We present two modulation and detection techniques that are designed to allow for efficient equalization for channels that exhibit an arbitrary Doppler spread but no delay spread. These techniques are based on principles similar to techniques designed for time-invariant delay spread channels (e.g., Orthogonal Frequency Division Multiplexing or OFDM) and have the same computational complexity. Through numerical simulations, we show that effective equalization is possible for channels that exhibit a high Doppler spread and even a modest delay spread, whereas equalized OFDM exhibits a strictly worse performance in these environments. Our results indicate that, in rapidly time-varying channels, such as those found in high-mobility or mmWave deployments, new modulation coupled with appropriate channel estimation and equalization techniques may significantly outperform modulation and detection schemes that are designed for static or slowly time varying multipath channels.

We present an algorithm that efficiently performs blind decoding of MIMO signals. That is, given no channel state information (CSI) at either the transmitter or the receiver, our algorithm takes a block of samples and returns an estimate of the underlying data symbols. In prior work, the problem of blind decoding was formulated as a non-convex optimization problem. In this paper, we present an algorithm that efficiently solves this non-convex problem in practical settings. This algorithm leverages the concepts of linear and mixed-integer linear programming. Empirically, we show that our technique has an error performance close to that of zero-forcing with perfect CSI at the receiver. Initial estimates of the run time of the algorithm presented in this paper suggest that the real-time blind decoding of MIMO signals is possible for even modest-sized MIMO systems.

We propose a method for multiple-input multiple-output (MIMO) decoding when channel-state information (CSI) is unknown to both the transmitter and receiver. The proposed method requires some structure in the transmitted signal for the decoding to be effective, in particular that the underlying sources are drawn from a hypercubic space. Our proposed technique fits a minimum volume parallelepiped to the received samples. This problem can be expressed as a non-convex optimization problem that can be solved with high probability by gradient descent. Our blind decoding algorithm can be used when communicating over unknown MIMO wireless channels using either binary phase-shift keying or MPAM modulation. We apply our technique to jointly estimate MIMO-channel gain matrices and decode the underlying transmissions with only knowledge of the transmitted constellation and without the use of pilot symbols. Our results provide theoretical guarantees that the proposed algorithm is correct when applied to MIMO systems with four or fewer transmit antennas. Empirical results show small sample size requirements, making this algorithm suitable for block-fading channels with coherence times typically seen in practice. Our approach has a loss of less than 3 dB compared to zero forcing with perfect CSI, imposing a similar performance penalty as space-time coding techniques without the loss of rate incurred by those techniques.

A new modulation technique for the time-frequency dispersive channel is considered. The waveform construction, called Frequency-Domain Multiplexing with a Frequency-Domain Cyclic Prefix (FDM-FDCP) efficiently corrects for the Doppler spread introduced by the channel. The mathematical foundations behind this construction are described and efficient algorithms presented to modulate and demodulate information symbols. It is found that for channels with a high Doppler spread and a low delay spread, the construction can sustain good performance in terms of low SER and minimal overhead, whereas OFDM is strictly worse. This shows that, in rapidly time-varying time-frequency dispersive channels, general time-frequency signaling schemes (FDM-FDCP being an example) may outperform OFDM or other waveform constructions designed for multipath channels with low mobility.

Network protocol parsers constantly dissect a large number of packets to place into internal data structures for further processing. We propose an approach that automatically generates custom protocol parsers to process network traffic to be used as part of an Intrusion Detection System. This paper takes a look at the case of command and control/industrial control networks that are characterized by a limited number of known protocols. We present a robust, secure, and high-performing solution that deals with the issues that have only partially been addressed in this domain.

We propose the new technique of physical-layer cryptography based on using a massive MIMO channel as a key between the sender and desired receiver, which need not be secret. The goal is for low-complexity encoding and decoding by the desired transmitter-receiver pair, whereas decoding by an eavesdropper is hard in terms of prohibitive complexity. The decoding complexity is analyzed by mapping the massive MIMO system to a lattice. We show that the eavesdropper's decoder for the MIMO system with M-PAM modulation is equivalent to solving standard lattice problems that are conjectured to be of exponential complexity for both classical and quantum computers. Hence, under the widely-held conjecture that standard lattice problems are hard to solve, the proposed encryption scheme has a more robust notion of security than that of the most common encryption methods used today such as RSA and Diffie-Hellman. In addition, we show that this scheme could be used to securely communicate without a pre-shared secret and little computational overhead. Thus, by exploiting the physical layer properties of the radio channel, the massive MIMO system provides for low-complexity encryption commensurate with the most sophisticated forms of application-layer encryption that are currently known.

Functional behavior is considered to be the most basic, yet a critical notion in order to determine the characteristics of a system. However, how to reason about the functional behavior of a system in a systematic manner, is mostly limited by our cognitive processing abilities. While the UML-based behavior models can support a visual conceptualization of the functional behavior, they lack the rigorous, machine-processable reasoning capabilities. In this paper, we present a practical, knowledge-based approach to model the functional behavior that incorporates the notions of Commonsense Reasoning and Functional Reasoning over its core defining aspects. We demonstrate our approach with a detailed example, along with a set of use case scenarios. The main motivation behind this work was to develop a rigorous, logic-based approach to verify the levels of functional consistencies between cross-platform event-based systems. The focus of this paper, however, is to present the representational facility that can be utilized for the consistency validation system. While we provide a brief overview of the consistency validation system in this paper, a separate article will be dedicated for the comprehensive overview of the validation system itself.

With the advancement of newer technologies, the frequency of malicious attacks is growing rapidly. Even private networks without external connections cannot hide from these attacks. Constant monitoring of the network is a vital element of an organization's security system. Among many monitoring techniques, network behavior analysis has become a common practice. Restricted private networks are characterized by a limited number of protocols. The normal traffic pattern of a network can be modeled as network constraints. Violation of any of these constraints indicates that an intrusion has occurred. This paper presents a novel framework to detect intrusions in a private network. We illustrate the framework with ten significant constraints on the real-time publish, subscribe and internet group management protocols. We present how the framework evaluates these constraints against traffic from an experimental network to prevent attacks.

This paper presents a semi-automated framework for identifying and representing different kinds of variability in Simulink models. Based on the observed variants found in similar subsystem patterns inferred using Simone, a text-based model clone detection tool, we propose a set of variability operators for Simulink models. By applying these operators to six example systems, we are able to represent the variability in their similar subsystem patterns as a single subsystem template directly in the Simulink environment. The product of our framework is a single consolidated subsystem model capable of expressing the observed variability across all instances of each inferred pattern. The process of pattern inference and variability analysis is largely automated and can be easily applied to other collections of Simulink models. The framework is aimed at providing assistance to engineers to identify, understand, and visualize patterns of subsystems in a large model set. This understanding may help in reducing maintenance effort and bug identification at an early stage of the software development.

We propose the new technique of physical-layer cryptography based on using a massive MIMO channel as a key between the sender and desired receiver, which need not be secret. The goal is for low-complexity encoding and decoding by the desired transmitter-receiver pair, whereas decoding by an eavesdropper is hard in terms of prohibitive complexity. The massive MIMO system has a channel gain matrix that is drawn i.i.d. according to a Gaussian distribution, subject to additive white Gaussian noise. The decoding complexity is analyzed by mapping the massive MIMO system to a lattice. We show that the eavesdropper's decoder for the MIMO system with M-PAM modulation is equivalent to solving standard lattice problems that are conjectured to be of exponential complexity for both classical and quantum computers. Hence, under the widely-held conjecture that standard lattice problems are of worst-case complexity, the proposed encryption scheme has security that exceeds that of the most common encryption methods used today such as RSA and Diffie-Hellman. Additionally, we show that this scheme could be used to securely communicate without a pre-shared secret key and little computational overhead. In particular, a standard parallel channel decomposition allows the desired transmitter-receiver pair to encode and decode transmissions over the MIMO channel based on the singular value decomposition of the channel, while decoding remains computationally hard for an eavesdropper with an independent channel gain matrix, even if it knows the channel gain matrix between the desired transmitter and receiver. Thus, the massive MIMO system provides for low-complexity encryption commensurate with the most sophisticated forms of application-layer encryption by exploiting the physical layer properties of the radio channel.

SUMMARY We introduce a new Syntax‐based Security Testing framework that uses a protocol specification to perform security testing on text‐based communication protocols. A protocol specification of a particular text‐based protocol under test represents its syntactic grammar and static constraints. The specification is used to generate test cases by mutating valid messages, breaking the syntax and constraints of the protocol. The framework is demonstrated using a toy web application and the open source application KOrganizer. Copyright © 2012 John Wiley & Sons, Ltd.

While graph-based techniques show good results in finding exactly similar subgraphs in graphical models, they have great difficulty in finding near-miss matches. Text-based clone detectors, on the other hand, do very well with near-miss matching in source code. In this paper we introduce SIMONE, an adaptation of the mature text-based code clone detector NICAD to the efficient identification of structurally meaningful near-miss subsystem clones in graphical models. By transforming graph-based models to normalized text form, SIMONE extends NICAD to identify near-miss subsystem clones in Simulink models, uncovering important model similarities that are difficult to find in any other way.

Abstract Legacy information systems, such as banking systems, are usually organized around their data model. Hence, when these systems are migrated to modern environments, translation of the data model involves the most critical decisions, having strong implications on the rest of the translation. In this paper, we report our experience and describe the approaches adopted in migrating a large banking system (ten million lines of code) to Java, starting from a proprietary data model which gives programmers explicit control of the variable overlay in memory. After presenting the basic translation scheme, we discuss the exceptions that may occur in practice. Then, we consider two heuristic approaches useful to reduce the number of cases where a behavior equivalent to that of unions must be reproduced in Java. Finally, we comment on the experimental results obtained so far. Copyright © 2009 John Wiley & Sons, Ltd.

Abstract Models are considered an essential step in capturing different system behaviours and simplifying the analysis required to check or improve the quality of software. Verification and testing of web software requires effective modelling techniques that address the specific challenges of web applications. In this study we survey 24 different modelling methods used in web site verification and testing. Based on a short catalogue of desirable properties of web applications that require analysis, two different views of the methods are presented: a general categorization by modelling level, and a detailed comparison based on property coverage. Copyright © 2008 John Wiley & Sons, Ltd.

In the working session on Industrial Realities of Program Comprehension (IRPC 2008), experience and ideas are shared regarding the challenges and opportunities of industrial application of program comprehension techniques. Participants work together to formulate a set of useful guidelines for introducing new program comprehension techniques into industrial practice as well as consolidating and increasing their use.

An appropriate translation of the data model is central to any language migration effort. Finding a mapping between original and target data models may be challenging for legacy languages (e.g., Assembly) which lack a structured data model and rely instead on explicit programmer control of the overlay of variables. Before legacy applications written in languages with an unstructured data model can be migrated to modern languages, a structured data model must be inferred. This paper describes a set of source transformations used to create such a model as part of a migration of eight million lines of code to Java. The original application is written in a proprietary language supporting variable layout by memory relocation.

AJAX is a Web application programming technique that allows portions of a Web page to be loaded dynamically, separate from other parts of the Web page. This gives the user a much smoother experience when viewing the Web page. This paper describes the process of converting a class of Web pages from round-trip to AJAX.

Aspect mining aims at identifying cross-cutting concerns in existing systems and therefore advocates the adaption to an aspect-oriented design. This paper presents a case study examining three existing aspect mining techniques from the literature by applying them to four different open source java applications. We compare and evaluate the individual technique and confirm the findings of a previous study of combining different aspect mining techniques in order to get better results with less manual intervention.

This special issue features extended versions of selected papers from the 8th IEEE International Symposium on Web Site Evolution (WSE 2006) that was held in Philadelphia PA, on 23-24 September 2006.The symposium was co-located with the 22nd IEEE International Conference on Software Maintenance (ICSM 2006).Since its inception in 1999, the Web Site Evolution (WSE) series of events have provided a forum for researchers and practitioners from the communities of Software Maintenance and Evolution and Web Engineering to present original work and discuss subjects related to the disciplined evolution of large-scale Web sites.Researchers and practitioners working in the areas of Web application design, development, maintenance, and evolution attend WSE to discuss results and exchange experiences about models, methods, tools, and technologies related to the above-mentioned areas.In particular, the last editions of WSE have represented a significant step in making the WSE community more and more interdisciplinary, building bridges with various areas such as communication, HCI, usability, and quality and maintenance.We wish to maintain and enrich this multi-faceted spirit of the community, as well as to reach and involve other researchers and practitioners in this effort.WSE began as a one-day workshop, but, thanks to the success in terms of attendance and number of submissions, in 2006 it expanded into a two-day symposium to include keynote presentations, technical sessions, working sessions, and panels discussions.Out of 31 submissions, 13 excellent papers were selected to be presented at the symposium.The accepted papers covered a broad range of topics of the whole life cycle of Web systems, from design to implementation, evaluation, and maintenance, including: Modeling and Architecture, Web Trends and Technology, Accessibility and User Behavior, Comprehension, Testing and Security.The WSE 2006 program also included two inspiring keynotes: 'Model Driven Evolution of Network-Centric Applications: Perspectives, Applications, and Issues' by Kostas Kontogiannis, and 'Knowing Your Online Readership, Organizing Your Communication' by Lorenzo Cantoni.After the symposium, five outstanding papers were selected by the program chairs for invitation to this special issue of the Journal of Software Maintenance and Evolution: Research and Practice.The authors of the selected papers were asked to prepare a significant extension on the symposium version of their papers.Each paper underwent a rigorous reviewing process, involving three independent reviewers and two rounds of revisions.Eventually, four papers were accepted for inclusion in this special issue, covering four different topics of Web systems maintenance and evolution: Comprehension, Testing, Empirical Studies, and Patterns.During Web application re-engineering, a common activity is to identify similar content located in different static and dynamically generated Web pages, so that the content can be more effectively reused.The paper 'Identifying Similar Pages of Web Applications using a Competitive Clustering

The year 2000 problem posed a difficult problem for many IT shops world wide. The most difficult part of the problem was not the actual changes to ensure compliance, but finding and classifying the data fields that represent dates. This is a problem well suited to design recovery. The paper presents an overview of LS/2000, a system that used design recovery to analyze source code for year 2000 risks and guide a source transformation that was able to automatically remediate over 99% of the year 2000 risks in over three billion lines of production IT source.

Introduces a general, extensible diagrammatic syntax for expressing software architectures based on typed nodes and connections and formalized using set theory. The syntax provides a notion of abstraction corresponding to the concept of a subsystem, and exploits this notion in a general mechanism for pattern matching over architectures. We demonstrate these ideas using a small example architecture language with a limited number of types of nodes and connectors, and a small taxonomy of architectures characterized as sets of patterns in the language.>