I obtained a B.S. in Computer Information Systems with an applied specialization in Criminal Justice and minor in English from John Jay College of Criminal Justice in June 2011. The courses I have taken have allowed me to learn the fundamentals of how to secure computers and their data. Based on my academic performance, I was accepted into my college's DHS Undergraduate Career Development Program funded by an HS-STEM Career Development Grant. This program provided me the opportunity to work in fields related to homeland security and conduct research related to anomaly detection and cyber security under the guidance of both Dr. James Abello and Dr. Bilal Khan who are active in this research area. Upon concluding my summer internship with DIMACS/ CCICADA, I hope to have a career related to cyber security or computer forensics.
This project addresses the problem of finding persistent patterns in
evolving networks. A central question is the
characterization of patterns that can be used as the basis
to detect anomalous activities in time-evolving
networks. One of the datasets we will be working with is data from Twitter.
Mentor: Dr. James Abello
A joint project between myself and Maria Taranov
I began this week by familiarizing myself with ASK-GraphView and Cytoscape which are two programs used for graph visualization. I also reviewed research papers on graph visualization software, matrices, and tensors. I met with Dr. Abello and discussed our next step which involves creating a client-server architecture for a user (the client) to have the ability to use ASK-GraphView or Cytoscape to select any node in a given graph and assign it to a new cluster. The necessary changes would then be sent to the server where a graph algorithm will be applied to calculate any new edges or vertices. The server would then create a new file with the node changes and send it back to the client.
I created two very basic client-server programs using C which simply allows the client to send a message to the server while the server responds to every message it receives. By the end of this week, I will be modifying these programs so that they are capable of sending and receiving actual files that contain graph information. In addition, Dr. Abello informed me that we will be detecting anomalies in data from Twitter. I am currently working on finding a good API capable of obtaining Twitter data. In the meantime, a graduate student at DIMACS provided me with a sample of Twitter data already graphed in ASK-GraphView so that I can begin looking for patterns in "retweets" and "Twitter hashtags".
I found an API capable of retrieving Twitter data from users whos tweet contains a specific search term. The following data is retrieved:
I was able to get my C++ program to read the Twitter data and format it into an undirected graph in which the username is the source node, the Tweet message is the destination node, and the timestamp is the edge/ interaction. In addition, Maria and I obtained a Java program which is able to read the undirected graph outputted by my C++ program and place the edges and vertices into clusters using network modularity function. In the meantime, Maria is working on a Java program which will calculate the membership ratio for each of the clusters. This is all being done so that we can effectively find patterns and anomalies in Twitter networks.
Coming Soon...
The ability to monitor normal and abnormal network
traffic in real time is vital since a network attack can
occur and be completed in seconds. One novel way to render
network traffic is through its acoustic representation. The
Centaur project (Centralized
Auralization) explores dynamic sonic
interpretation of live TCP/IP network packets as musical
notes of varying pitch, volume, duration and instrumentation. Centaur
renders a stream of TCP packets in a manner that reflects
the system's continuously updated beliefs concerning the
network state, e.g. whether a “port
scan” or “distributed denial of service attack” (DDoS) is
taking place. Additionally, the system is capable of
mapping normal web traffic contents into musical notes. Multiple
Centaur sensors can be deployed to monitor machines across
the wide area Internet; a central Centaur server receives musical note
commands over the network from deployed sensors. The advantage of this architecture is that the guarded
machines need not cohabit the same local area network (LAN). Future work will
evaluate the extent to which such acoustic renderings
enable administrators to more effectively (and viscerally)
sense shifts in patterns of network utilization.
Mentor: Dr. Bilal Khan
This project involves the design and development of
a multi-user multi-role web-based system that will be
utilized by John Jay College's PRISM Program. PRISM offers
mentoring and stipends to undergraduate students with
research interests relating to science. The project's aim
was to enable students to search and apply online for
PRISM-related opportunities instead of requiring
paperwork. Once a student uploads their application,
references can submit their recommendation letters
electronically. In addition, mentors have access to the
website to approve students/projects they wish to
supervise. Once all of the components of the student's
application are completed, the reviewers can evaluate the
full application and submit their decision. This project
makes use of a MySQL database which stores user
information, application data, and active solicitations
that PRISM chooses to make available to students. The
website itself, designed with HTML, PHP, Javascript, and
CSS, allows users to upload, download, view, and submit
data to PRISM
Mentor: Dr. Bilal Khan
A joint project between myself and Mateusz Opalinski
