Cyber Data Anomaly Detection Using Autoencoder Neural Networks

The Department of Defense requires a secure presence in the cyber domain to successfully execute its stated mission of deterring war and protecting the security of the United States. With potentially millions of logged network events occurring on defended networks daily, a limited staff of cyber analysts require the capability to identify novel network actions for security adjudication. The detection methodology proposed uses an autoencoder neural network optimized via design of experiments for the identification of anomalous network events. Once trained, each logged network event is analyzed by the neural network and assigned an outlier score. The network events with the largest outlier scores are anomalous and worthy of further review by cyber analysts. This neural network approach can operate in conjunction with alternate tools for outlier detection, enhancing the overall anomaly detection capability of cyber analysts

BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK

With the explosive development of the critical services network systems and Internet, the need for networks security systems have become even critical with the enlargement of information technology in everyday life. Intrusion Prevention System (IPS) provides an in-line mechanism focus on identifying and blocking malicious network activity in real time. This thesis presents new intrusion prevention and self-healing system (SH) for critical services network security. The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. Firstly, the current intrusions preventions systems, biological innate and adaptive immune systems, autonomic computing and self-healing mechanisms are studied and analyzed. The importance of intrusion prevention system recommends that artificial immune systems (AIS) should incorporate abstraction models from innate, adaptive immune system, pattern recognition, machine learning and self-healing mechanisms to present autonomous IPS system with fast and high accurate detection and prevention performance and survivability for critical services network system. Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. Finally, the validation of the system carried out by simulation tests, measuring, benchmarking and comparative studies. New benchmarking metrics for detection capabilities, prevention predictability trust and self-healing reliability are introduced as contributions for the IPS and SH system measuring and validation. Using the software system, design theories, AIS features, new nonlinear classification algorithm, and self-healing system show how the use of presented systems can ensure safety for critical services networks and heal the damage caused by intrusion. This autonomous system improves the performance of the current intrusion prevention system and carries on system continuity by using self-healing mechanism

Normalization in World Politics

The imposition of normalcy on fragile states and crises and its implications for world politics

Normalization in World Politics

The imposition of normalcy on fragile states and crises and its implications for world politics

The Maritime Archaeology of West Africa in the Atlantic World: Investigations at Elmina, Ghana

This dissertation focuses on the first maritime archaeology research project conducted in Ghana, specifically off the town of Elmina in the Central Region. Survey and diver investigations resulted in the discovery of a mid-seventeenth century shipwreck, which archaeological and archival research suggests may be the Dutch West India Company vessel Groeningen that sank after arriving to Elmina on a trading voyage in 1647. The site lies approximately 2.4 kilometers (1.5 miles) southeast of Elmina and is characterized by a mass of trade goods, including brass and pewter basins, brass manillas, lead rolls, trade beads, pins, cowrie shells, as well as large iron cannons. I utilize a multi-scalar approach in this research, which allows me to take the shipwreck as the basic unit of analysis (an event or événement as Braudel would place it in his three scales of history), and situate it within the broader sphere of the Atlantic World. This geographical and chronological construction, encompassing Africa, Europe and the Americas and spanning the fifteenth to the nineteenth centuries, can be considered an example of the longue dureé as defined by the Annales school, a level of analysis involved with long term structures and world views. In utilizing these multi-scalar constructs, the Elmina Wreck serves as an example of the maritime element within the interconnections of the Atlantic World. Artifacts from the wreck site provide insights into the commodities involved in exchange between Africans and Europeans on the coast, and speak to the culture contact and flow of commodities across different cultural contexts

Unsupervised Intrusion Detection with Cross-Domain Artificial Intelligence Methods

Cybercrime is a major concern for corporations, business owners, governments and citizens, and it continues to grow in spite of increasing investments in security and fraud prevention. The main challenges in this research field are: being able to detect unknown attacks, and reducing the false positive ratio. The aim of this research work was to target both problems by leveraging four artificial intelligence techniques. The first technique is a novel unsupervised learning method based on skip-gram modeling. It was designed, developed and tested against a public dataset with popular intrusion patterns. A high accuracy and a low false positive rate were achieved without prior knowledge of attack patterns. The second technique is a novel unsupervised learning method based on topic modeling. It was applied to three related domains (network attacks, payments fraud, IoT malware traffic). A high accuracy was achieved in the three scenarios, even though the malicious activity significantly differs from one domain to the other. The third technique is a novel unsupervised learning method based on deep autoencoders, with feature selection performed by a supervised method, random forest. Obtained results showed that this technique can outperform other similar techniques. The fourth technique is based on an MLP neural network, and is applied to alert reduction in fraud prevention. This method automates manual reviews previously done by human experts, without significantly impacting accuracy

Silenced Bodies: (En)Gendering Syrian Refugee Insecurity in Lebanon

While there has been a shift in security studies from the security of states to that of people, realpolitik still takes place under the banner of an emerging discourse of ‘refugee crisis.’ Refugee insecurities are (en)gendered and experienced where their depth and breadth pose significant challenges to asylum seekers, neighboring host-states, and humanitarian agencies. To this end, this research captures the unique dynamics of a South-South refugee crisis in Lebanon, in which Syrians residents make up nearly one-third of its population. It applies a transnational feminist framework to trace how refugee security norms get defined, are managed, and how they impact local context. In effect, a gender lens enables an in-depth investigation of the day-to-day challenges Syrian refugee women experience and manage within an unreceptive environment that disproportionately affect their resilience efforts. Located at the intersection of Security Studies and Refugee scholarship, this dissertation provides a much-needed feminist approach that can bridge the tension between two paradigms previously perceived as exclusionary when exploring a transnational phenomenon such as forced migration. In a refugee-security context, an interdisciplinary study sheds light on how impromptu choices made by involved bodies—such as the Lebanese government and the UNHCR—can significantly impact local realities, creating a vicious cycle of refugee insecurities. This research, thus, addresses the political, socio-cultural, and organizational dynamics that disproportionately affect the majority of registered Syrian refugees in Lebanon: Syrian women. It utilizes several tools, including expert interviews, in-depth longitudinal cultural-theme analysis, and an action-oriented participatory method called Photovoice. These tools help this research explore the multi-layeredness of Syrian refugee (in)security in Lebanon with structural and gendered implications. Hence, this study adds to the critical knowledge from Security Studies, Refugee Protection Regimes, and Women’s and Gender Studies, serving as a useful tool for future projects on the contested politics of refugee (in)security and gender practices

Extimate Technology

"This book investigates how we should form ourselves in a world saturated with technologies that are profoundly intruding in the very fabric of our selfhood.　 New and emerging technologies, such as smart technological environments, imaging technologies and smart drugs, are increasingly shaping who and what we are and influencing who we ought to be. How should we adequately understand, evaluate and appreciate this development? Tackling this question requires going beyond the persistent and stubborn inside-outside dualism and recognizing that what we consider our ""inside"" self is to a great extent shaped by our ""outside"" world. Inspired by various philosophers – especially Nietzsche, Peirce and Lacan –this book shows how the values, goals and ideals that humans encounter in their environments not only shape their identities but also enable them to critically relate to their present state. The author argues against understanding technological self-formation in terms of making ourselves better, stronger and smarter. Rather, we should conceive it in terms of technological sublimation, which redefines the very notion of human enhancement. In this respect the author introduces an alternative, more suitable theory, namely Technological Sublimation Theory (TST). Extimate Technology will be of interest to scholars and advanced students working in philosophy of technology, philosophy of the self, phenomenology, pragmatism, and history of philosophy.

Extimate Technology

"This book investigates how we should form ourselves in a world saturated with technologies that are profoundly intruding in the very fabric of our selfhood.　 New and emerging technologies, such as smart technological environments, imaging technologies and smart drugs, are increasingly shaping who and what we are and influencing who we ought to be. How should we adequately understand, evaluate and appreciate this development? Tackling this question requires going beyond the persistent and stubborn inside-outside dualism and recognizing that what we consider our ""inside"" self is to a great extent shaped by our ""outside"" world. Inspired by various philosophers – especially Nietzsche, Peirce and Lacan –this book shows how the values, goals and ideals that humans encounter in their environments not only shape their identities but also enable them to critically relate to their present state. The author argues against understanding technological self-formation in terms of making ourselves better, stronger and smarter. Rather, we should conceive it in terms of technological sublimation, which redefines the very notion of human enhancement. In this respect the author introduces an alternative, more suitable theory, namely Technological Sublimation Theory (TST). Extimate Technology will be of interest to scholars and advanced students working in philosophy of technology, philosophy of the self, phenomenology, pragmatism, and history of philosophy.