Increasing the accessibility of NLP techniques for Defence and Security using a web-based tool

As machine learning becomes more common in defence and security, there is a real risk that the low accessibility of techniques to non-specialists will hinder the process of operationalising the technologies. This poster will present a tool to support a variety of Natural Language Processing (NLP) techniques including the management of corpora – data sets of documents used for NLP tasks, creating and training models, in addition to visualising the output of the models. The aim of this tool is to allow non-specialists to exploit complex NLP techniques to understand the content of large volumes of reports.NLP techniques are the mechanisms by which a machine can process and analyse text written by humans. These methods can used for a range of tasks including categorising documents, translation and summarising text. For many of these tasks the ability to process and analyse large corpora of text is key. With current methods, the ability to manage corpora is rarely considered, instead relying on researchers and practitioners to do this manually in their file system. To train models, researchers use ad-hoc code directly, writing scripts or code and compiling or running them through an interpreter. These approaches can be a challenge when working in multidisciplinary fields, such as defence and security and cyber security. This is even more salient when delivering research where outputs may be operationalised and the accessibility can be a limiting factor in their deployment and use.We present a web interface that uses an asynchronous service-based architecture to enable non-specialists to easily manage multiple large corpora and create and operationalise a variety of different models – at this early stage we have focussed on one NLP technique, that of topic models.This tool-support has been created as part of a project considering the use of NLP to better understand reports of insider threat attacks. These are security incidents where the attacker is a member of staff or another trusted individual. Insider threat attacks are particularly difficult to defend against due to the level of access these individuals gain during the regular course of their employment. The wider use of these techniques would generate greater impact both tactically in defending against these attacks and strategically in developing policy and procedures. There are tools available, however they are often complex and perform a single-task, limiting their use. To generate maximum impact from our research we have developed this web-based software to make the tools more accessible, especially to non-specialist researchers, customers and potential users.Dst

A Computational Decipherment of Linear B

The mystery of the world’s undeciphered scripts continue to draw in amateurs and experts alike. Machine translation currently allows us to translate known languages and writing systems such as between English and French or between English and Greek but this technology could be used to unlock the mysteries of the past and computers may hold the key to the understanding of these scripts. This project is a reconstruction of the decipherment of the Linear B script using computational techniques. Computational decipherment is a very important field; many ancient languages remain undeciphered such as Linear A, Etruscan, Rongo Rongo in addition to other ciphers or unknown writing system such as the Voynich Manuscript. Advances in decipherment could reveal more about the ancient world and answer key archaeological questions. In addition to deciphering more languages decipherment techniques can be used to further enhance machine translation by allowing translation with smaller corpuses. This project has deciphered Linear B in 3 stages, like the original decipherment, with the assumption that we have all tablets available in the dataset. In the first stage, an unsupervised algorithm will be used to automatically find inflected nouns. In the second phase, the results of this algorithm will be used to create a grid of values where signs share vowels or consonants. In the final phase, we will use a genetic algorithm to suggest possible values using evidence from statistics and known values of similar and related signs

Increasing the accessibility of NLP techniques for Defence and Security using a web-based tool

As machine learning becomes more common in defence and security, there is a real risk that the low accessibility of techniques to non-specialists will hinder the process of operationalising the technologies. This poster will present a tool to support a variety of Natural Language Processing (NLP) techniques including the management of corpora – data sets of documents used for NLP tasks, creating and training models, in addition to visualising the output of the models. The aim of this tool is to allow non-specialists to exploit complex NLP techniques to understand the content of large volumes of reports. NLP techniques are the mechanisms by which a machine can process and analyse text written by humans. These methods can used for a range of tasks including categorising documents, translation and summarising text. For many of these tasks the ability to process and analyse large corpora of text is key. With current methods, the ability to manage corpora is rarely considered, instead relying on researchers and practitioners to do this manually in their file system. To train models, researchers use ad-hoc code directly, writing scripts or code and compiling or running them through an interpreter. These approaches can be a challenge when working in multidisciplinary fields, such as defence and security and cyber security. This is even more salient when delivering research where outputs may be operationalised and the accessibility can be a limiting factor in their deployment and use. We present a web interface that uses an asynchronous service-based architecture to enable non-specialists to easily manage multiple large corpora and create and operationalise a variety of different models – at this early stage we have focussed on one NLP technique, that of topic models. This tool-support has been created as part of a project considering the use of NLP to better understand reports of insider threat attacks. These are security incidents where the attacker is a member of staff or another trusted individual. Insider threat attacks are particularly difficult to defend against due to the level of access these individuals gain during the regular course of their employment. The wider use of these techniques would generate greater impact both tactically in defending against these attacks and strategically in developing policy and procedures. There are tools available, however they are often complex and perform a single-task, limiting their use. To generate maximum impact from our research we have developed this web-based software to make the tools more accessible, especially to non-specialist researchers, customers and potential users

Interlinked Computing in 2040 : Safety, Truth, Ownership and Accountability

Computer systems are increasingly linked together, with systems controlled by different parties cooperating to deliver services. Such links offer both huge benefits and possible risks. Both the potential benefits and risks may be magnified as novel technologies such as Artificial Intelligence are integrated into these toolchains. What are these risks, and how might we begin to address them? Using a Delphi-based method, we interviewed twelve experts at envisaging technology futures to gain insight into likely trends, their impact on society, and how we might start to mitigate negative impacts. From the results, we highlight five forecasts, and six possible interventions that could help. The forecasts include major challenges related to Artificial Intelligence and system complexity, particularly where these involve interactions between independent systems. Addressing these challenges using the suggested interventions offers a good strategy to prepare ourselves for 2040

An analysis of the writing of ‘suicide cult’ members

The infamous ‘Heaven’s Gate cult’ committed a mass suicide in 1995 believing members of the group would achieve salvation through bodily transformation and departure aboard UFOs. The group left a large volume of writing available as a book and a website which outlined their belief structure. This writing, largely by the group’s leaders Ti and Do, is supplemented by ‘exit statements’ written by the group members. We analysed these writings and demonstrated how the texts evolve from accessible texts for recruiting individuals into the group through more complex texts for cementing the belief structure and reinforcing the ingroup. We also identify differences in the ‘exit statements’ that demonstrate the ideas and concepts that gained traction with the group members

Security-Focused Prototyping: A Natural Precursor to Secure Development

Secure development is often thought of as a proactive approach to cyber security. Rather than building a technological solution and then securing it in retrospect, secure development strives to embed good security practices throughout the development process and reduce risk. Unfortunately, evidence suggests secure development is complex, costly, and limited in practice. This article therefore introduces security-focused prototyping as a natural precursor to secure development. Security-focused prototyping embeds security at the beginning of the development process, can be used to discover domain-specific security requirements through active learning, and can help communicate the complexity of secure development to organizations such that the resources and commitment it requires are better understood. A case study considering the application layer of an Internet of Things system is presented and shows that security-focused prototyping has the potential to facilitate further secure development through the achievement of well-established prototyping objectives, such as communication, active learning, and reduced time/costs. Future work could build on this work by conducting additional case studies to further explore the potential of security-focused prototyping and investigating the importance of fidelity with regards to security-focused prototypes

Interlinked Computing : Initial Forecasts

Our project explores the future of interlinked computing: how connections, networks and grids between many independent, separately owned, systems, will work together. Based on nine interviews with expert futurists as the first step in a Delphi study, we offer these possible forecasts for comments. They are in the form of statements, both predictions, and concerns needing research now