The JHU Department of Computer Science is a department within the Whiting School of Engineering. While studies and research cover a very wide area, there are five main research interests:
Algorithms – A core area and long-standing strength of the department, dating from before the department’s formation. Robotics, Vision, and Graphics – Much of the research in these areas, which involve 3-D computer modeling, is done within the Center for Computer-Integrated Surgical Systems and Technology (CISST). Related research includes human-computer interaction, and shape recognition and shape matching. Security – This is an incredibly broad area and research, focused within the JHU Information Security Institute, involves many aspects of computer and network security. Systems – This core research area grapples with improving operating systems and data storage and defining higher standards for security evaluation. Natural Language Processing – This concerns enabling computers to work more effectively with human languages, identifying input strings and corresponding output, defining correlations between text and speech, form and content, syntax and translations. The Center for Language and Speech Processing (CLSP) is centrally involved with this work.
(2013-12-11T20:33:59Z) Rubin, Aviel D.; Green, Matthew; Checkoway, Stephen; Rushanan, Michael; Martin, Paul D.
A new technique is presented for identifying the implementation version number of software that is used for Internet communications. While many programs may exchange version numbers, oftentimes only a small subset of them send any information at all. Furthermore, they usually do not provide accurate details about which implementation is used. We use machine learning techniques to build a feature database and then apply this to network traffic to try to identify specific implementations on servers. We apply our technique to OpenSSL and report our results.
(2013-12-11T20:32:51Z) Brocker, Matthew; Checkoway, Stephen
The ubiquitous webcam indicator LED is an important privacy feature which provides a visual cue that the camera is turned on. We describe how to disable the LED on a class of Apple internal iSight webcams used in some versions of MacBook laptops and iMac desktops. This enables video to be captured without any visual indication to the user and can be accomplished entirely in user space by an unprivileged (non- root) application.
The same technique that allows us to disable the LED, namely reprogramming the firmware that runs on the iSight, enables a virtual machine escape whereby malware running inside a virtual machine reprograms the camera to act as a USB Human Interface Device (HID) keyboard which executes code in the host operating system.
We build two proofs-of-concept: (1) an OS X application, iSeeYou, which demonstrates capturing video with the LED disabled; and (2) a virtual machine escape that launches Terminal.app and runs shell commands. To defend against these and related threats, we build an OS X kernel extension, iSightDefender, which prohibits the modification of the iSight’s firmware from user space.