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Milestone of Student Research Projects

Milestone of Research Projects


Note that the following projects are conducted by Cybersecurity MS/BS students.
  • Secure Sensor Network: Finding Objects for Layout Generation

    • Abstract
      This project aims at identifying an object while a robot is moving in
      the previous unknown/never-recognized zone where there is no GPS information
      available.
      The robots, e.g., RC vehicles equipped with proximity sensors, XBee transcrivers,
      distance sensors, etc, are moving in such an area to figure out
      the layout of the zone.
      For example, in a closed area, inlets and outlets are finally recognized along
      with the walls surrounding.
    • Student: Juan Ortiz and James Markward
    Locating an object from human un-attended environments, e.g., caves or nuclear radiators
  • Secure Sensor Network: Mining Wireless Sensor Data

    • Abstract
      As smartphones become an emerging interface platform between humans and systems,
      they also enable wireless sensors to interface with host servers.
      As sensors monitor application domains and sensor data is frequently polled and
      transmitted to a host server,
      the server data will be a big volume, big variety and big velocity,
      which is the characteristic of big data.
      Mining patterns from big data is a very important and active research topic
      since it can be used to forecast and β€œnowcast” for any dynamisms in application domains.
      However, typical data mining algorithms are not successful yet due to
      the characteristics of big data.
      This project proposes three-tied data mining paradigm.
      Alongside the streamline of sensor data transmission,
      at the microcontroller tier, sensor data sets are mined to form patterns,
      at the smartphone tier, negative and positive patterns are grouped and verified,
      and finally at the host server tier, human expertise is associated with the patterns.
      The contribution includes 1) lowering data transmission by mining from the lower tiers,
      2) mining time-critical data earlier than it would be done at the host server tier and
      3) hence urgent responses can be made timely at the proper tier.
    • Student: Juan Ortiz and James Markward
    Sensor networks over Arduinos
    Sensor networks over Arduinos
    Sensor networks over Memsic
  • Secure Sensor Network: Collaboration Sensing of Acoustic and Time

    • Abstract
      This project aims at identifying the origin source of an incident which
      generates a noise and which will be reported by surveillance cameras.
      In typical situations, surveillance cameras continue to take video sceans
      and transmit to a back-end server. Since an event or an accident occurs
      in-frequently, unnecessarily overwelmingly many video scenes are transmitted.
      We want to let our sensors identify the noises that come from the incident location.
      Then, the sensors trigger the surveillance cameras to pan and tilt to locate
      the incident and start sending video images.
    • Student: Juan Ortiz and James Markward
    Setting up Arduinos on Moving Objects

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    Configuring Sensors with Arduinos on Moving Objects

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    Configuring Sensors with Arduinos on Moving Objects

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  • Secured Network: Detecting Streaming Packet Data

    • Abstract
      GEMMA IDS is an Intrusion Detection System, signature-based,
      to detect the network packets of intrusive attacks.
      The system employs a low powered computational device as network sensors to
      detect intrusions over the Wi-Fi and wired networks.
      It is implemented in Python 3.4 on Windows 7 and Linux and
      the detective mechanism is developed by both Snort rules and its dialects.
      Selecting the option to save the logs in the internal memory or
      in a centralized shared location. The payload is saved using
      the ASCII code format when possible otherwise the byte code
      with no ASCII representation is stored.
    • Student: Angel Roberto Contreras Tamez
    Matching Packets

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    Rulesets for Packet Matching

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    Contents of Matched Packets

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  • Securing Website: Crawling and Detecting Webpages

    • Abstract
      It is well known that malicious and suspicious data/message may be shared
      through the Internet webpages.
      This project aims at crawling webpages by webpages automatically to
      detect any suspicious data/text over the Internet.
      The extended work would be to detect images and videos from such webpages.
    Visit Websites

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    Read Webpages (also To Collect href Linked Addresses)

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  • Cryptography: RC4 & A51 Algorithms

    • Abstract
      This simple implementation of RC4 is to first generate a streaming key and then
      encrypt a given streaming data with the streaming key.
      RC4 algorithm is used for signal encryption in IEEE802.11 protocol. This implementation shows clearly
      the weakness of RC4.
      There is another implementation: A5/1 algorithm is implemented to generate
      a streaming key.
      A5/1 algorithm is used for cellular signal encryption in mobile networks.
      In the screen shot below are the two Algorithms, RC4 and A51.
    • Student:
  • Forensic Investigation: File Recovery

    • Abstract
      Computer Forensics has emerged as a critical component of the Law Enforcement and
      Federal Government investigatory process. Although Computer Forensics is seen as the
      "CSI" of the Computer science field, it is much more complex.
      One of the major investigation steps of computer forensics is to recover
      and restore deleted files.
      This project uses Python scripting language to recover
      deleted files in the following steps: 1) obtain the image of a target disk storage;
      2) read the image in hex; 3) scan the hex code of the header; and
      4) save the range of hex code,
      assuming that the hex code of the header and footer of a deleted file.
    • Student: Rebecca Bullard
    Capturing the Disk Image in Hex and Running the File Recovery Program (in Python)
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  • Forensic Investigation: Smartphone Investigation

    • Abstract
      One of the simple but massive processing for smartphone jpeg images is to
      script a program in Python.
      Since smartphone exif jpeg files contain GPS data including
      latitude, longitude, altitude and time, this Python script
      can collect them from one jpeg file at a time and save them in an output file.
    • Student:
    Scanning Metadata, including lattitude, longitude, altitude and time, by Python Scripting

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