Logico-linguistic semantic representation of documents

The knowledge behind the gigantic pool of data remains largely unextracted. Techniques such as ontology design, RDF representations, hpernym extraction, etc. have been used to represent the knowledge. However, the area of logic (FOPL) and linguistics (Semantics) has not been explored in depth for this purpose. Search engines suffer in extraction of specific answers to queries because of the absence of structured domain knowledge. The current paper deals with the design of formalism to extract and represent knowledge from the data in a consistent format. The application of logic and linguistics combined greatly eases and increases the precision of knowledge translation from natural language. The results clearly indicate the effectiveness of the knowledge extraction and representation methodology developed providing intelligence to machines for efficient analysis of data. The methodology helps machines to precise results in an efficient manner

Cyber-Physical Systems and Smart Cities in India: Opportunities, Issues, and Challenges

A large section of the population around the globe is migrating towards urban settlements. Nations are working toward smart city projects to provide a better wellbeing for the inhabitants. Cyber-physical systems are at the core of the smart city setups. They are used in almost every system component within a smart city ecosystem. This paper attempts to discuss the key components and issues involved in transforming conventional cities into smart cities with a special focus on cyber-physical systems in the Indian context. The paper primarily focuses on the infrastructural facilities and technical knowhow to smartly convert classical cities that were built haphazardly due to overpopulation and ill planning into smart cities. It further discusses cyber-physical systems as a core component of smart city setups, highlighting the related security issues. The opportunities for businesses, governments, inhabitants, and other stakeholders in a smart city ecosystem in the Indian context are also discussed. Finally, it highlights the issues and challenges concerning technical, financial, and other social and infrastructural bottlenecks in the way of realizing smart city concepts along with future research directions

A Continuous Risk Management Approach for Cyber-Security in Industrial Control Systems

In industrial networks, a cyber-incident can have, as a consequence, the interference with physical processes, which can potentially cause damages to property, to humans’ health and safety, and to the environment. Currently most safeguards built into Industrial Control Systems provide mitigations against accidents and faults but are not necessarily effective against malicious acts. Moreover, even if cyber-threats can be contained, significant costs will be incurred whenever operations have to shut down in response to a cyber-attack. As there are important gaps in Industrial Control Systems, they have increasingly been targeted over the past decade, creating concern among the cyber-security and the process control engineering communities. Operators may be reluctant or unable to implement standard cyber-security controls in this type of systems because they might interfere with time-sensitive control loops, interrupt continuous operation or potentially compromise safety. This situation calls for a more proactive approach to monitor cyber-risks since many of them cannot be totally eliminated or properly controlled by preventative measures. Traditional risk management approaches do not address this, since they are not conceived to work at the same speed that changes can occur in cyber-security operations. This thesis aims to facilitate the adoption of Continuous Risk Management in industrial networks by proposing a risk assessment methodology focused mainly on the aspect of risk likelihood updates. The approach proposed is based on a Continuous Risk Assessment Methodology, which is derived from a typical Risk Management process and modified to work in a continuous basis. The methodology consists of workflows and a description of each process involved, including its inputs and outputs. Additionally, a number of resources to support the implementation of the methodology on industrial environments were developed. These resources consist of the introduction and categorisation of the concept of “Indicator of Risk” (IoR), a knowledge base, containing a set of different categories of IoRs, named as the “IoR Library” and the implementation of this knowledge base on a Bayesian Network template. Finally, behavioural anomaly detection using sensors data is demonstrated to illustrate the use of IoRs based on data from physical processes as a resource to detect possible cyber-risks. These resources provided concrete means to address issues in industrial cyber-security risk management such as the availability and quality of information, the complexity of defining rules and identifying normal and abnormal states, the limited scope of academic work, and the lack of integration between risk management and cyber-security operations