decorrelation properties of the radio channel, can enhance confidentiality and authentication services. We outline some basic constructions for these services, and then provide a case study for how such strategies can be integrated into a broader security framework for a wireless network.

Cybersecurity is critical to society at large, and its importance is growing daily. The rapid advancement in technology has caused a large-scale integration of computing, communication, and information technologies into virtually every aspect of our modern society[...]

Wireless sensor networks are typically deployed to monitor phenomena that vary over the spatial region the sensor network covers. The sensor readings may also be dual-used for additional purposes. In this paper, we propose to use the inherent spatial variability in physical phenomena, such as temperature or ambient acoustic energy, to support localization and position verification. We first present the problem of localization using general spatial information fields, and then, propose a theory for exploiting this spatial variability for localization. Our Spatial Correlation Weighting Mechanism (SCWM) uses spatial correlation across different phenomena to isolate an appropriate subset of environmental parameters for better location accuracy. We then develop an array of algorithms employing environmental parameters using a two-level approach: first, we develop the strategies on how the subset of parameters should be chosen, and second, we derive mapping functions for position estimation. Our algorithms support our theoretical model for performing localization utilizing environmental properties. Finally, we provide an experimental evaluation of our approach by using a collection of physical phenomena measured across 100 locations inside a building. Our results provide strong evidence of the viability of using general sensor readings for location-aware applications.

Wireless technologies have had a significant impact on computing and communication technologies in the past decade, and we are thus now progressing to the new "anytime-anywhere" service model of the mobile Internet. Unfortunately, the affordability and availability of wireless technologies that makes them so attractive, also makes them an enticing target for security threats. As new wireless technologies continue to emerge, many of which will be highly flexible and programmable (such as the next generation of software radios), it will be easier than ever before for adversaries to acquire the equipment and the means to launch new security or privacy attacks.

Location information should be verifiable in order to support new computing and information services. In this paper, we adapt the classical challenge-response method for authentication to the task of verifying an entity's location. Our scheme utilizes a collection of transmitters, and adapts the power allocations across these transmitters to verify a user's claimed location. This strategy, which we call a power-modulated challenge response, is able to be used with existing. wireless sensor networks. First, we propose a direct method, where some transmitters are selected to send ldquochallengesrdquo that the claimant node should be able to witness based on its claimed location, and for which the claimant node must correctly respond to in order to prove its location. Second, we reverse the strategy by presenting an indirect method, where some transmitters send challenges that the claimant node should not be able to witness. Then, we present a signal-strength-based method, where the node responds with its received signal strength and thereby provides improved location verification. To evaluate our schemes, we examine different adversarial models for the claimant, and characterize the performance of our power-modulated challenge response schemes under these adversarial models. Further, we propose a new localization attack, where a set of nodes collaborates to pretend that there is a node at the claimed location. This collusion attack can do tremendous harm to localization and the performance of the aforementined methods under collusion attack are explained. Finally, we propose the use of a rotational directional power-modulated challenge response, where directional antennas are used to defend against collusion attacks.

Vehicular ad hoc networks (VANETs) represent a promising new communication technology that can facilitate many new forms of automotive applications. Many of the applications that will run on these networks will require a high degree of security and privacy. In this paper, we present a robust and efficient security framework for vehicular networks suited for both inter-vehicular and vehicle-to-infrastructure communication. Our system uses identity-based cryptography (IBC) to provide authentication, confidentiality, non-repudiation, and message integrity. It exploits the implicit authentication provided by IBC to significantly reduce the security/privacy-related communication overhead. Additionally, it provides scalable, user-customizable security and privacy using short-lived, authenticated, and unforgeable, pseudonyms. This feature can be used by VANET applications that require quantifiable trust and privacy to provide differentiated service based on various levels of trust and privacy thresholds. Copyright © 2008 John Wiley & Sons, Ltd.

Emerging wireless systems will need to address multiple, conflicting objectives: ensuring the secrecy of the communication secrecy (i.e., maximizing the un-eavesdropped throughput at the receiver), and ensuring the “security” of the communication (i.e., minimizing damage that might arise because of the possibility that there is leakage in communication). This problem presents a dilemma for system engineers since the optimal solution for one of objective might be not optimal for the other. This dilemma calls for a need for designing a trade-off solution for these objectives. In this paper, we propose the use of a Kalai-Smorodinsky bargaining solution between secrecy and security for OFDM-style communications, which allows one to select the security level of communication. In particular, this solution allows one to maintain the ratios of maximal gains for cooperative fulfilment of both objectives.

Security is a fundamental problem facing wireless systems employing spectrum sharing, and thus scanning algorithms are used to detect malicious or illegal activity in such systems. A crucial issue in designing such algorithms is incorporating knowledge about the environment, as well as what knowledge an adversary might have, into the scanning algorithm to improve detection performance. In particular, if such knowledge is initially incomplete, it becomes desirable to adapt one's knowledge based upon the results of the scanning activities, so as to further improve detection performance. To obtain insight into this problem, we suggest a Bayesian game-theoretical model of bandwidth scanning with learning. We show that such knowledge could change the structure of the strategies employed from distributing effort among all the bands, to band-sharing or even band on/off strategies and improve detection performance. Also, we have shown that a lack of information for the scanner compare to the adversary makes the scanner strategy more sensitive to the information he has.

Jamming attacks are a class of network denial of service attacks that can easily be carried out in wireless networks. In order to be able to repair a network in the presence of such attacks, it is desirable to identify the location of jammed nodes and the congested area that is affected by the jammer. In this paper, we propose the design of a Q-learning based attack-localization algorithm that is integrated with the OLSR routing protocol. Our Q-learning attack-localization algorithm is distributed, asynchronous and can identify the location of the jammer in run-time as the attack takes place. We examine the performance of our approach using NS3 network simulations under two different network topologies, and for both naive and intelligent attack scenarios.

Detecting malicious users in dynamic spectrum access scenarios is a crucial problem that requires an intrusion detection system (IDS) that scans spectrum for malicious activities. In this paper we design a spectrum scanning protocol that incorporates knowledge about the scanning effectiveness across different bands, which can increase scanning efficiency. The adversary, however, can also exploit such knowledge to its advantage. To understand the interplay underlying this problem, we formulate a Bayesian model, where the IDS faces a scanning allocation dilemma: if the intruder has no knowledge, then all the bands are under equal threat, while if the intruder has complete knowledge, then less-protected bands are more likely to be threatened. We solve this dilemma and show the optimal IDS strategy switches between the optimal response to these threats. Finally, we show that the strategy might be sensitive to prior knowledge, which can be corrected by adapted learning.

Wireless sensor networks are built upon a shared medium that makes it easy for adversaries to conduct radio interference, or jamming, attacks that effectively cause a denial of service of either transmission or reception functionalities. These attacks can easily be accomplished by an adversary by either bypassing MAC-layer protocols or emitting a radio signal targeted at jamming a particular channel. In this article we survey different jamming attacks that may be employed against a sensor network. In order to cope with the problem of jamming, we discuss a two-phase strategy involving the diagnosis of the attack, followed by a suitable defense strategy. We highlight the challenges associated with detecting jamming. To cope with jamming, we propose two different but complementary approaches. One approach is to simply retreat from the interferer which may be accomplished by either spectral evasion (channel surfing) or spatial evasion (spatial retreats). The second approach aims to compete more actively with the interferer by adjusting resources, such as power levels and communication coding, to achieve communication in the presence of the jammer.

Digital fingerprinting is a method for protecting digital data in which fingerprints that are embedded in multimedia are capable of identifying unauthorized use of digital content. A powerful attack that can be employed to reduce this tracing capability is collusion, where several users combine their copies of the same content to attenuate/remove the original fingerprints. In this paper, we study the collusion resistance of a fingerprinting system employing Gaussian distributed fingerprints and orthogonal modulation. We introduce the maximum detector and the thresholding detector for colluder identification. We then analyze the collusion resistance of a system to the averaging collusion attack for the performance criteria represented by the probability of a false negative and the probability of a false positive. Lower and upper bounds for the maximum number of colluders K/sub max/ are derived. We then show that the detectors are robust to different collusion attacks. We further study different sets of performance criteria, and our results indicate that attacks based on a few dozen independent copies can confound such a fingerprinting system. We also propose a likelihood-based approach to estimate the number of colluders. Finally, we demonstrate the performance for detecting colluders through experiments using real images.

The problem of controlling access to multimedia multicasts requires the distribution and maintenance of keying information. Typically, the problem of key management is considered separately from the problem of distributing the rekeying messages. Multimedia sources provide two approaches to distributing the rekeying messages associated with securing group communication. The first, and more conventional approach employs the use of a media-independent channel to convey rekeying messages. We propose, however, a second approach that involves the use of a media-dependent channel, and is achieved for multimedia by using data embedding techniques. Compared to a media-independent channel, the use of data embedding to convey rekeying messages provides enhanced security by masking the presence of rekeying operations. This covert communication makes it difficult for an adversary to gather information regarding the group membership and its dynamics. In addition to proposing a new mode of conveyance for the rekeying messages, we introduce a new message format that is suitable for multicast key management schemes. This new message format uses one-way functions to securely distribute new key material to subgroups of users. An advantage of this approach over the traditional message format is that no additional messages must be sent to flag the users which portion of the message is intended for them, thereby reducing communication overhead. We then show how to map the message to a tree structure in order to achieve desirable scalability in communication and computational overhead. Next, as an example of the interplay between the key management scheme and the mode of conveyance, we study the feasibility of embedding rekeying messages using a data embedding method that has been recently proposed for fractional-pel video coding standards such as H.263 and MPEG-2. Finally, since multimedia services will involve multiple layers or objects, we extend the tree-based key management schemes to include new operations needed to handle multilayer multimedia applications where group members may subscribe or cancel membership to some layers while maintaining membership to other layers.

Digital fingerprinting is a technique for identifying users who use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are combined to disrupt the underlying fingerprints. We investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the effect that averaging collusion has on orthogonal modulation. We introduce a tree-structured detection algorithm for identifying the fingerprints associated with K colluders that requires O(Klog(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based on code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACCs), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-off keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only O(/spl radic/n) orthogonal signals for a given number of colluders. We introduce three different detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate the performance of our ACC for fingerprinting multimedia and identifying colluders through experiments using Gaussian signals and real images.

Fairness plays an important role in networking as it fundamentally describes how different communication participants access and share network resources. The fair sharing of resources becomes complicated when the network faces harsh operational conditions, which may be associated with mutual interference or adversarial conditions. In this paper, we study the problem of fair allocation of resources in a network facing harsh operational conditions associated with communication transmission. Such a problem is becoming increasingly relevant in wireless system design as multiple wireless technologies are being deployed in shared spectrum, e.g. WiFi and LTE-U, and wireless networks are facing unprecedented levels of malicious activities. To obtain insight into this problem we suggest a simple game theoretical model involving resource allocation. We solve the game explicitly, which allows us to explore the structure of resource allocation strategies, and thereby provide guidance into the integration of fair resource allocation in networks.

The lack of access control and regulation in the current Internet has resulted in many security and privacy problems. To prevent unauthorized access to protected information, integrating access control into future Internet design is crucial. In this paper, a suite of access control mechanisms that are well-suited for the mobile Internet are introduced. We employ a representative future Internet architecture that is currently being developed as a part of a clean slate design effort. The emphasis of the proposed methods is on supporting new spatio-temporal access control, which can be a powerful new paradigm for security in mobile systems.

We propose a distributed scheme by which nodes select an appropriate access point to associate with using each individual device's channel utilization. Specifically, we define a new metric, channel utilization, which is defined as the ratio of required bandwidth to available bandwidth estimation. By incorporating channel utilization into the access point selection protocol, we effectively reduce unnecessary reassociations and improve upper layer performance in terms of throughput, packet delivery delay, etc. We further enhance our protocol by using reinforcement learning to adapt the scheduling of probing neighboring access points (APs), ultimately reducing probing overhead by learning from past experience whether the current operational scenario would suffer from undesirable overhead. When channel utilization is combined with adaptive probing, we observed a significant performance improvement compared to traditional association approaches.

We provide a brief overview of identity-based spoofing attack, and its impact to the wireless and sensor networks in this chapter.

User spoofing has a serious impact to the normal operation of wireless and sensor networks. It is thus desirable to detect the presence of identity-based attacks and eliminate them from the network. The traditional approach to address identity-based attacks is to apply cryptographic authentication. However, authentication requires additional infrastructural overhead and computational power associated with distributing, and maintaining cryptographic keys. Due to the limited power and resources available to the wireless devices and sensor nodes, it is not always possible to deploy authentication. In this chapter, we take a different approach by using the physical properties associated with wireless transmissions to detect identity-based attacks. Specifically, we utilizes the Received Signal Strength (RSS) measured across a set of landmarks (i.e., reference points with known locations) to perform detection of identity-based attacks. In this chapter, we focus on static nodes, which are common for most identity-based attacks scenarios (Sheng et al., Detecting 802.11 MAC layer spoofing using received signal strength, in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), April 2008). Our scheme does not add any overhead to the wireless devices and sensor nodes.

Under a malicious spoofing attack, multiple adversaries may masquerade as the same identity and collaborate to launch a denial-of-service attack quickly. Therefore, it is important to further determine the number of attackers that masquerade as the same identity in the wireless network. Further, detecting the presence of identity-based attacks in the network provides first order information towards defending against attackers. Learning the physical location of the attackers allows the network administrators to further exploit a wide range of defense strategies. For example, we can physically visit multiple adversaries and eliminate it from the network. We then explore how to find the positions of the adversaries by integrating our attack detector into a real-time indoor localization system.

We study how secret communication can be effected by the fact that an adversary’s capability to eavesdrop on a collection of communications from a base station to a set of users may be restricted and unknown to the transmitter. In this situation, the eavesdropping adversary might have to choose which user to eavesdrop upon if it cannot eavesdrop upon the full set. Thus, the transmitter must make a decision on how to better maintain secret communication, and to do this it must take into account that the eavesdropper might possibly be passive or could be an active adversary that must actively make a choice about which user to eavesdrop upon. Using an example of a Bayesian game-theoretical model with unknown eavesdropping capacity we show why it is important to incorporate in a secret transmission protocol the possibility of an eavesdropper having restricted eavesdropping capacity. Also, since the equilibrium strategies are obtained explicitly, we establish some interesting properties that can guide deployment of such a system.

Attacks involving identity fraud can facilitate a variety of advanced attacks to significantly impact the normal operation of wireless networks (F. Ferreri, M. Bernaschi, and L. Valcamonici, “Access points vulnerabilities to dos attacks in 802.11 networks,” in Proceedings of the IEEE Wireless Communications and Networking Conference, 2004; J. Bellardo and S. Savage, “802.11 denial-of-service attacks: Real vulnerabilities and practical solutions,” in Proceedings of the USENIX Security Symposium, 2003, pp. 15–28; D. Faria and D. Cheriton, “Detecting identity-based attacks in wireless networks using signalprints,” in Proceedings of the ACM Workshop on Wireless Security (WiSe), September 2006; Q. Li andW. Trappe, “Relationship-based detection of spoofing-related anomalous traffic in ad hoc networks,” in Proceedings of the Third Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), September 2006). Identity fraud performed by mobile wireless devices may further inflict security and privacy damages on the social life of the individual who carries wireless devices. We call these kind of attacks as mobile spoofing attacks. There has been active work in detecting spoofing attacks (D. Faria and D. Cheriton, “Detecting identity-based attacks in wireless networks using signalprints,” in Proceedings of the ACM Workshop on Wireless Security (WiSe), September 2006; Y. Chen, W. Trappe, and R. P. Martin, “Detecting and localizing wirelss spoofing attacks,” in Proceedings of the Fourth Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), May 2007. (Acceptance rate: 20%); Y. Sheng, K. Tan, G. Chen, D. Kotz, and A. Campbell, “Detecting 802.11 MAC layer spoofing using received signal strength,” in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), April 2008). D. Faria and D. Cheriton, (“Detecting identity-based attacks in wireless networks using signalprints,” in Proceedings of the ACM Workshop on Wireless Security (WiSe), September 2006) proposed the use of matching rules of Received Signal Strength (RSS) for spoofing detection, (Y. Chen, W. Trappe, and R. P. Martin, “Detecting and localizing wirelss spoofing attacks,” in Proceedings of the Fourth Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), May 2007. used K-means cluster analysis of RSS, and (Y. Sheng, K. Tan, G. Chen, D. Kotz, and A. Campbell, “Detecting 802.11 MAC layer spoofing using received signal strength,” in Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), April 2008.) modeled RSS readings as a Gaussian mixture model to capture antenna diversity. However, these mechanisms only work in static wireless environments, i.e., the victim node has a fixed location. In this chapter, we focus on spoofing attack detection in mobile wireless environments, that is, the wireless devices including the victim node and/or the spoofing node are moving around. Thus, detecting identity fraud launched by mobile agents is important as it allows the network to further exploit a wide range of defense strategies in different network layers, and consequently helps to ensure secure and trustworthy communication in emerging mobile pervasive computing.

Physical layer secret communication is evaluated by the secrecy rate/capacity, which loosely is the Alice-Bob communication rate minus the Alice-Eve communication rate. Eve’s objective is to reduce the secrecy rate and typically this is accomplished by eavesdropping, but it also can be accomplished by Eve directing interference at Bob, reducing the Alice-Bob channel rate. We examine secret communication from Eve’s perspective, where she can either eavesdrop or jam, but not both simultaneously. There are costs and advantages associated with these two options, and to explore the selection between these two options, we apply a game-theoretical approach. We find the equilibrium strategies for two scenarios: (a) Alice and Eve have to decide the probability for which each can apply On/Off power strategies in choosing between eavesdropping and jamming options, (b) Alice and Eve tune transmission/jamming powers and Eve chooses either a single-level or bi-level mode for interfering with the Alice-Bob communication. We show in the tuned-power scenario that Eve prefers either pure jamming or a mixed strategy over pure eavesdropping. We show the concave dependence of Eve’s payoff on the eavesdropping fading channel gain. Surprisingly, we find that both Eve and Alice-Bob can benefit for a small range of eavesdropping channel gains when Eve switches from pure jamming to a mixed strategy.

Transferring the role of leadership between members of a team is an important requirement in tactical operations as it allows an operation to continue in spite of unforeseen events. Delegation, at first glance, appears to be the simple act of giving someone else a right that one possesses. However, this basic function is challenging to implement electronically, and thus there is a need for mechanisms to enforce flexible delegation policies in distributed systems. It has been shown that Law Governed Interaction (LGI) can address these challenges based on the assumption of the trustworthiness of its own enforcement infrastructure. However, to meet the needs of tactical missions, the proposed mechanism should also be resilient to the Byzantine compromise of the infrastructure. Therefore, in this paper we extend the original LGI model to provide containment, guaranteeing that a single Byzantine agent cannot compromise the properties of the system and in general, our approach can withstand the presence of multiple Byzantine agents as long as a correlated pair of agents is not corrupt.

In this paper we investigate the problem of designing a spectrum scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem we apply game-theoretical tools. We model the situation as a game between a Scanner and an Invader where the Invader faces a dilemma: the more bandwidth the Invader attempts to use leads to a larger payoff if he is not detected, but at the same time also increases the probability of being detected and thus fined. Similarly, the Scanner faces a dilemma: the wider the bandwidth scanned, the higher the probability of detecting the Invader, but at the expense of increasing the cost of building the scanning system. The equilibrium strategies are found explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the type of the Invader's award. This discontinuity on fine means that the network provider has to take into account a human factor since some threshold values of fine could be very sensible for the Invader, while in other situations simply increasing the fine has minimal deterrence impact. Also we show how different reward types for the Invader (e.g. motivated by using different type of application, say, video-streaming or downloading files) can be incorporated into scanning strategy to increase its efficiency.

A recent trend in clean-slate network design has been to separate the role of identifiers from network locators. An essential component to such a separation is the ability to resolve names into network addresses. One challenge facing name resolution is securing the name resolution service. This paper examines the security of a clean-slate name resolution service suitable for mobile networking. We begin with a high-level threat analysis, and identify several types of attacks that may be used against name resolution services. We then present secure protocols that together form a secure global name resolution service. Specifically, we present a secure update protocol that allows users to update their network addresses as they migrate and that includes several checkpoints that prevents spoofing, collusion, stale identifiers and false identifier announcements. Since the primary function behind a name resolution service is to respond to address-lookup queries, we also present a secure query protocol. Finally, we address the security risks associated with IP holes that can arise in a global name resolution service.

We consider the game where Alice wants to communicate with Bob secretely, while Eve wants to hinder this objective by either eavesdropping or jamming, though she cannot employ both eavesdropping and jamming simultaneously. Alice is employing a multi-channel communication scheme, such as OFDM, and can control the transmit power allocation of her signal among the channels. If Eve chooses to jam, she can control her jamming power allocation amongst the channels, but in this case cannot eavesdrop. In this paper we examine three different patterns for Alice's (and Eve's) behavior: (a) Alice assumes Eve employs either a pure jamming or eavesdropping strategy and determines her optimal mixed strategy under this assumption; (b) assuming a fixed probability with which Eve will jam/eavesdrop, Alice/Eve's equilibrium power allocation strategies can be determined, and then Eve chooses the probability that maximizes her payoff; (c) Eve chooses between two modes (either to jam or eavesdrop) as well as power allocations simultaneous with Alice's selection of power allocation. Using a game-theoretic formulation, the equilibrium strategies are found for each model and conditions where players apply mixed strategies are produced.

We describe a decentralized peer-to-peer online secondary spectrum marketplace, where consumers can trade exclusive access rights to a specific portion of the spectrum (designated by geographic location, frequency band and time period) in return for fee payment, under the constraint of obeying the trading rules formulated by the government. The main advantage of such an innovative secondary spectrum marketplace over the current state of the art is that it reduces the complexity of spectrum management by removing governmental agencies from being directly involved in the completion of such transactions. The proposed model allows spectrum consumers to sell, lease or transfer the access rights to a chunk of spectrum by disaggregating, partitioning or time-sharing the corresponding spectrum in their possession. Further, we also outline an architecture in which such exclusive access rights to a portion of the spectrum could be used to regulate radio device transmission to enable proactive enforcement of the spectrum usage policies and to deter unauthorized transmissions. Overall our secondary spectrum marketplace model has the potential to reduce cost, increase spectrum efficiency, and to simplify the task of spectrum management.

In this paper, we examine the problem of identifying different association protocols based on client probing patterns. We take the view point of an attacker, who aims to trick certain clients to switch their association to a compromised AP, so that the attacker can easily perform various attacks, such as passing false management frames and stealing client information. In order to do that, the attacker must know what association protocol the client is using since it determines the clients switching criteria. Therefore, the attacker must be able to identify the association protocol by monitoring the network traffic. We investigated methods to identify four association protocols and propose an approach which combines k-means clustering and Gaussian fitting to classify the association protocols based on probing patterns. We tested the designed scheme on traffic traces for a variety of network scenarios. We also designed a method to quantify the likelihood of the identification using confidence intervals. Results show that the proposed method can correctly identify association protocols. Further interpretation of the results also reveals information regarding important metrics of the clients chosen association protocol.

Technological advancements have made it possible to use information associated with a mobile's location to form new computing and services. One concern with these emerging location-based services (LBS) is their ability to provide security while remaining reliable and accurate. In this paper, we focus on securing Mobile Location-based Services (MLBS), where certain goods or services are provided by mobile vendors to a clientele based on the proximity of vendors to potential customers. We identify different attacks and misuse faced by MLBS, and show that position verification is a critical step in providing a secure and trustworthy MLBS. To provide position verification, we propose a scheme called Key Distribution-based Position Verification (KEPI), which takes advantage of an auxiliary network of transponders to facilitate trustworthy location-based services. We derive an analytical model to evaluate our approach and our simulation results provide useful insights about how auxiliary networks can help provide trustworthy mobile services.