Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective

Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT) networks, which can be mostly attributed to the increasing communication and sensing capabilities of wireless systems. Big data analysis, pervasive computing, and eventually artificial intelligence (AI) are envisaged to be deployed on top of the IoT and create a new world featured by data-driven AI. In this context, a novel paradigm of merging AI and wireless communications, called Wireless AI that pushes AI frontiers to the network edge, is widely regarded as a key enabler for future intelligent network evolution. To this end, we present a comprehensive survey of the latest studies in wireless AI from the data-driven perspective. Specifically, we first propose a novel Wireless AI architecture that covers five key data-driven AI themes in wireless networks, including Sensing AI, Network Device AI, Access AI, User Device AI and Data-provenance AI. Then, for each data-driven AI theme, we present an overview on the use of AI approaches to solve the emerging data-related problems and show how AI can empower wireless network functionalities. Particularly, compared to the other related survey papers, we provide an in-depth discussion on the Wireless AI applications in various data-driven domains wherein AI proves extremely useful for wireless network design and optimization. Finally, research challenges and future visions are also discussed to spur further research in this promising area.Comment: Accepted at the IEEE Communications Surveys & Tutorials, 42 page

VoipLoc : VoIP call provenance using acoustic side-channels

We develop a novel technique to determine call provenance in anonymous VoIP communications using acoustic side-channels. The technique exploits location-attributable information embedded within audio speech data. The victim’s speech is exploited as an excitation signal, which is modulated (acted upon) by the acoustic reflection characteristics of the victim’s location. We show that leading VoIP communication channels faithfully transfer this information between sender-receiver pairs, enabling passive receivers to extract a location fingerprint, to establish call provenance. To establish provenance, a fingerprint is compared against a database of labelled fingerprints to identify a match. The technique is fully passive and does not depend on any characteristic background sounds, is speaker independent, and is robust to lossy network conditions. Evaluation using a corpus of recordings of VoIP conversations, over the Tor network, confirms that recording locations can be fingerprinted and detected remotely with low false-positive rate

Air Force Institute of Technology Research Report 2014

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Air Force Institute of Technology Research Report 2012

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Air Force Institute of Technology Research Report 2015

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Emerging Security Threats in Modern Digital Computing Systems: A Power Management Perspective

Design of computing systems — from pocket-sized smart phones to massive cloud based data-centers — have one common daunting challenge : minimizing the power consumption. In this effort, power management sector is undergoing a rapid and profound transformation to promote clean and energy proportional computing. At the hardware end of system design, there is proliferation of specialized, feature rich and complex power management hardware components. Similarly, in the software design layer complex power management suites are growing rapidly. Concurrent to this development, there has been an upsurge in the integration of third-party components to counter the pressures of shorter time-to-market. These trends collectively raise serious concerns about trust and security of power management solutions. In recent times, problems such as overheating, performance degradation and poor battery life, have dogged the mobile devices market, including the infamous recall of Samsung Note 7. Power outage in the data-center of a major airline left innumerable passengers stranded, with thousands of canceled flights costing over 100 million dollars. This research examines whether such events of unintentional reliability failure, can be replicated using targeted attacks by exploiting the security loopholes in the complex power management infrastructure of a computing system. At its core, this research answers an imminent research question: How can system designers ensure secure and reliable operation of third-party power management units? Specifically, this work investigates possible attack vectors, and novel non-invasive detection and defense mechanisms to safeguard system against malicious power attacks. By a joint exploration of the threat model and techniques to seamlessly detect and protect against power attacks, this project can have a lasting impact, by enabling the design of secure and cost-effective next generation hardware platforms

Air Force Institute of Technology Research Report 2015

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics