Biblio

This paper proposes an algorithm for multi-channel SAR ground moving target detection and estimation using the Fractional Fourier Transform(FrFT). To detect the moving target with low speed, the clutter is first suppressed by Displace Phase Center Antenna(DPCA), then the signal-to-clutter can be enhanced. Have suppressed the clutter, the echo of moving target remains and can be regarded as a chirp signal whose parameters can be estimated by FrFT. FrFT, one of the most widely used tools to time-frequency analysis, is utilized to estimate the Doppler parameters, from which the moving parameters, including the velocity and the acceleration can be obtained. The effectiveness of the proposed method is validated by the simulation.
 

In the United States, the number of Phasor Measurement Units (PMU) will increase from 166 networked devices in 2010 to 1043 in 2014. According to the Department of Energy, they are being installed in order to “evaluate and visualize reliability margin (which describes how close the system is to the edge of its stability boundary).” However, there is still a lot of debate in academia and industry around the usefulness of phase angles as unambiguous predictors of dynamic stability. In this paper, using 4-year of actual data from Hydro-Québec EMS, it is shown that phase angles enable satisfactory predictions of power transfer and dynamic security margins across critical interface using random forest models, with both explanation level and R-squares accuracy exceeding 99%. A generalized linear model (GLM) is next implemented to predict phase angles from day-ahead to hour-ahead time frames, using historical phase angles values and load forecast. Combining GLM based angles forecast with random forest mapping of phase angles to power transfers result in a new data-driven approach for dynamic security monitoring.
 

Modern power systems heavily rely on the associated cyber network, and cyber attacks against the control network may cause undesired consequences such as load shedding, equipment damage, and so forth. The behaviors of the attackers can be random, thus it is crucial to develop novel methods to evaluate the adequacy of the power system under probabilistic cyber attacks. In this study, the external and internal cyber structures of the substation are introduced, and possible attack paths against the breakers are analyzed. The attack resources and vulnerability factors of the cyber network are discussed considering their impacts on the success probability of a cyber attack. A procedure integrating the reliability of physical components and the impact of cyber attacks against breakers are proposed considering the behaviors of the physical devices and attackers. Simulations are conducted based on the IEEE RTS79 system. The impact of the attack resources and attack attempt numbers are analyzed for attackers from different threats groups. It is concluded that implementing effective cyber security measures is crucial to the cyber-physical power grids.

The video surveillance widely installed in public areas poses a significant threat to the privacy. This paper proposes a new privacy preserving method via the Generalized Random-Grid based Visual Cryptography Scheme (GRG-based VCS). We first separate the foreground from the background for each video frame. These foreground pixels contain the most important information that needs to be protected. Every foreground area is encrypted into two shares based on GRG-based VCS. One share is taken as the foreground, and the other one is embedded into another frame with random selection. The content of foreground can only be recovered when these two shares are got together. The performance evaluation on several surveillance scenarios demonstrates that our proposed method can effectively protect sensitive privacy information in surveillance videos.

This paper presents the design and implementation of an information flow tracking framework based on code rewrite to prevent sensitive information leaks in browsers, combining the ideas of taint and information flow analysis. Our system has two main processes. First, it abstracts the semantic of JavaScript code and converts it to a general form of intermediate representation on the basis of JavaScript abstract syntax tree. Second, the abstract intermediate representation is implemented as a special taint engine to analyze tainted information flow. Our approach can ensure fine-grained isolation for both confidentiality and integrity of information. We have implemented a proof-of-concept prototype, named JSTFlow, and have deployed it as a browser proxy to rewrite web applications at runtime. The experiment results show that JSTFlow can guarantee the security of sensitive data and detect XSS attacks with about 3x performance overhead. Because it does not involve any modifications to the target system, our system is readily deployable in practice.
 

The wireless network is become larger than past. So in the recent years the wireless with multiple sinks is more useful. The anonymity and privacy in this network is a challenge now. In this paper, we propose a new method for anonymity in multi sink wireless sensor network. In this method we use layer encryption to provide source and event privacy and we use a label switching routing method to provide sink anonymity in each cluster. A master sink that is a powerful base station is used to connect sinks to each other.

Detecting stationary crowd groups and analyzing their behaviors have important applications in crowd video surveillance, but have rarely been studied. The contributions of this paper are in two aspects. First, a stationary crowd detection algorithm is proposed to estimate the stationary time of foreground pixels. It employs spatial-temporal filtering and motion filtering in order to be robust to noise caused by occlusions and crowd clutters. Second, in order to characterize the emergence and dispersal processes of stationary crowds and their behaviors during the stationary periods, three attributes are proposed for quantitative analysis. These attributes are recognized with a set of proposed crowd descriptors which extract visual features from the results of stationary crowd detection. The effectiveness of the proposed algorithms is shown through experiments on a benchmark dataset.

Trusted Platform Module (TPM) has gained its popularity in computing systems as a hardware security approach. TPM provides the boot time security by verifying the platform integrity including hardware and software. However, once the software is loaded, TPM can no longer protect the software execution. In this work, we propose a dynamic TPM design, which performs control flow checking to protect the program from runtime attacks. The control flow checker is integrated at the commit stage of the processor pipeline. The control flow of program is verified to defend the attacks such as stack smashing using buffer overflow and code reuse. We implement the proposed dynamic TPM design in FPGA to achieve high performance, low cost and flexibility for easy functionality upgrade based on FPGA. In our design, neither the source code nor the Instruction Set Architecture (ISA) needs to be changed. The benchmark simulations demonstrate less than 1% of performance penalty on the processor, and an effective software protection from the attacks.

As information and communication networks are highly interconnected with the power grid, cyber security of the supervisory control and data acquisition (SCADA) system has become a critical issue in the power system. By intruding into the SCADA system via the remote access points, the attackers are able to eavesdrop critical data and reconfigure devices to trip the system breakers. The cyber attacks are able to impact the reliability of the power system through the SCADA system. In this paper, six cyber attack scenarios in the SCADA system are considered. A Bayesian attack graph model is used to evaluate the probabilities of successful cyber attacks on the SCADA system, which will result in breaker trips. A forced outage rate (FOR) model is proposed considering the frequencies of successful attacks on the generators and transmission lines. With increased FOR values resulted from the cyber attacks, the loss of load probabilities (LOLP) in reliability test system 79 (RTS79) are estimated. The results of the simulations demonstrate that the power system becomes less reliable as the frequency of successful attacks increases.

This paper deals with the robust H∞ cyber-attacks estimation problem for control systems under stochastic cyber-attacks and disturbances. The focus is on designing a H∞ filter which maximize the attack sensitivity and minimize the effect of disturbances. The design requires not only the disturbance attenuation, but also the residual to remain the attack sensitivity as much as possible while the effect of disturbance is minimized. A stochastic model of control system with stochastic cyber-attacks which satisfy the Markovian stochastic process is constructed. And we also present the stochastic attack models that a control system is possibly exposed to. Furthermore, applying H∞ filtering technique-based on linear matrix inequalities (LMIs), the paper obtains sufficient conditions that ensure the filtering error dynamic is asymptotically stable and satisfies a prescribed ratio between cyber-attack sensitivity and disturbance sensitivity. Finally, the results are applied to the control of a Quadruple-tank process (QTP) under a stochastic cyber-attack and a stochastic disturbance. The simulation results underline that the designed filters is effective and feasible in practical application.

Similarity search plays an important role in many applications involving high-dimensional data. Due to the known dimensionality curse, the performance of most existing indexing structures degrades quickly as the feature dimensionality increases. Hashing methods, such as locality sensitive hashing (LSH) and its variants, have been widely used to achieve fast approximate similarity search by trading search quality for efficiency. However, most existing hashing methods make use of randomized algorithms to generate hash codes without considering the specific structural information in the data. In this paper, we propose a novel hashing method, namely, robust hashing with local models (RHLM), which learns a set of robust hash functions to map the high-dimensional data points into binary hash codes by effectively utilizing local structural information. In RHLM, for each individual data point in the training dataset, a local hashing model is learned and used to predict the hash codes of its neighboring data points. The local models from all the data points are globally aligned so that an optimal hash code can be assigned to each data point. After obtaining the hash codes of all the training data points, we design a robust method by employing ℓ2,1-norm minimization on the loss function to learn effective hash functions, which are then used to map each database point into its hash code. Given a query data point, the search process first maps it into the query hash code by the hash functions and then explores the buckets, which have similar hash codes to the query hash code. Extensive experimental results conducted on real-life datasets show that the proposed RHLM outperforms the state-of-the-art methods in terms of search quality and efficiency.
 

The E-mail messaging is one of the most popular uses of the Internet and the multiple Internet users can exchange messages within short span of time. Although the security of the E-mail messages is an important issue, no such security is supported by the Internet standards. One well known scheme, called PGP (Pretty Good Privacy) is used for personal security of E-mail messages. There is an attack on CFB Mode Encryption as used by OpenPGP. To overcome the attacks and to improve the security a new model is proposed which is "Secure Mail using Visual Cryptography". In the secure mail using visual cryptography the message to be transmitted is converted into a gray scale image. Then (2, 2) visual cryptographic shares are generated from the gray scale image. The shares are encrypted using A Chaos-Based Image Encryption Algorithm Using Wavelet Transform and authenticated using Public Key based Image Authentication method. One of the shares is send to a server and the second share is send to the receipent's mail box. The two shares are transmitted through two different transmission medium so man in the middle attack is not possible. If an adversary has only one out of the two shares, then he has absolutely no information about the message. At the receiver side the two shares are fetched, decrypted and stacked to generate the grey scale image. From the grey scale image the message is reconstructed.
 

Certificateless public key cryptography (CL-PKC) combines the advantage of both traditional PKC and identity-based cryptography (IBC) as it eliminates the certificate management problem in traditional PKC and resolves the key escrow problem in IBC. Recently, Choi et al. and Tso et al.proposed two different efficient CL short signature schemes and claimed that the two schemes are secure against super adversaries and satisfy the strongest security. In this study, the authors show that both Choi et al.'s scheme and Tso et al.'s scheme are insecure against the strong adversaries who can replace users' public keys and have access to the signing oracle under the replaced public keys.
 

In PMIPv6-based network, mobile nodes can be made smaller and lighter because the network nodes perform the mobility management-related functions on behalf of the mobile nodes. One of the protocols, Fast Handovers for Proxy Mobile IPv6 (FPMIPv6) [1] was studied by the Internet Engineering Task Force (IETF). Since FPMIPv6 adopts the entities and the concepts of Fast Handovers for Mobile IPv6 (FMIPv6) in Proxy Mobile IPv6 (PMIPv6), it reduces the packet loss. The conventional scheme has been proposed to cooperate with an Authentication, Authorization and Accounting (AAA) infrastructure for authentication of a mobile node in PMIPv6. Despite the fact that this approach resulted in the best efficiency, without beginning secured signaling messages, The PMIPv6 is vulnerable to various security threats and it does not support global mobility. In this paper, the authors analyzed the Kang-Park & ESS-FH scheme, and proposed an Enhanced Security scheme for FPMIPv6 (ESS-FP). Based on the CGA method and the public key Cryptography, ESS-FP provides a strong key exchange and key independence in addition to improving the weaknesses of FPMIPv6 and its handover latency was analyzed and compared with that of the Kang-Park scheme & ESS-FH.
 

Alex Endert's dissertation "Semantic Interaction for Visual Analytics: Inferring Analytical Reasoning for Model Steering" described semantic interaction, a user interaction methodology for visual analytics (VA). It showed that user interaction embodies users' analytic process and can thus be mapped to model-steering functionality for "human-in-the-loop" system design. The dissertation contributed a framework (or pipeline) that describes such a process, a prototype VA system to test semantic interaction, and a user evaluation to demonstrate semantic interaction's impact on the analytic process. This research is influencing current VA research and has implications for future VA research.

Threats to modern ICT systems are rapidly changing these days. Organizations are not mainly concerned about virus infestation, but increasingly need to deal with targeted attacks. This kind of attacks are specifically designed to stay below the radar of standard ICT security systems. As a consequence, vendors have begun to ship self-learning intrusion detection systems with sophisticated heuristic detection engines. While these approaches are promising to relax the serious security situation, one of the main challenges is the proper evaluation of such systems under realistic conditions during development and before roll-out. Especially the wide variety of configuration settings makes it hard to find the optimal setup for a specific infrastructure. However, extensive testing in a live environment is not only cumbersome but usually also impacts daily business. In this paper, we therefore introduce an approach of an evaluation setup that consists of virtual components, which imitate real systems and human user interactions as close as possible to produce system events, network flows and logging data of complex ICT service environments. This data is a key prerequisite for the evaluation of modern intrusion detection and prevention systems. With these generated data sets, a system's detection performance can be accurately rated and tuned for very specific settings.

H.264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

Modern storage systems stripe redundant data across multiple nodes to provide availability guarantees against node failures. One form of data redundancy is based on XOR-based erasure codes, which use only XOR operations for encoding and decoding. In addition to tolerating failures, a storage system must also provide fast failure recovery to reduce the window of vulnerability. This work addresses the problem of speeding up the recovery of a single-node failure for general XOR-based erasure codes. We propose a replace recovery algorithm, which uses a hill-climbing technique to search for a fast recovery solution, such that the solution search can be completed within a short time period. We further extend the algorithm to adapt to the scenario where nodes have heterogeneous capabilities (e.g., processing power and transmission bandwidth). We implement our replace recovery algorithm atop a parallelized architecture to demonstrate its feasibility. We conduct experiments on a networked storage system testbed, and show that our replace recovery algorithm uses less recovery time than the conventional recovery approach.
 

Security threats are irregular, sometimes very sophisticated, and difficult to measure in an economic sense. Much published data about them comes from either anecdotes or surveys and is often either not quantified or not quantified in a way that's comparable across organizations. It's hard even to separate the increase in actual danger from year to year from the increase in the perception of danger from year to year. Staffing to meet these threats is still more a matter of judgment than science, and in particular, optimizing staff allocation will likely leave your organization vulnerable at the worst times.

In this paper we propose a framework for automating feedback control to balance hard-to-predict wind power variations. The power imbalance is a result of non-zero mean error around the wind power forecast. Our proposed framework is aimed at achieving the objective of frequency stabilization and regulation through one control action. A case-study for a real-world system on Flores island in Portugal is provided. Using a battery-based storage on the island, we illustrate the proposed control framework.
 

Sybil attack poses a serious threat to geographic routing. In this attack, a malicious node attempts to broadcast incorrect location information, identity and secret key information. A Sybil node can tamper its neighboring nodes for the purpose of converting them as malicious. As the amount of Sybil nodes increase in the network, the network traffic will seriously affect and the data packets will never reach to their destinations. To address this problem, researchers have proposed several schemes to detect Sybil attacks. However, most of these schemes assume costly setup such as the use of relay nodes or use of expensive devices and expensive encryption methods to verify the location information. In this paper, the authors present a method to detect Sybil attacks using Sequential Hypothesis Testing. The proposed method has been examined using a Greedy Perimeter Stateless Routing (GPSR) protocol with analysis and simulation. The simulation results demonstrate that the proposed method is robust against detecting Sybil attacks.

Sybil attack poses a serious threat to geographic routing. In this attack, a malicious node attempts to broadcast incorrect location information, identity and secret key information. A Sybil node can tamper its neighboring nodes for the purpose of converting them as malicious. As the amount of Sybil nodes increase in the network, the network traffic will seriously affect and the data packets will never reach to their destinations. To address this problem, researchers have proposed several schemes to detect Sybil attacks. However, most of these schemes assume costly setup such as the use of relay nodes or use of expensive devices and expensive encryption methods to verify the location information. In this paper, the authors present a method to detect Sybil attacks using Sequential Hypothesis Testing. The proposed method has been examined using a Greedy Perimeter Stateless Routing (GPSR) protocol with analysis and simulation. The simulation results demonstrate that the proposed method is robust against detecting Sybil attacks.

Visual cryptography is a way to encrypt the secret image into several meaningless share images. Noted that no information can be obtained if not all of the shares are collected. Stacking the share images, the secret image can be retrieved. The share images are meaningless to owner which results in difficult to manage. Tagged visual cryptography is a skill to print a pattern onto meaningless share images. After that, users can easily manage their own share images according to the printed pattern. Besides, access control is another popular topic to allow a user or a group to see the own authorizations. In this paper, a self-authentication mechanism with lossless construction ability for image secret sharing scheme is proposed. The experiments provide the positive data to show the feasibility of the proposed scheme.
 

Being the most important critical infrastructure in Cyber-Physical Systems (CPSs), a smart grid exhibits the complicated nature of large scale, distributed, and dynamic environment. Taxonomy of attacks is an effective tool in systematically classifying attacks and it has been placed as a top research topic in CPS by a National Science Foundation (NSG) Workshop. Most existing taxonomy of attacks in CPS are inadequate in addressing the tight coupling of cyber-physical process or/and lack systematical construction. This paper attempts to introduce taxonomy of attacks of agent-based smart grids as an effective tool to provide a structured framework. The proposed idea of introducing the structure of space-time and information flow direction, security feature, and cyber-physical causality is innovative, and it can establish a taxonomy design mechanism that can systematically construct the taxonomy of cyber attacks, which could have a potential impact on the normal operation of the agent-based smart grids. Based on the cyber-physical relationship revealed in the taxonomy, a concrete physical process based cyber attack detection scheme has been proposed. A numerical illustrative example has been provided to validate the proposed physical process based cyber detection scheme.
 

The longstanding debate on a fundamental science of security has led to advances in systems, software, and network security. However, existing efforts have done little to inform how an environment should react to emerging and ongoing threats and compromises. The authors explore the goals and structures of a new science of cyber-decision-making in the Cyber-Security Collaborative Research Alliance, which seeks to develop a fundamental theory for reasoning under uncertainty the best possible action in a given cyber environment. They also explore the needs and limitations of detection mechanisms; agile systems; and the users, adversaries, and defenders that use and exploit them, and conclude by considering how environmental security can be cast as a continuous optimization problem.