The Proceedings of 14th Australian Digital Forensics Conference, 5-6 December 2016, Edith Cowan University, Perth, Australia

Conference Foreword This is the fifth year that the Australian Digital Forensics Conference has been held under the banner of the Security Research Institute, which is in part due to the success of the security conference program at ECU. As with previous years, the conference continues to see a quality papers with a number from local and international authors. 11 papers were submitted and following a double blind peer review process, 8 were accepted for final presentation and publication. Conferences such as these are simply not possible without willing volunteers who follow through with the commitment they have initially made, and I would like to take this opportunity to thank the conference committee for their tireless efforts in this regard. These efforts have included but not been limited to the reviewing and editing of the conference papers, and helping with the planning, organisation and execution of the conference. Particular thanks go to those international reviewers who took the time to review papers for the conference, irrespective of the fact that they are unable to attend this year. To our sponsors and supporters a vote of thanks for both the financial and moral support provided to the conference. Finally, to the student volunteers and staff of the ECU Security Research Institute, your efforts as always are appreciated and invaluable. Yours sincerely, Conference Chair Professor Craig Valli Director, Security Research Institut

Understanding and Improving the Performance of Read Operations Across the Storage Stack

We live in a data-driven era, large amounts of data are generated and collected every day. Storage systems are the backbone of this era, as they store and retrieve data. To cope with increasing data demands (e.g., diversity, scalability), storage systems are experiencing changes across the stack. As other computer systems, storage systems rely on layering and modularity, to allow rapid development. Unfortunately, this can hinder performance clarity and introduce degradations (e.g., tail latency), due to unexpected interactions between components of the stack. In this thesis, we first perform a study to understand the behavior across different layers of the storage stack. We focus on sequential read workloads, a common I/O pattern in distributed le systems (e.g., HDFS, GFS). We analyze the interaction between read workloads, local le systems (i.e., ext4), and storage media (i.e., SSDs). We perform the same experiment over different periods of time (e.g., le lifetime). We uncover 3 slowdowns, all of which occur in the lower layers. When combined, these slowdowns can degrade throughput by 30%. We find that increased parallelism on the local le system mitigates these slowdowns, showing the need for adaptability in storage stacks. Given the fact that performance instabilities can occur at any layer of the stack, it is important that upper-layer systems are able to react. We propose smart hedging, a novel technique to manage high-percentile (tail) latency variations in read operations. Smart hedging considers production challenges, such as massive scalability, heterogeneity, and ease of deployment and maintainability. Our technique establishes a dynamic threshold by tracking latencies on the client-side. If a read operation exceeds the threshold, a new hedged request is issued, in an exponential back-off manner. We implement our technique in HDFS and evaluate it on 70k servers in 3 datacenters. Our technique reduces average tail latency, without generating excessive system load

Internet of Things From Hype to Reality

The Internet of Things (IoT) has gained significant mindshare, let alone attention, in academia and the industry especially over the past few years. The reasons behind this interest are the potential capabilities that IoT promises to offer. On the personal level, it paints a picture of a future world where all the things in our ambient environment are connected to the Internet and seamlessly communicate with each other to operate intelligently. The ultimate goal is to enable objects around us to efficiently sense our surroundings, inexpensively communicate, and ultimately create a better environment for us: one where everyday objects act based on what we need and like without explicit instructions

Big data analytics for large-scale wireless networks: Challenges and opportunities

© 2019 Association for Computing Machinery. The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large-scale wireless networks. Big data of large-scale wireless networks has the key features of wide variety, high volume, real-time velocity, and huge value leading to the unique research challenges that are different from existing computing systems. In this article, we present a survey of the state-of-art big data analytics (BDA) approaches for large-scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage, and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large-scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area

Combining Edge Computing and Data Processing with Kubernetes

The objective of this thesis is to explore and expand on cutting edge concepts that have been introduced in the coursework during this bachelor's degree. In particular, we will be going into the world of distributed and "Cloud Computing", including the use of "Internet of Things" devices. We will also demonstrate our use case scenario implementing "Artificial Intelligence" concepts, including building and configuring a Neural Network. In more detail, we explore how a computer cluster is built, scaling an application throughout an array of connected computers, building such applications on containers, and deploying them into the cluster. To build our use case scenario we will be developing an intelligent temperature control system that uses AI to determine the future temperature and using that prediction to reduce network congestion. This temperature control system and its other supporting applications will be run on the computer cluster and its performance will be evaluated.Grado en Ingeniería Informátic

Computer Science's Digest Volume 3

This series of textbooks was created for the students of the Systems Engineering Program at the University of Nariño. They have been intentionally written in English to promote reading in a foreign language. The textbooks are a collection of reflections and workshops on specific situations in the field of computer science, based on the authors’ experiences. The main purpose of these textbooks is essentially academic. The way in which the reflections and workshops were constructed follows a didactic structure, to facilitate teaching and learning, making use of English as a second language. This book covers Professional Issues in Computing and Programming the Interne

BLOCKGRID: A BLOCKCHAIN-MEDIATED CYBER-PHYSICAL INSTRUCTIONAL PLATFORM

Includes supplementary material, which may be found at https://calhoun.nps.edu/handle/10945/66767Blockchain technology has garnered significant attention for its disruptive potential in several domains of national security interest. For the United States government to meet the challenge of incorporating blockchain technology into its IT infrastructure and cyber warfare strategy, personnel must be educated about blockchain technology and its applications. This thesis presents both the design and prototype implementation for a blockchain-mediated cyber-physical system called a BlockGrid. The system consists of a cluster of microcomputers that form a simple smart grid controlled by smart contracts on a private blockchain. The microcomputers act as private blockchain nodes and are programmed to activate microcomputer-attached circuits in response to smart-contract transactions. LEDs are used as visible circuit elements that serve as indicators of the blockchain’s activity and allow demonstration of the technology to observers. Innovations in networking configuration and physical layout allow the prototype to be highly portable and pre-configured for use upon assembly. Implementation options allow the use of BlockGrid in a variety of instructional settings, thus increasing its potential benefit to educators.Civilian, CyberCorps: Scholarship for ServiceApproved for public release. distribution is unlimite