451,859 research outputs found
Recommended from our members
CONVERGING REDUNDANT SENSOR NETWORK INFORMATION FOR IMPROVED BUILDING CONTROL
Knowing how many people occupy a building, and where they are located, is a key component of building energy management and security. Commercial, industrial and residential buildings often incorporate systems used to determine occupancy, however, current sensor technology and control algorithms limit the effectiveness of both energy management and security systems. This topical report describes results from the first phase of a project to design, implement, validate, and prototype new technologies to monitor occupancy, control indoor environment services, and promote security in buildings. Phase I of the project focused on instrumentation and data collection. In this project phase a new occupancy detection system was developed, commissioned and installed in a sample of private offices and open-plan office workstations. Data acquisition systems were developed and deployed to collect data on space occupancy profiles. Analysis tools based on Bayesian probability theory were applied to the occupancy data generated by the sensor network. The inference of primary importance is a probability distribution over the number of occupants and their locations in a building, given past and present sensor measurements. Inferences were computed for occupancy and its temporal persistence in individual offices as well as the persistence of sensor status. The raw sensor data were also used to calibrate the sensor belief network, including the occupancy transition matrix used in the Markov model, sensor sensitivity, and sensor failure models. This study shows that the belief network framework can be applied to the analysis of data streams from sensor networks, offering significant benefits to building operation compared to current practice
xLED: Covert Data Exfiltration from Air-Gapped Networks via Router LEDs
In this paper we show how attackers can covertly leak data (e.g., encryption
keys, passwords and files) from highly secure or air-gapped networks via the
row of status LEDs that exists in networking equipment such as LAN switches and
routers. Although it is known that some network equipment emanates optical
signals correlated with the information being processed by the device
('side-channel'), intentionally controlling the status LEDs to carry any type
of data ('covert-channel') has never studied before. A malicious code is
executed on the LAN switch or router, allowing full control of the status LEDs.
Sensitive data can be encoded and modulated over the blinking of the LEDs. The
generated signals can then be recorded by various types of remote cameras and
optical sensors. We provide the technical background on the internal
architecture of switches and routers (at both the hardware and software level)
which enables this type of attack. We also present amplitude and frequency
based modulation and encoding schemas, along with a simple transmission
protocol. We implement a prototype of an exfiltration malware and discuss its
design and implementation. We evaluate this method with a few routers and
different types of LEDs. In addition, we tested various receivers including
remote cameras, security cameras, smartphone cameras, and optical sensors, and
also discuss different detection and prevention countermeasures. Our experiment
shows that sensitive data can be covertly leaked via the status LEDs of
switches and routers at a bit rates of 10 bit/sec to more than 1Kbit/sec per
LED
ETS (Efficient, Transparent, and Secured) Self-healing Service for Pervasive Computing Applications
To ensure smooth functioning of numerous handheld devices anywhere anytime, the importance of self-healing mechanism cannot be overlooked. Incorporation of efficient fault detection and recovery in device itself is the quest for long but there is no existing self-healing scheme for devices running in pervasive computing environments that can be claimed as the ultimate solution. Moreover, the highest degree of transparency, security and privacy attainability should also be maintained. ETS Self-healing service, an integral part of our developing middleware named MARKS (Middleware Adaptability for Resource discovery, Knowledge usability, and Self-healing), holds promise for offering all of those functionalities
- ā¦