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How can we extract useful information from a security forum? We focus onidentifying threads of interest to a security professional: (a) alerts ofworrisome events, such as attacks, (b) offering of malicious services andproducts, (c) hacking information to perform malicious acts, and (d) usefulsecurity-related experiences. The analysis of security forums is in its infancydespite several promising recent works. Novel approaches are needed to addressthe challenges in this domain: (a) the difficulty in specifying the "topics" ofinterest efficiently, and (b) the unstructured and informal nature of the text.We propose, REST, a systematic methodology to: (a) identify threads of interestbased on a, possibly incomplete, bag of words, and (b) classify them into oneof the four classes above. The key novelty of the work is a multi-step weightedembedding approach: we project words, threads and classes in appropriateembedding spaces and establish relevance and similarity there. We evaluate ourmethod with real data from three security forums with a total of 164k posts and21K threads. First, REST robustness to initial keyword selection can extend theuser-provided keyword set and thus, it can recover from missing keywords.Second, REST categorizes the threads into the classes of interest with superioraccuracy compared to five other methods: REST exhibits an accuracy between63.3-76.9%. We see our approach as a first step for harnessing the wealth ofinformation of online forums in a user-friendly way, since the user can looselyspecify her keywords of interest.

REST: A Thread Embedding Approach for Identifying and Classifying User-specified Information in Security Forums