A user-centered approach to road design : blending distributed situation awareness with self-explaining roads

Driving is a complex dynamic task. As the car driver drives along a route they have to adjust their driving technique in accordance with the traffic level, infrastructure and environment around them. The amount of information in the environment would be overwhelming were it not for the presence of stored mental templates, accumulated through training and experience, which become active when certain features are encountered. Problems occur when the environment triggers the incorrect templates, or fails to trigger the correct templates. Problems like these can be overcome by adopting a “self-explaining” (SER) approach to road design. That is to say, purposefully designed roads which trigger correct behaviour. A concept which can help improve the theoretical robustness of the SER approach is Situation Awareness (SA). SA describes how the environment and mental templates work together to ensure drivers remain coupled to the dynamics of their situation. It is a widely researched concept in the field of Human Factors but not in the domain of Self-Explaining Roads (SER), despite the very obvious conceptual overlaps. This thesis, for the first time, blends the two approaches, SA and SER, together. From this the ability to extract cognitively salient features and ability to enhance driving behaviour and their effects on driving behaviour are sufficiently enhanced. After establishing SA as critical to driving through literature review the experiment phase started with determining the source of driver SA. Road environment was found to be of utmost importance for feeding into driver SA. This was also confirmed with the results of the on-road exploratory study. The success of the exploratory study led to large scale naturalistic study. It provided data on driver mental workload, subjective situation awareness, speed profile and endemic feature. Endemic features are unique characteristics of a road which make a road what it is. It was found that not all endemic features contribute to SA of a road system. Therefore through social network analysis list of cognitive salient features were derived. It is these cognitive salient features which hold compatible SA and facilitate SA transaction in a road system. These features were found to reduce speed variance among drivers on a road. The thesis ends by proposing a ‘road drivability tool’ which can predict potentially dangerous zones. Overall, the findings contribute to new imaginative ways road design in order to maximize safety and efficiency

Capturing Malware Behaviour with Ontology-based Knowledge Graphs

Exponential rise of Internet increases the risk of cyber attack related incidents which are generally caused by wide spread frequency of new malware generation. Different types of malware families have complex, dynamic behaviours and characteristics which can cause a novel and targeted attack in a cyber-system. Existence of large volume of malware types with frequent new additions hinders cyber resilience effort. To address the gap, we propose a new ontology driven framework that captures recent malware behaviours. According to code structure malware can be divided into three categories: basic, polymorphic and metamorphic. Packing or code obfuscation is also a technique adopted by the malware developers to make the code unreadable and avoid detection. Given that ontology techniques are useful to express the domain knowledge meaningfully , this paper aims to develop an ontology for dynamic analysis of malware behaviour and to capture metamorphic and polymorphic malware behaviour. This will be helpful to understand malicious behaviour exhibited by new generation malware samples and changes in their code structure. The proposed framework includes 14 malware families with their sub-families and 3 types of malware code-structure with their individuals. With a focus on malware behaviour the proposed ontology depicts the relations among malware families and malware code-structures with their respective behaviour.Output Status: Forthcomin

Capturing Malware Behaviour with Ontology-based Knowledge Graphs

Exponential rise of Internet increases the risk of cyber attack related incidents which are generally caused by wide spread frequency of new malware generation. Different types of malware families have complex, dynamic behaviours and characteristics which can cause a novel and targeted attack in a cyber-system. Existence of large volume of malware types with frequent new additions hinders cyber resilience effort. To address the gap, we propose a new ontology driven framework that captures recent malware behaviours. According to code structure malware can be divided into three categories: basic, polymorphic and metamorphic. Packing or code obfuscation is also a technique adopted by the malware developers to make the code unreadable and avoid detection. Given that ontology techniques are useful to express the domain knowledge meaningfully , this paper aims to develop an ontology for dynamic analysis of malware behaviour and to capture metamorphic and polymorphic malware behaviour. This will be helpful to understand malicious behaviour exhibited by new generation malware samples and changes in their code structure. The proposed framework includes 14 malware families with their sub-families and 3 types of malware code-structure with their individuals. With a focus on malware behaviour the proposed ontology depicts the relations among malware families and malware code-structures with their respective behaviour

Self explaining roads and situation awareness

This paper places theories of SA into contact with the issue of Self Explaining Roads. Twelve drivers took part in an on-road study and performed a verbal commentary as they drove around a defined test route. The verbal transcripts were partitioned into six road types, and driver SA was modeled using semantic networks. The content and structure of these networks was analysed and cognitively salient endemic road features were extracted. These were then compared with aspects of driver behaviour. The findings highlight the systemic nature of the driver–vehicle–road interaction, and show that SA is highly contingent on road type. The findings also reveal that motorways/freeways are the most cognitively compatible road type and that incompatibilities grow rapidly as road types become increasingly minor and less overtly ‘designed’. The paper is exploratory in nature but succeeds in innovating a theoretically robust means of examining road environments under naturalistic conditions. It also succeeds in providing numerous insights and hypotheses for a developing program of work

A Review of Human Reliability Programs for Nuclear Security

Human Reliability Program (HRP) is a set of procedures, protocols, and the corresponding performance of activities to support and sustain the secure and safe operation of a facility. Our review indicated that HRP is referred to by various names, such as, Personnel Reliability Program (PRP), Trustworthiness Program, and Fitness for Duty Program, with PRP being the most common amongst them. A brief description of the evolution of HRP and its components for Finland, Japan, Jordan, Nigeria, Russia, US, and UK is provided. Details of the Trustworthiness Program by the International Atomic Energy Agency are also provided. Most of the HRPs have similar components and implementation steps with few variations, and they all have identical objectives. Even though a structured HRP may not exist in Indian civil nuclear energy facilities, an account of various HRP components practiced in India is discussed. The HRP review provided should help security practitioners and academics