Extracting actionable information from Security Forums
The goal of this work is to systematically extract information from hacker forums, whose information would be in general described as unstructured: the text of a post is not necessarily following any writing rules. By contrast, many security initiatives and commercial entities are harnessing the readily public information, but they seem to focus on structured sources of information. Here, we focus on the problem of analyzing text content in security forums. A key novelty is that we use user profiles and contextual features along with transfer learning approach and also embedding space to help us identify and refine information that we could not get from security forum with trivial analysis. We collect a wealth of data from 5 different security forums. The contribution of our work is twofold; (a) we develop a method to automatically identify through the forums malicious IP addresses (b) we also propose a systematic method to identify and classify user-specified threads of interest into four categories. We further showcase how this information can inform knowledge extraction from the forums. As the cyber-wars are becoming more intense, having early accesses to useful information becomes more imperative to remove the hackers first-move advantage, and our work is a solid step towards this direction.
InferIP: Extracting actionable information from security discussion forums
How much useful information can we extract from security forums? Many security initiatives and commercial entities are harnessing the readily public information, but they seem to focus on structured sources of information. Our goal here is to extract information from hacker forums, whose information is provided in ad hoc and unstructured ways. Here, we focus on the problem of identifying malicious IPs addresses, when these are being reported in the forums. We develop a method to automate the identification of malicious IPs with the design goal of being independent of external sources. A key novelty is that we use a matrix decomposition method to extract latent features of the behavioral information of the users, which we combine with textual information from the related posts. As key design feature, our technique can be applied to different language forums since it relies on a simple NLP solution in combination with behavioral features. In particular, our solution only needs a small number of keywords in the new language plus the user's behavior captured by specific features. We also develop a tool to automate the data collection from security forums. We collect approximately 600K posts from 3 different forums. Our method exhibits high classification accuracy, while the precision of identifying malicious IP in post is greater than 88% in all three sites. Furthermore, by applying our method, we find up to 3 times more potentially malicious IPs than compared to the reference blacklist VirusTotal. As the cyber-wars are becoming more intense, having early accesses to useful information becomes more imperative to remove the hackers first-move advantage, and our work is a solid step towards this direction.
Kinematic Modelling and Simulation of a 2R Robot Using SolidWorks and Verification by MATLAB / Simulink Regular Paper
The  simulation  of  robot  systems  is  becoming very popular, especially with  the  lowering of  the cost of computers,  and  it  can  be  used  for  layout  evaluation, feasibility studies, presentations with animation and off‐ line programming. The  trajectory  planning  of  redundant manipulators  is  a very  active  area  since  many  tasks  require  special characteristics  to  be  satisfied.  The  importance  of redundant manipulators has  increased over  the  last  two decades  because  of  the  possibility  of  avoiding singularities  as  well  as  obstacles  within  the  course  of motion.  The  angle  that  the  last  link  of  a  2  DOF manipulator makes with the x‐axis is required in order to find the solution for the inverse kinematics problem. This angle  could  be  optimized  with  respect  to  a  given specified  key  factor  (time,  velocity,  torques)  while  the end‐effector  performs  a  chosen  trajectory  (i.e., avoiding an obstacle) in the task space. Modeling  and  simulation  of  robots  could  be  achieved using  either  of  the  following  models:  the  geometrical model (positions, postures), the kinematic model and the dynamic model. To  do  so,  the  modelization  of  a  2‐R  robot  type  is implemented. Our main  tasks  are  comparing  two  robot postures with the same trajectory (path) and for the same length  of  time,  and  establishing  a  computing  code  to obtain the kinematic and dynamic parameters. SolidWorks  and MATLAB/Simulink  softwares  are  used to check the theory and the robot motion simulation. This  could  be  easily  generalized  to  a  3‐R  robot  and possibly therefore to any serial robot (Scara, Puma, etc.). The verification of the obtained results by both softwares allows  us  to  qualitatively  evaluate  and  underline  the validityof  the  chosen  model  and  obtain  the  right conclusions. The results of  the simulations are discussed and an agreement between the two softwares is certainly obtained.