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Found 8 papers, 0 papers with code
An Electric Vehicle Control Strategy to Mitigate Load Altering Attacks Against Power Grids
After the controller synthesis and presentation of the attack scenarios, we demonstrate the effectiveness and success of our defense mechanism against the three known types of LA attacks.
Dynamic Load Altering EV Attacks Against Power Grid Frequency Control
Driven by the necessity to combat climate change, Electric Vehicles (EV) are being deployed to take advantage of their ability in reducing emissions generated by the transportation sector.
DPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning
Outsourcing anomaly detection to third-parties can allow data owners to overcome resource constraints (e. g., in lightweight IoT devices), facilitate collaborative analysis (e. g., under distributed or multi-party scenarios), and benefit from lower costs and specialized expertise (e. g., of Managed Security Service Providers).
Electric Vehicle Attack Impact on Power Grid Operation
We start by examining the existing vulnerabilities in the EV ecosystem that can be exploited to control the EV charging and launch attacks against the power grid.
Toward Multimodal Interaction in Scalable Visual Digital Evidence Visualization Using Computer Vision Techniques and ISS
Visualization requirements in Forensic Lucid have to do with different levels of case knowledge abstraction, representation, aggregation, as well as the operational aspects as the final long-term goal of this proposal.
Android Malware Detection using Deep Learning on API Method Sequences
We evaluate MalDozer on multiple Android malware datasets ranging from 1K to 33K malware apps, and 38K benign apps.
DySign: Dynamic Fingerprinting for the Automatic Detection of Android Malware
However, to the best of our knowledge, there is no such fingerprinting technique that leverages dynamic analysis and would act as the first defense against Android malware attacks.
Cryptography and Security
MARFCAT: Transitioning to Binary and Larger Data Sets of SATE IV
We present a second iteration of a machine learning approach to static code analysis and fingerprinting for weaknesses related to security, software engineering, and others using the open-source MARF framework and the MARFCAT application based on it for the NIST's SATE IV static analysis tool exposition workshop's data sets that include additional test cases, including new large synthetic cases.
