Cooperative Mapping and Exploration using Counter-rotational Potential Fields

This paper presents a novel technique for mapping and exploration using cooperating autonomous underwater vehicles. Rather than using the typical lawnmower sweep pattern to search an entire area, the proposed navigational plan involves guiding the formation directly towards each object of interest in turn, before arriving at a final goal position. This is achieved by the use of traditional artificial potential fields alongside counter-rotational potential fields. These clockwise and counter-clockwise fields are employed simultaneously by vehicles to ensure that the entire object is scanned rather than simply avoided as is the case with traditional collision avoidance techniques. The proposed methodology allows a formation to have fluid-like motion whilst a separation distance between cooperating agents (free of angular constraints) is maintained with a greater degree of flexibility than traditional formation control approaches. Owing to its nature, this technique is suited for applications such as exploration, mapping and underwater inspection to name a few. Simulation results demonstrate the efficacy of the proposed approach.

N-opcode analysis for android malware classification and categorization

Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.