Bridging statistical learning and formal reasoning for cyber attack detection

Current cyber-infrastructures are facing increasingly stealthy attacks that implant malicious payloads under the cover of benign programs. Current attack detection approaches based on statistical learning methods may generate misleading decision boundaries when processing noisy data with such a mixture of benign and malicious behaviors. On the other hand, attack detection based on formal program analysis may lack completeness or adaptivity when modeling attack behaviors. In light of these limitations, we have developed LEAPS, an attack detection system based on supervised statistical learning to classify benign and malicious system events. Furthermore, we leverage control flow graphs inferred from the system event logs to enable automatic pruning of the training data, which leads to a more accurate classification model when applied to the testing data. Our extensive evaluation shows that, compared with pure statistical learning models, LEAPS achieves consistently higher accuracy when detecting real-world camouflaged attackswith benign program cover-up

The Use Of The Internet In Teaching English To Senior High School Students At SMK Muhammadiyah 3 Surakarta

The objectives of this study are:1) to identify the teachers’ activities in teaching English using internet; 2) to identify the programs used by the teacher in the usage of internet in teaching English; and 3) to identify the the problems faced by the teachers in teaching English using internet and the attempts to solve them. In connducting this research, the researcher uses descriptive qualitative type. There are two kinds of data, they are primary data and secondary data. In collecting the data, this research uses interview, observation, and documentation. The result of the research are: 1) the teacher activities in the usage of internet in English teaching are: controlling learning activities and ensuring that the program and internet connection are running well; solving students’ problem in doing tasks from internet program; organizing learning activities; and explaining material; 2) the programs used by the teacher in the usage of internet in teaching English are Dyned Courseware and Side by Side (SBS). The programs build some activities to develop the student skill in listening, speaking, reading and writing; 3) the problems faced by the teachers in teaching English using internet are: The internet program syllabus and school syllabus are quite different, so that the teacher must adapt the internet syllabus in accordance with school syllabus; Imperfect instructional material, Differences in students’ ability; Various studemts’ characters; The teacher get hindrances to dispose the activity in learning with internet; The classroom activity sometimes seemed crowded and noisy because the large number of students; Problems with internet connection; and Getting silence in communication; 4) The teachers’ attempts to solve the problems are: In order to solve the problem of English internet program syllabus, the teachers had to develop and adapt the syllabus into syllabus of English internet program; In order to overcome imperfect learning material for English teaching using internet, the teachers explored various kinds of materials; In order to overcome various students’ characters and abilities, the teacher gave the material step by step; In order to overcome crowded and noisy class, the teachers divided the class into groups; and In order to solve electricity and internet connection problem, SMK Batik Surakarta hired an engineer to do electricity and machinery maintenance

Learning to Infer Graphics Programs from Hand-Drawn Images

We introduce a model that learns to convert simple hand drawings into graphics programs written in a subset of \LaTeX. The model combines techniques from deep learning and program synthesis. We learn a convolutional neural network that proposes plausible drawing primitives that explain an image. These drawing primitives are like a trace of the set of primitive commands issued by a graphics program. We learn a model that uses program synthesis techniques to recover a graphics program from that trace. These programs have constructs like variable bindings, iterative loops, or simple kinds of conditionals. With a graphics program in hand, we can correct errors made by the deep network, measure similarity between drawings by use of similar high-level geometric structures, and extrapolate drawings. Taken together these results are a step towards agents that induce useful, human-readable programs from perceptual input