Adaptive image steganography based on Syndrome-Trellis codes

Syndrome-Trellis Codes (STCs) have been widely used in adaptive steganography due to their high embedding efficiency. However, this type of steganographic codes is sensitive to stego damage, which may be incurred by compression, channel noise, active attacks, and so on, in practical covert communication. In this paper, a construction of robust STCs is proposed to achieve a good balance between robustness and embedding efficiency. The encoder of the proposed scheme performs a specified Error Correction Code (ECC) on the STC’s intermediate outputs. Further, a Viterbi algorithm is suggested to effectively find the optimum stego vector. At the extraction phase, the received stego vector is first decoded by the decoder of the employed ECC and then sent to the STC decoder, which gives the extracted message bits. Experimental results show the proposed scheme presents a good robustness performance, meanwhile the stego remains an acceptable detection resistance against steganalyzers.

The paper examined the problem of modeling and design of software computer systems. The article briefly describes the content aspects of the various stages of the implementation of software complexes and systems. The methodology of research and analysis of systems, which uses the method of computer simulation modeling, is given. The aim of the work is to create a new universal approach to the design and implementation of software systems of various levels of complexity. During the study, the following general scientific methods were used: system analysis, synthesis, formalization, modeling, decomposition, structuring, description, comparison. The materials used in the study were: computers and software development tools. As a result of the study proposed a universal agent-module approach to the design and implementation of software systems based on simulation agent-based modeling. The study presents the processes of modeling and designing software systems, their stages, and the possibility of their integration within the described approach. Examples of formal model and structure of the software system under design based on the agent-module approach are presented. The proposed approach can be used in the process of software development at the initial stages related to modeling and designing of software systems. Integration of modeling and design stages in the proposed approach will significantly reduce software development time and simplify the design process by making it clearer and more formalized. Materials of the article are of scientific and practical value for a wide range of specialists interested in system analysis, modeling, design and implementation of software systems.

The growth in the volume of information transmission and transaction over the internet has necessitated the development and enhancement of measures and techniques required to ensure the safety of critical information during transmission. with developments in mobile technologies and the adoption and diffusion of android mobile devices, research must therefore continue to explore more secured media in which information can be hidden. One of such medium is the use of image carriers referred to as steganography. In tis paper, we provide insughts into the development of an android-based Image Steganography System for concealing data and information using adaptive image steganography. The Least Significant Bit (LSB) algorithm was employed as the algorithmic sequence for the development. Preliminary results from implementation and testing showed promising results Keywords: Android, image steganography, data, information, transmission, images, security

To improve the efficiency of peer-to-peer (P2P) systems while adapting to changing environmental conditions, static peer-to-peer protocols can be replaced by adaptive plans. The resulting systems are inherently complex, which makes their development and characterization a challenge for traditional methods. Here we propose the design and analysis of adaptive P2P systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. These measures allow the evaluation of adaptive P2P systems and thus can be used to guide their design. We evaluate the proposal with a P2P computing system provided with adaptation mechanisms. We show the evolution of the system with static and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, which correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less “aggressive”, the system may be more stable, but the optimal performance may not be achieved.

Genetic Algorithms Are NOT Function Optimizers

The article consists of two parts. The first part presents a brief informative description of the averaging method proposed as a method for design and analysis of adaptive control systems using locally optimal control laws and identification by the recursive least-squares method. The second part presents the simulation results, examines their fit to theoretical results, and elucidates some features of behavior outside the scope of the theory.

The demand for creating increasingly dynamic, autonomous and proactive software systems is challenging for the traditional Multi-agent Systems (MASs) approaches. Such requirement has given rise to adaptive software agents approaches. At the same time, norm is an essential and challenging feature that still tends to be addressed in adaptive MAS. In fact, norms to regulate agent behavior is still a vague concept that has not been properly investigated in terms of modeling and implementation. Even though many researchers have proposed modeling languages to deal with different abstractions, these languages fail to support the modeling of abstractions, such as adaptation and norms. Even more severe is the fact that little has been done to support the systematic design of Adaptive Normative Multi-Agent Systems (ANMASs). To facilitate the design and development of ANMASs, this paper presents a new metamodel, as well as language support, as means to provide tools to enable software developers. The proposed metamodel fosters a better understanding of the way agents are able to change their behaviors to deal with norms and captures interactions between agent’s norms and adaptation. To this end, our research is organized into five steps: (i) a literature review to identify the limitations of existing approaches related to ANMAS modeling; (ii) propose a new metamodel to support adaptative and normative concepts; (iii) propose a new language for modeling ANMASs; (iv) perform a qualitative and quantitative evaluation of the proposed language using a real case scenario, and (v) an empirical evaluation. The proposed metamodel and its associated modeling language advances the state of the art in modeling MASs and the approach is assessed in terms of correctness, time and difficulty. Our initial results revealed that our approach can be feasibly applied in a real world application, and is less difficult to apply and requires less time in comparison with a traditional approach. As software applications become more dynamic and adaptive, we believe it is essential to support developers to model MASs with abstractions such as adaptive agents, norms and their relationships. Such information can be foundational to steer future research on modeling adaptive agents capable of understanding and dealing with norms and adaptation.

The case study described in this chapter concerns the introduction of a new computer based integrated Clinical Information System (CIS) into a British National Health Services Trust-the Sunrise Trust. At the time of the study most of the system modules had been developed and were being tested largely for technical aspects. The system was being introduced during a period when the organization was experiencing significant changes. It was an environment where new structures were being created and the existing ones changed. Indeed, the case study was selected primarily because of these factors. The analysis of these structures, formal and informal, provides insight into the management of information systems. Various stakeholders in the Hospital Trust felt that a computer based information system would facilitate the change process. However the analysis and design of the system posed its own problems. The system turned out to be inflexible with respect to the core health care delivery process. It was also nonresponsive to the needs of the key stakeholders. Analysis of the case shows that clearly the formal methods adopted by the system analysts fell short of determining the rapid changes required for care. In particular this was an important issue, since the context of the British National Health Services posed pressures on individual trusts to be cost effective. This resulted in long term patients being moved out into the community. However, this richness in the context was overlooked by the analysts. They developed “logical” models of the system, which ended up in being “tidy pictures of reality” and were prescriptive and utterly inflexible. Structured Systems Analysis and Design Method (SSADM) was used as a modelling tool, which amplified the rational view of decision making and information technology (IT) applications (for more details on SSADM see Downs et al., 1988). The interpretations identified in the case show a clear mis-match between the formal models and perceptions of the system users who inevitably reflect a more informal and pragmatic approach to their own organizational realities. The analysis of the case poses a number of interesting issues. It questions the relationship between the complexity of the social relations and systems design. Furthermore it brings to the fore the paradoxical viewpoints of different stakeholders and the emergent concerns for a system analyst. The chapter also identifies the impact of an “overformalized” information system on the integrity of an organization. In doing so it evaluates the nature and significance of social power structures in systems analysis, design and implementation.

Multiple academic and industry-based communities have engaged in defining the theoretical constructs, practical approaches, and technical standards for technology-enabled systems of human learning. However, conceptual and architectural models of Adaptive Instructional Systems (AISs) often focus on the functions of the technology, with the learner as a user external to the system. We offer an AIS model that considers the learner as a key component at the heart of a learning system. The learner, along with other human actors and environmental conditions, interact with technology components in a distributed learning system. Modular components surrounding the learner are interoperable. Data flow between the components using standards-based interfaces for instrumented and adaptive learner experiences. The model builds on functional components identified by Glowa & Goodell (2016) in Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning. The model is further informed by the IEEE workgroup P2247.1 developing a standard for the classification of adaptive instructional systems. It examines the learning system at a conceptual level and then maps those conceptual categories to functional components as modules in a distributed learning system. The model is rooted in the process of learning engineering as defined by the IEEE Industry Connection Industry Consortium on Learning Engineering (ICICLE). We envision future design and development of adaptive instructional systems benefiting from an emerging learning engineering discipline that embraces an iterative problem-solving approach. The proposed AIS model is a self-improving system by design that embodies key learning engineering processes.

Web personalization facilitate customizing a web site as per users preferences by using the various data mining techniques, taking advantage of the knowledge acquired from the analysis of the user’s navigational usage data. The web personalization reduces the searching time of the user and serves the purchasing interest of the user. In this paper, we have proposed the Analysis and design of the E-Commerce Systems. On the basis of the proposed Software specification Requirements ,for analysis of the systems, we proposed the class diagram for Preprocessing Systems, Knowledge Discovery Systems and Recommendation Subsystems and then provided workflow of the systems by proposing the required functional model of the systems. In the design of the systems we proposed the data structure design and Dynamic Web Systems architecture and implemented the systems. Lastly we have shown the results of the navigational behavior of the user during particular transaction.

Several systematic approaches have been developed for the optimal design of cable-based systems. Global indices are usually employed to quantify the effectiveness of a specific design inside a reference region of the workspace. The performances at the moving platform are strictly related to cable configuration, which, in turn, depends on the pose of the moving platform. As a result, traditional designs are characterized by the high variability of performances within the workspace and are often badly tailored to the design goals. The motivation behind this paper is to formalize a new design methodology for cable-driven devices. Based on a total or partial decoupling between cable disposition and end-effector pose, this methodology allows us to achieve well-tailored design solutions for a given design requirement. The resulting systems are here defined as adaptive cable-driven systems. Two simple design problems are presented and solved with both the traditional and the novel approaches, and the advantages of the latter are emphasized by comparing the resulting design solutions.

There are considerable hurdles that must be overcome in order to maintain adequate security against cyber-attacks in cloud settings because of their dynamic and dispersed nature. A proactive method to identifying and mitigating new threats in real time is provided by adaptive intrusion detection systems (IDS) that make use of machine learning (ML). The design and operation of adaptive intrusion detection systems (IDS) that are adapted for cloud platforms are investigated in this study. Particular attention is paid to the utilisation of supervised, unsupervised, and reinforcement learning methods. It investigates the benefits of adaptive intrusion detection systems (IDS) in terms of identifying abnormal behaviours, minimising the number of false positives, and adapting to shifting threat environments. Several important factors, including the selection of features, the quality of the dataset, and the optimisation of the algorithm, are covered. In addition to this, we investigate the possibility of integrating adaptive intrusion detection systems with cloud-native technologies such as serverless computing and containers. Performance measurements and comparative evaluations demonstrate that machine learning-based intrusion detection systems are more effective than older techniques. Additionally, the study addresses issues such as scalability, data privacy, and adversarial assaults, and it proposes viable methods to improve dependability. The adaptive intrusion detection system (IDS) is an essential component of cloud security methods since it enables continuous monitoring and reaction to complex kinds of attacks.

It is widely known that, for most computer applications, their users and contexts of usage are quite heterogeneous and change in time. A variability analysis approach was developed to bridge the gap between requirements engineering and human-computer interaction can help identify these variations and design flexible, adaptable and adaptive solutions that accommodate them at interaction time, i.e., during system usage. The core assumption of the approach is that an in-depth exploration of how user goals can be formulated into diverse user requests expressed in a linguistic structure using cases, designers will be better equipped to create solutions that cope with variations during user-system interaction. This paper shows how a set of adaptation-related questions and related interactive solutions may help to bridge the problem and solution spaces of flexible, adaptable and adaptive systems.

The theory and design of linear adaptive filters based on FIR filter structures is well developed and widely applied in practice. However, the same is not true for more general classes of adaptive systems such as linear infinite impulse response adaptive filters (MR) and nonlinear adaptive systems. This situation results because both linear IIR structures and nonlinear structures tend to produce multi-modal error surfaces for which stochastic gradient optimization strategies may fail to reach the global minimum. After briefly discussing the state of the art in linear adaptive filtering, the attention of this paper is turned to MR and nonlinear adaptive systems for potential use in echo cancellation, channel equalization, acoustic channel modeling, nonlinear prediction, and nonlinear system identification. Structured stochastic optimization algorithms that are effective on multimodal error surfaces are then introduced, with particular attention to the particle swarm optimization (PSO) technique. The PSO algorithm is demonstrated on some representative IIR and nonlinear filter structures, and both performance and computational complexity are analyzed for these types of nonlinear systems.

BackgroundThe importance of health policy and systems research and analysis (HPSR + A) has been increasingly recognised, but it is still unclear how most effectively to strengthen the capacity of the different organisations involved in this field. Universities are particularly crucial but the expansive literature on capacity development has little to offer the unique needs of HPSR + A activity within universities, and often overlooks the pivotal contribution of capacity assessments to capacity strengthening.MethodsThe Consortium for Health Policy and Systems Analysis in Africa 2011–2015 designed and implemented a new framework for capacity assessment for HPSR + A within universities. The methodology is reported in detail.ResultsOur reflections on developing and conducting the assessment generated four lessons for colleagues in the field. Notably, there are currently no published capacity assessment methodologies for HPSR + A that focus solely on universities – we report a first for the field to initiate the dialogue and exchange of experiences with others. Second, in HPSR + A, the unit of assessment can be a challenge, because HPSR + A groups within universities tend to overlap between academic departments and are embedded in different networks. Third, capacity assessment experience can itself be capacity strengthening, even when taking into account that doing such assessments require capacity.ConclusionsFrom our experience, we propose that future systematic assessments of HPSR + A capacity need to focus on both capacity assets and needs and assess capacity at individual, organisational, and systems levels, whilst taking into account the networked nature of HPSR + A activity. A genuine partnership process between evaluators and those participating in an assessment can improve the quality of assessment and uptake of results in capacity strengthening.