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In cryptography, secure channels enable the confidential and authenticated message exchange between authorized users. A generic approach of constructing such channels is by combining an encryption primitive with an authentication primitive (MAC). In this work, we introduce the design of a new cryptographic primitive to be used in the construction of secure channels. Instead of using general purpose MACs, we propose the deployment of special purpose MACs, named (\cal E)-MACs. The main motivation behind this work is the observation that, since the message must be both encrypted and authenticated, there might be some redundancy in the computations performed by the two primitives. Therefore, removing such redundancy can improve the efficiency of the overall composition. Moreover, computations performed by the encryption algorithm can be further utilized to improve the security of the authentication algorithm. In particular, we will show how (\cal E)-MACs can be designed to reduce the amount of computation required by standard MACs based on universal hash functions, and show how (\cal E)-MACs can be secured against key-recovery attacks. [ABSTRACT FROM AUTHOR]

Detection of targets moving within a field of interest is a fundamental service Wireless Sensor Network (WSN) service. The WSN’s target detection performance is directly related to the placement of the sensors within the field of interest. In this paper, we address the problem of deterministic sensor deployment on the plane and in space, for the purpose of detecting mobile targets. We map the target detection problem to a line-set intersection problem and derive analytic expressions for the probability of detecting mobile targets. Compared to previous works, our mapping allows us to consider sensors with heterogeneous sensing capabilities, thus analyzing sensor networks that employ multiple sensing modalities. We show that the complexity of evaluating the target detection probability grows exponentially with the network size and, hence, derive appropriate lower and upper bounds. We also show that maximizing the lower bound on the probability for target detection on the plane and in space, is analogous to the problem of minimizing the average symbol error probability in two-dimensional and three-dimensional digital modulation schemes, respectively, over additive white Gaussian noise. These problems can be addressed using the circle packing problem for the plane, and the sphere packing problem for space. Using the analogy to digital modulation schemes, we derive sensor constellations from well known signal constellations with low average symbol error probability. [ABSTRACT FROM AUTHOR]

In this correspondence, we propose a new model for threshold schemes with disenrollment capability (TSDC), to address the scenarios in which the ability of a coalition to construct future shared secrets is prohibited. Compared to existing TSDC models, our model provides forward secrecy by adding a constraint that the broadcast from the dealer is required to activate the reconstruction of any secret. We also present a TSDC model in which the dealer has the enhanced capability of disenrolling any subset of participants, to prevent the otherwise unnecessary rekey of the entire group when a large number of participants are compromised. We establish the lower bounds on the entropy of broadcast messages in both proposed models, as guidelines on constructing broadcast efficient schemes, and present bound achieving schemes. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we identify and study an important patient privacy protection problem related to medical images. Following Health Insurance Portability and Accountability Act (HIPAA) mandate on privacy protection of patients'' medical records, efforts have been devoted to guaranteeing the confidentiality of data and medical images during storage and transmission via an untrustworthy channel. However, to our knowledge, there has not been any effort towards protecting against unauthorized release of images by an authorized recipient. In this paper, we study the problem of tracing illegally distributed medical images in a group communication environment and identify a set of design requirements that must be met. We propose a fingerprint model suitable for many-to-many multicast, that is computationally efficient and scalable in user storage and key update communication. Simulation results also show that our scheme is highly robust to typical medical image processing and collusion attacks, while yielding high quality watermarked images. [Copyright &y& Elsevier]

Presents information on a study which showed that the rooted-tree-based multicast key distribution problem can be posed as an optimization problem using basic concepts from information theory. Review of the non-tree-based key distribution approaches for secure multicast communication; Formulation of the problem based on deletion statistics; Conclusions.

This paper studies the synthesis of controllers for cyber-physical systems (CPSs) that are required to carry out complex time-sensitive tasks in the presence of an adversary. The time-sensitive task is specified as a formula in the metric interval temporal logic (MITL). CPSs that operate in adversarial environments have typically been abstracted as stochastic games (SGs); however, because traditional SG models do not incorporate a notion of time, they cannot be used in a setting where the objective is time-sensitive. To address this, we introduce durational stochastic games (DSGs). DSGs generalize SGs to incorporate a notion of time and model the adversary's abilities to tamper with the control input (actuator attack) and manipulate the timing information that is perceived by the CPS (timing attack). We define notions of spatial, temporal, and spatio-temporal robustness to quantify the amounts by which system trajectories under the synthesized policy can be perturbed in space and time without affecting satisfaction of the MITL objective. In the case of an actuator attack, we design computational procedures to synthesize controllers that will satisfy the MITL task along with a guarantee of its robustness. In the presence of a timing attack, we relax the robustness constraint to develop a value iteration-based procedure to compute the CPS policy as a finite-state controller to maximize the probability of satisfying the MITL task. A numerical evaluation of our approach is presented on a signalized traffic network to illustrate our results. [ABSTRACT FROM AUTHOR]

In this paper, we explore a new direction towards solving the identity authentication problem in RFID systems. We break the RFID authentication process into two main problems: message authentication and random number generation. For parties equipped with a good source of randomness and a secure cryptographic primitive to authenticate messages, the literature of cryptography is rich with well-studied solutions for secure identity authentication. However, the two operations, random number generation and message authentication, can be expensive for low-cost RFID tags. In this paper, we lay down the foundations of a new direction towards solving these problems in RFID systems. We propose an unconditionally secure direction for authenticating RFID systems. We use the fact that RFID readers are computationally powerful devices to design a protocol that allows RFID readers to deliver random numbers to RFID tags in an unconditionally secure manner. Then, by taking advantage of the information-theoretic security of the transmitted messages, we develop a novel unconditionally secure message authentication code that is computed with a single multiplication operation. The goal of this work is to bring more research to the design of such unconditionally secure protocols, as opposed to the computationally secure protocols that have been proposed extensively, for the purpose of suiting the stringent computational capabilities of low-cost devices. [ABSTRACT FROM AUTHOR]

Message authentication codes (MACs) based on universal hash-function families are becoming increasingly popular due to their fast implementation. In this paper, we investigate a family of universal hash functions that has been appeared repeatedly in the literature and provide a detailed algebraic analysis for the security of authentication codes based on this universal hash family. In particular, the universal hash family under analysis, as appeared in the literature, uses operation in the finite field ℤℤ p. No previous work has studied the extension of such universal hash family when computations are performed modulo a non-prime integer n. In this work, we provide the first such analysis. We investigate the security of authentication when computations are performed over arbitrary finite integer rings ℤℤ n and derive an explicit relation between the prime factorization of n and the bound on the probability of successful forgery. More specifically, we show that the probability of successful forgery against authentication codes based on such a universal hash-function family is bounded by the reciprocal of the smallest prime factor of the modulus n. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. We propose to use a group representative to handle the recognition with a varying number of group members, and use an asynchronous hidden Markov model (AHMM) to model the relationship between people. Furthermore, we propose a group activity detection algorithm which can handle both symmetric and asymmetric group activities, and demonstrate that this approach enables the detection of hierarchical interactions between people. Experimental results show the effectiveness of our approach. [ABSTRACT FROM PUBLISHER]

Abstract-This paper presents a novel approach for automatic recognition of human activities for video surveillance applications. We propose to represent an activity by a combination of category components and demonstrate that this approach offers flexibility to add new activities to the system and an ability to deal with the problem of building models for activities lacking training data. For improving the recognition accuracy, a confident-frame-based recognition algorithm is also proposed, where the video frames with high confidence for recognizing an activity are used as a specialized local model to help classify the remainder of the video frames. Experimental results show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Cascading failures typically occur following a large disturbance in power systems, such as tripping of a generating unit or a transmission line. Such failures can propagate and destabilize the entire power system, potentially leading to widespread outages. One approach to mitigate impending cascading failures is through controlled islanding, in which a set of transmission lines is deliberately tripped to partition the unstable system into several disjoint, internally stable islands. Selecting such a set of transmission lines is inherently a combinatorial optimization problem. Current approaches address this problem in two steps: first, classify coherent generators into groups and then separate generator groups into different islands with minimal load-generation imbalance. These methods, however, are based on computationally expensive heuristics that do not provide optimality guarantees. This paper proposes a novel approach to controlled islanding based on weak submodularity. The new formulation jointly captures the minimal generator non-coherency and minimal load-generation imbalance in one objective function. The islanding problem is then relaxed to a formulation with bounded submodularity ratio and a matroid constraint. An approximation algorithm is proposed which achieves a provable optimality bound on non-coherency and load-generation imbalance. The proposed framework is tested on IEEE 39-bus and 118-bus power systems. [ABSTRACT FROM AUTHOR]

This paper studies the problem of selecting a submatrix of a positive definite matrix in order to achieve a desired bound on the smallest eigenvalue of the submatrix. Maximizing this smallest eigenvalue has applications to selecting input nodes in order to guarantee consensus of networks with negative edges as well as maximizing the convergence rate of distributed systems. We develop a submodular optimization approach to maximizing the smallest eigenvalue by first proving that positivity of the eigenvalues of a submatrix can be characterized using the probability distribution of the quadratic form induced by the submatrix. We then exploit that connection to prove that positive-definiteness of a submatrix can be expressed as a constraint on a submodular function. We prove that our approach results in polynomial-time algorithms with provable bounds on the size of the submatrix. We also present generalizations to non-symmetric matrices, alternative sufficient conditions for the smallest eigenvalue to exceed a desired bound that are valid for Laplacian matrices, and a numerical evaluation. [ABSTRACT FROM AUTHOR]

Voltage instability occurs when a power system is unable to meet the reactive power demand, and is typically corrected by switching on additional reactive power devices such as capacitor banks. Real-time monitoring and communication technologies can potentially improve voltage stability by enabling the rapid detection of low voltages and the implementation of corrective actions. These corrective actions, however, will only be effective in restoring stability if they are chosen in a timely, scalable manner. In this paper, we propose a submodular optimization approach for designing a control strategy that prevents voltage instability. Our key insight is that the voltage deviation from the desired level is a supermodular function of the set of reactive power injections that are employed, leading to computationally efficient control algorithms for stabilization with provable optimality guarantees. This submodular control framework is tested on the IEEE 300-bus transmission system. [ABSTRACT FROM PUBLISHER]

A common approach to controlling complex networks is to directly control a subset of input nodes, which then controls the remaining nodes via network interactions. Current approaches for selecting input nodes assume that either all system matrix entries are known and fixed, or are independent free parameters, and focus either on performance or controllability. In this paper, we make two contributions towards input selection in networked systems. First, we propose polynomial-time algorithms for input selection in structured linear descriptor systems, which are systems with dependencies between free parameters due to physical laws or design constraints. Second, we develop a framework for input selection based on joint consideration of controllability and performance. We make both contributions by mapping input selection to a submodular optimization problem under two matroid constraints, which enables development of polynomial-time algorithms with provable optimality guarantees. We provide improved optimality guarantees for special cases such as strongly connected networks, consensus networks, double integrators, and networks where all system parameters can take any arbitrary real values. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports within the issue on topics including trustworthy operations for cellular networks, content leakage during video streaming, and trustworthy service evaluation .

Cognitive radio (CR) is an emerging advanced radio technology in wireless access, with many promising benefits including dynamic spectrum sharing, robust cross-layer adaptation, and collaborative networking. Based on software-defined radio (SDR), CRs are fully programmable, and can sense their environment and dynamically adapt their transmission frequencies, power levels, modulation schemes, and networking protocols for improving network and application performance. It is anticipated that CR technology will be the next wave of innovation in information and communications technologies. [ABSTRACT FROM PUBLISHER]

In RFID literature, most “privacy-preserving” protocols require the reader to search all tags in the system in order to identify a single tag. In another class of protocols, the search complexity is reduced to be logarithmic in the number of tags, but it comes with two major drawbacks: it requires a large communication overhead over the fragile wireless channel, and the compromise of a tag in the system reveals secret information about other, uncompromised, tags in the same system. In this work, we take a different approach to address time complexity of private identification in large-scale RFID systems. We utilize the special architecture of RFID systems to propose a symmetric-key privacy-preserving authentication protocol for RFID systems with constant-time identification. Instead of increasing communication overhead, the existence of a large storage device in RFID systems, the database, is utilized for improving the time efficiency of tag identification. [ABSTRACT FROM AUTHOR]