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We consider a single carrier communication system subjected to multi-jammer interference, and study optimal power control in the framework of game theory. The Nash and Stackelberg equilibria are derived in closed form. Conditions involving the background noise variance and the transmission cost are established for determining whether the equilibria are unique. It is proven that in the case of multiple equilibria, the user has the same payoff at each equilibrium, which reflects the stability of the communication. Also, consistent with the literature on single-jammer scenarios, it is shown that when the jammers are in a Stackelberg game, although they act as followers, they gain in payoffs as compared to the Nash game.

We consider the communication between a source (user) and a receiver in the presence of multiple jammers, and study resource assignment in a non-cooperative game theory framework using communication latency as the user's utility. Equilibrium strategies are found in closed form, and their uniqueness is proven. This allows one to identify jammers whose equilibrium strategies have an on/off structure, or they are sensitive to small variations in the network parameters.

We consider the communication between a source (user) and a destination in the presence of a jammer, and study resource assignment in a non-cooperative game theory framework. A player (the user or the jammer) has incomplete information about its rival’s identity in the form of uncertainty; the player only knows the probabilities that its rival is a player implementing a behavioral strategy as a follower in a Stackelberg game (smart-type), or selects a feasible strategy as in a Nash game (regular-type). We model the problem as two Bayesian games. In the first game, the user has incomplete information about the jammer, and in the second game, the jammer has incomplete information about the user. The user’s utility is throughput. We prove that a unique equilibrium exists and derive it in closed form as a function of the known probabilities. We show that the Nash and Stackelberg equilibria are boundary cases of the obtained equilibrium. Thus, our approach allows one to incorporate the Nash and Stackelberg equilibria into a unified scale of equilibria. Monotonicity properties of the equilibrium strategies and the corresponding payoffs with respect to the network parameters are proven, and also supported by simulations.

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.

Underlay is an aggressive spectrum sharing paradigm that allows secondary nodes to be active simultaneously with the primary nodes through interference cancelation (IC). In this paper, we design an online admission control algorithm to handle dynamic session arrival and departure in the underlay coexistence paradigm for multi-hop primary and secondary networks. For IC, we employ multiple antennas at each secondary node. Through distributed computation and degree-of-freedom (DoF) allocation at each secondary node, our algorithm ensures that all interference to/from the multi-hop primary network and interference within the multi-hop secondary network are canceled properly so that data transport is free of interference in both multi-hop primary and secondary networks. Further, we show that the DoF allocation by our algorithm is feasible (implementable) at the physical layer at all time. Through extensive performance evaluation, we find that our online admission control algorithm can offer competitive performance when compared to an offline centralized algorithm.

Spectrum sharing enables radar and communication systems to share the spectrum efficiently by minimizing mutual interference. Recently proposed multiple-input multiple-output radars based on sparse sensing and matrix completion (MIMO-MC), in addition to reducing communication bandwidth and power as compared with MIMO radars, offer a significant advantage for spectrum sharing. The advantage stems from the way the sampling scheme at the radar receivers modulates the interference channel from the communication system transmitters, rendering it symbol dependent and reducing its row space. This makes it easier for the communication system to design its waveforms in an adaptive fashion so that it minimizes the interference to the radar subject to meeting rate and power constraints. Two methods are proposed. First, based on the knowledge of the radar sampling scheme, the communication system transmit covariance matrix is designed to minimize the effective interference power (EIP) at the radar receiver, while maintaining certain average capacity and transmit power for the communication system. Second, a joint design of the communication transmit covariance matrix and the MIMO-MC radar sampling scheme is proposed, which achieves even further EIP reduction.

We propose a distributed access point selection scheme by which nodes select an appropriate access point to associate with based upon each individual device's channel utilization. In this paper, we define channel utilization as the ratio of required bandwidth to estimated available bandwidth. By incorporating channel utilization into the access point selection protocol, we can effectively reduce unnecessary reassociations and improve upper layer performance such as throughput and packet delivery delay. We have further enhanced our association protocol by using reinforcement learning to dynamically schedule the probing of neighboring access points (APs), ultimately bringing down the probing overhead by learning from past experience. When channel utilization is combined with adaptive probing, we observe a significant performance improvement compared to traditional association approaches.

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.

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.

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.

Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

Multiple-input multiple-output (MIMO) technologies are a popular choice for emerging wireless systems due to their promised gains in throughput and reliability. In order to realize any gains over traditional non-MIMO communication systems, these systems must possess accurate knowledge of the wireless channel. In this paper, we investigate strategies for disrupting MIMO communications by developing attacks that target the often overlooked, but essential, channel estimation procedure. Our study focuses on the two most popular and well-known MIMO techniques: the capacity achieving SVD-based MIMO scheme, and the Alamouti space-time block code (STBC), which spans many protocols including 802.11n, WiMAX, and 3GPP. We augment theoretical and simulation results with real-world experimentation using the USRP/GNU Radio software defined radio platform. We also present novel methodology to protect the channel estimation procedure from such attacks by embedding authentication messages into physical layer features of the transmissions.

We describe a method for estimating achievable data rates in urban microcells using multiple-input/multiple-output (MIMO) techniques. Specifically, we use site maps and a versatile ray-tracing tool to compute MIMO gain matrices as a function of terminal location; and we use these matrices to determine achievable rates for various MIMO transmission modes (spatial multiplexing, beamforming, and diversity). Numerical results are generated for specific paths in Boston and Manhattan, though our results are shown to be fairly insensitive to neighborhood or city. We also show that, in urban microcells, data rate prediction using site-specific ray tracing is more informative than using stochastic models; and that adaptive switching among MIMO transmission modes as a terminal moves along its trajectory can help sustain high data rates. A new mode-switching algorithm is proposed that requires switching rates lower than those for the optimal scheme by a factor greater than 10, with little loss in average data rate. We also propose a novel software algorithm for optimally placing microcell bases. For a Manhattan neighborhood of area 0.5 km2, we find that full coverage can be obtained using only 5 bases, and that the highest total throughput is achieved using a frequency reuse factor of 1.

Sniffing encrypted data packets traveling across networks can often be useful in inferring nontrivial information about their contents because of the manner in which the transmission of such packets is handled by lower layers in the communications protocol stack. In this paper, we formally study the side-channel formed by variable packet sizes, and explore obfuscation approaches to prevent information leakage while jointly considering the practical cost of obfuscation. We show that randomized algorithms for obfuscation perform best and can be studied as well-known information-theoretic constructs, such as discrete channels with and without memory. We envision a separate layer called a Bit - Trap, that employs buffering and bit-padding as orthogonal methods for obfuscating such side channels. For streams of packets, we introduce the use of mutual-information rate as an appropriate metric for the level of obfuscation that captures nonlinear relationships between original and modified streams. Using buffering-delay and average bit-padding as the respective costs, a Bit - Trap formulates a constrained optimization problem with bounds on the average costs, to implement the best possible obfuscation policy. We find that combining small amounts of delay and padding together can create much more obfuscation than either approach alone, and that a simple convex trade-off exists between buffering delay and padding for a given level of obfuscation.

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.

We consider a secret communication scenario where Alice wants to transmit secretly to Bob in presence of a passive eavesdropper Eve. The Alice-Bob channel is a fixed-SNR AWGN channel, while the Alice-Eve channel is a fast Rayleigh fading channel, with the channel states only known to Eve. Alice knows the statistics of Alice-Eve channel, but not the exact realizations. We investigate the achievable secrecy rates for this channel model with Gaussian signaling and discrete signaling. For Gaussian signaling, several transmission strategies according to the main channel's relative channel gain are proposed and evaluated. For discrete signaling, achievable secrecy rates with Quadrature Amplitude Modulation (QAM) are evaluated. When Bob's channel is much better than Eve's channel, simple Gaussian signaling can perform close to the upper bound, and is better than the rate achieved with M-QAM. When Bob's channel gain is on average worse than the eavesdropper's average channel gain, positive secrecy rate can still be achieved for Gaussian signaling with artificial noise injection and a burst signaling strategy. Moreover, M-QAM can outperform Gaussian signaling. The key factor that enables secret communication in this case is that both M-QAM and artificial noise limit the leakage of information when Eve's channel is unusually good.

Wireless networks are vulnerable to identity-based attacks, including spoofing and Sybil attacks, which allows for many other forms of attacks on the networks. Although the identity of a node can be verified through cryptographic authentication, authentication is not always possible, because it requires key management and additional infrastructural overhead. In this paper, we propose a method for detecting both spoofing and Sybil attacks by using the same set of techniques. We first propose a generalized attack-detection model that utilizes the spatial correlation of received signal strength (RSS) inherited from wireless nodes. We further provide a theoretical analysis of our approach. We then derive the test statistics for detection of identity-based attacks by using the K-means algorithm. Our attack detector is robust when handling the situations of attackers that use different transmission power levels to attack the detection scheme. We further describe how we integrated our attack detector into a real-time indoor localization system, which can also localize the positions of the attackers. We show that the positions of the attackers can be localized using either area- or point-based localization algorithms with the same relative errors as in the normal case. We further evaluated our methods through experimentation in two real office buildings using both an IEEE 802.11 (WiFi) network and an IEEE 802.15.4 (ZigBee) network. Our results show that it is possible to detect wireless identity-based attacks with both a high detection rate and a low false-positive rate, thereby providing strong evidence of the effectiveness of the attack detector utilizing the spatial correlation of RSS and the attack localizer.

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.

Worldwide inter-operability for microwave access (WiMAX) is a promising technology that provides high data throughput with low delays for various user types and modes of operation. While much research had been conducted on physical and MAC layers, little attention has been paid to a comprehensive and efficient security solution for WiMAX. We propose a hybrid security solution combining identity-based cryptography (IBC) and certificate based approaches. We provide detailed message exchange steps in order to achieve a complete security that addresses the various kind of threats identified in previous research. While attaining this goal, efficient fusion of both techniques resulted in a 53% bandwidth improvement compared to the standard's approach, PKMv2. Also, in this hybrid approach, we have clarified the key revocation procedures and key lifetimes. Consequently, to the best of knowledge our approach is the first work that unites the advantages of both techniques for improved security while maintaining the low overhead for WiMAX.

The radio channel response decorrelates rapidly as the transmitter changes location in an environment with rich scatterers and reflectors. Based on this fact, a channel-based authentication scheme was previously proposed to discriminate between transmitters at different locations, and thus to detect spoofing attacks in wireless networks. In this paper, we study its application in frequency-selective Rayleigh channels, considering channel time variations due to environmental changes and terminal mobility, as well as the channel estimation errors due to the interference from other radios. We propose a generalized likelihood ratio test (GLRT) that is optimal but computationally cumbersome, and a simplified version that requires no a priori knowledge of channel parameters and is therefore more practical. We verify the efficacy of the channel-based spoofing detectors via numerical analysis, showing how performance is improved by using multiple antennas, higher transmit power, and wider system bandwidth. We show that, under a wide variety of practical conditions, spoofing can be detected with better than 90% probability while keeping the probability of falsely rejecting valid transmissions below 10%.

Due to the broadcast nature of the wireless medium, wireless networks are especially vulnerable to Sybil attacks, where a malicious node illegitimately claims a large number of identities and thus depletes system resources. We propose an enhanced physical-layer authentication scheme to detect Sybil attacks, exploiting the spatial variability of radio channels in environments with rich scattering, as is typical in indoor and urban environments. We build a hypothesis test to detect Sybil clients for both wideband and narrowband wireless systems, such as WiFi and WiMax systems. Based on the existing channel estimation mechanisms, our method can be easily implemented with low overhead, either independently or combined with other physical-layer security methods, e.g., spoofing attack detection. The performance of our Sybil detector is verified, via both a propagation modeling software and field measurements using a vector network analyzer, for typical indoor environments. Our evaluation examines numerous combinations of system parameters, including bandwidth, signal power, number of channel estimates, number of total clients, number of Sybil clients, and number of access points. For instance, both the false alarm rate and the miss rate of Sybil attacks are usually below 0.01, with three tones, pilot power of 10 mW, and a system bandwidth of 20 MHz.

We investigate the reliability of radio channel simulators in predicting channel responses throughout a well-specified environment. Indoor environments for which the geometric layout and material properties of surfaces are known lend themselves to such site-specific simulation. We assess the performance of this approach by comparing its predictions with measurements in a specific static environment. The good agreement on path loss, Ricean K-factor and RMS delay spread, over the set of paths measured and simulated, suggests that a well-designed radio simulator can be used reliably to predict system behavior. Typically, wireless channel models obtained through this or similar techniques do not capture the temporal variability in the channel response due to people movement in the environment. We treat the time-varying part of the channel response using stochastic processes. Using channel sounding experiments for several typical office scenarios, we show that autoregressive processes can be used to model the time-varying tap gains for several different motion scenarios.

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.

It has been discussed in the literature that the mobility of a mobile sensor network (MSN) can be used to improve its sensing coverage. How the mobility can efficiently be managed toward a better coverage, however, remains unanswered. In this paper, motivated by classical dynamics that study the movement of objects, we propose the concept of network dynamics and define the associated potential functions that capture the operational goals, as well as the environment of an MSN. We find that in managing the mobility of an MSN, Newton's laws of motion in classical dynamics are insufficient, for they introduce oscillations into the movement of sensor nodes. Instead, in network dynamics, the laws of motion are formulated using the steepest descent method in optimization. Based on the network dynamics model, we first devise a parallel and distributed algorithm (parallel and distributed network dynamics (PDND)) that runs on each sensor node to guide its movement. PDND then turns sensor nodes into autonomous entities that are capable of adjusting their locations according to the operational goals and environmental changes. After that, we formally prove the convergence of PDND. Finally, we apply PDND in three applications to demonstrate its effectiveness.

Many wireless networks are susceptible to spoofing attacks. Conventionally, ensuring the identity of the communicator and detecting an adversarial presence is performed via device authentication. Unfortunately, full-scale authentication is not always desirable as it requires key management and more extensive computations. In this paper, we propose noncryptographic mechanisms that are complementary to authentication and can detect device spoofing with little or no dependency on cryptographic keys. We introduce forge-resistant relationships associated with transmitted packets, and forge-resistant consistency checks, which allow other network entities to detect anomalous activity. We then provide several practical examples of forge-resistant relationships for detecting anomalous network activity. We explore the use of monotonic relationships in the sequence number fields, the use of a supplemental identifier field that evolves in time according to a reverse one-way function chain, and the use of traffic statistics to differentiate between anomalous traffic and congestion. We then show how these relationships can be used to construct classifiers that provide a multilevel threat assessment. We validate these methods through experiments conducted on the ORBIT wireless testbed.

Many techniques for multicast authentication employ the principle of delayed key disclosure. These methods introduce delay in authentication, employ receiver-side buffers, and are susceptible to denial-of-service (DoS) attacks. Delayed key disclosure schemes have a binary concept of authentication and do not incorporate any notion of partial trust. This paper introduces staggered timed efficient stream loss-tolerant authentication (TESLA), a method for achieving multigrade authentication in multicast scenarios that reduces the delay needed to filter forged multicast packets and, consequently, mitigates the effects of DoS attacks. Staggered TESLA involves modifications to the popular multicast authentication scheme, TESLA, by incorporating the notion of multilevel trust through the use of multiple, staggered authentication keys in creating message authentication codes (MACs) for a multicast packet. We provide guidelines for determining the appropriate buffer size, and show that the use of multiple MACs and, hence, multiple grades of authentication, allows the receiver to flush forged packets quicker than in conventional TESLA. As a result, staggered TESLA provides an advantage against DoS attacks compared to conventional TESLA. We then examine two new strategies for reducing the time needed for complete authentication. In the first strategy, the multicast source uses assurance of the trustworthiness of entities in a neighborhood of the source, in conjunction with the multigrade authentication provided by staggered TESLA. The second strategy achieves reduced delay by introducing additional key distributors in the network.

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 Diffie-Hellman problem is often the basis for establishing conference keys. In heterogeneous networks, many conferences have participants of varying resources, yet most conference keying schemes do not address this concern and place the same burden upon less powerful clients as more powerful ones. The establishment of conference keys should minimize the burden placed on resource-limited users while ensuring that the entire group can establish the key. In this paper, we present a hierarchical conference keying scheme that forms subgroup keys for successively larger subgroups en route to establishing the group key. A tree, called the conference tree, governs the order in which subgroup keys are formed. Key establishment schemes that consider users with varying costs or budgets are built by appropriately designing the conference tree. We then examine the scenario where users have both varying costs and budget constraints. A greedy algorithm is presented that achieves near-optimal performance, and requires significantly less computational effort than finding the optimal solution. We provide a comparison of the total cost of tree-based conference keying schemes against several existing schemes, and introduce a new performance criterion, the probability of establishing the session key (PESKY), to study the likelihood that a conference key can be established in the presence of budget constraints. Simulations show that the likelihood of forming a group key using a tree-based conference keying scheme is higher than the GDH schemes of Steiner et al.. Finally, we study the effect that greedy users have upon the Huffman-based conference keying scheme, and present a method to mitigate the detrimental effects of the greedy users upon the total cost.

Secure multicast applications require key management that provides access control. In wireless networks, where the error rate is high and the bandwidth is limited, the design of key management schemes should place emphasis on reducing the communication burden associated with key updating. A communication-efficient class of key management schemes is those that employ a tree hierarchy. However, these tree-based key management schemes do not exploit issues related to the delivery of keying information that provide opportunities to further reduce the communication burden of rekeying. In this paper, we propose a method for designing multicast key management trees that match the network topology. The proposed key management scheme localizes the transmission of keying information and significantly reduces the communication burden of rekeying. Further, in mobile wireless applications, the issue of user handoff between base stations may cause user relocation on the key management tree. We address the problem of user handoff by proposing an efficient handoff scheme for our topology-matching key management trees. The proposed scheme also addresses the heterogeneity of the network. For multicast applications containing several thousands of users, simulations indicate a 55%-80% reduction in the communication cost compared to key trees that are independent of the network topology. Analysis and simulations also show that the communication cost of the proposed topology-matching key management tree scales better than topology-independent trees as the size of multicast group grows.

The invention of the automobile has transformed how people live, work, and interact in society. Today, with an ever-increasing number of in-vehicle options/activities, as well as the increasing demands being placed on the driver, vehicle platform, and transportation infrastructure, more is being asked of engineers, designers, scientists, and transportation specialists. Signal processing is playing an increasingly substantial role in this domain, including such general topics as monitoring driver distraction, vehicle lane/control detection/tracking, driver assistance through autonomous platforms, and vehicle infrastructure support and planning/monitoring.

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.

We spend a considerable amount of time driving—to work, to home, for recreation, for travel. This love for the automobile is on the precipice of becoming a worldwide phenomenon. While new markets, like China, have opened up in the past decade, the need for the automotive industry to find new customers, combined with an array of emerging technologies that will make driving easier, will allow cars to reach markets that never before had access to driving. Likewise, the promise of new capabilities that automate and enhance the safety of the driving experience will guarantee that existing drivers return to purchase the latest model.

Examines ways in which signal processing engineers can benefit from new forms of informatino and data analysis in the era of "Big Data." Science and engineering are rapidly heading toward a major culture change—a change in how we think about data. This change is already happening, and it will be dramatic and exciting! It will completely change how most of us think about data and how we tackle science and engineering problems. With it will come a flood of new discoveries—advances in the sciences and in new technologies—that were never before possible. What is this revolution? How did we get here? Where is it going, and how is signal processing involved? The short answer is that we are entering an era of treasure hunting. Rather than digging through dirt like archaeologists looking for ancient artifacts, the future will involve digging through data. .

In this paper, we introduce a delay-sensitive service that involves transmitting large amounts of location-based data to nodes at multiple locations. Given a limited amount of access points (APs) and an abundance of service requests that result from the nodes moving around, a typical content delivery service would inevitably introduce considerable delay. To solve this problem, we analyze the movement pattern of mobile nodes and approximate it as a semi-Markov process. Based on this model, we explore different components of the underlying service delay and propose that APs should use a multicast strategy to minimize the queuing delay component. Furthermore, we demonstrate the feasibility of employing nodes, which already have their own local copies of location-relevant data, to relay such data to other nodes by employing one or multiple communication channels. Lastly, we examine the resulting algorithms and study their performance relative to baseline content-delivery schemes through simulations.

The problem of ensuring the secrecy of a communication while simultaneously maintaining sufficient throughput is a fundamental challenge facing secret communication. One of the challenges for such problems is that the optimal solution for one of objective might be not optimal for the other (e.g., an increase in secrecy might yield a decrease in throughput). Thus, there is a need for finding a trade-off solution for these objectives. In this paper, we consider a two-step approach to solve such problems and illustrate it for orthogonal frequency-division multiplexing-style communications. In the first step , we use the $\alpha $ -fairness criteria for formulating the tradeoff between objectives. A generalized water-filling equation for this tradeoff problem is solved. This equation includes, as a limit case, the classical case for secret communication with secrecy capacity as payoff. In the second step , we aim to find the best $\alpha $ -fair strategy, and show that Jain’s fairness can potentially lead to an unbalanced tradeoff between the two objectives. We arrive at a more balanced tradeoff by means of bargaining over the continuum of $\alpha $ -fair solutions. Both the Nash and Kalai–Smorodinsky bargaining solutions for fulfillment of both objectives are found, and the algorithms for finding the bargaining solutions are derived.

The aim of this special issue is to examine information security and privacy methods that complement traditional cryptographic services. The articles chosen survey the challenges associated with achieving security and privacy in both communications networks as well as distributed systems and identify signal processing approaches to protect information.

The 31 papers in this special issue focus on using the physical layer for securing the next generation of communication systems.