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BLATTA: Early Exploit Detection on Network Traffic with Recurrent Neural Networks

Baskoro A. Pratomo, Pete Burnap, George Theodorakopoulos
2020 Security and Communication Networks  
Hence, we propose a novel early exploit detection mechanism that scans network traffic, reading only 35.21% of application layer messages to predict malicious traffic while retaining a 97.57% detection  ...  Inspecting the payload of network traffic may offer better performance in detecting exploits as they tend to hide their presence and behave similarly to legitimate traffic.  ...  First, Blatta builds a dictionary containing most common n-grams in the training set. en, it is trained over benign and malicious sequences of n-grams to classify exploit traffic.  ... 
doi:10.1155/2020/8826038 fatcat:if5gccqfavbjlnhspvqazhe2wa

Ransomware Analysis using Feature Engineering and Deep Neural Networks [article]

Arslan Ashraf, Abdul Aziz, Umme Zahoora, Muttukrishnan Rajarajan, Asifullah Khan
2020 arXiv   pre-print
Additionally, important sequences are found with the help of the N-Gram technique.  ...  It is also observed that in the case of Registry Delete operation, if a malicious file tries to delete registries, it follows a specific and repeated sequence.  ...  Experiments include the n-gram sequence analysis of Recall TP TP FN  Registry Operation to find the underlying discriminative patterns.  ... 
arXiv:1910.00286v2 fatcat:l6eobebgcjdxpowrk4ekd5iqre

NLP Technique for Malware Detection Using 1D CNN Fusion Model

Paul Ntim Yeboah, Haruna Balle Baz Musah
2022 Security and Communication Networks  
Predictions of the 1D CNN model trained on multiple feature sets of n-gram opcode sequences are combined using a weighted average ensemble.  ...  The proposed model automatically extracts features from semantically embedded n-grams of raw static operation code (opcodes) sequences to determine the maliciousness of a binary file.  ...  of the proposed model on ensemble n-gram opcode sequences.  ... 
doi:10.1155/2022/2957203 doaj:33488b946a024bf7affa002ac7294395 fatcat:uwgqxp27d5b4nnhflnqx37mlnm

Unsupervised Incremental Learning and Prediction of Music Signals [article]

Ricard Marxer, Hendrik Purwins
2015 arXiv   pre-print
, 4) extraction of statistical regularities of the symbol sequence, using hierarchical N-grams and the newly introduced conceptual Boltzmann machine, and 5) prediction of the next sound event in the sequence  ...  A sequence learning algorithm adapts its structure to a dynamically changing clustering tree.  ...  to adapt Pfleger's HN [37] to our architecture, we have to link the operations of the clustering model to the operations on the n-gram (Fig. 2) .  ... 
arXiv:1502.00524v2 fatcat:ouplzvgkwfamtcp73mkomyzgiq

Unsupervised Incremental Online Learning and Prediction of Musical Audio Signals

Ricard Marxer, Hendrik Purwins
2016 IEEE/ACM Transactions on Audio Speech and Language Processing  
, 4) extraction of statistical regularities of the symbol sequence, using hierarchical N-grams and the newly introduced conceptual Boltzmann machine, and 5) prediction of the next sound event in the sequence  ...  A sequence learning algorithm adapts its structure to a dynamically changing clustering tree.  ...  to adapt Pfleger's HN [37] to our architecture, we have to link the operations of the clustering model to the operations on the n-gram (Fig. 2) .  ... 
doi:10.1109/taslp.2016.2530409 fatcat:4qjp3mlosfhklp4p4g6pivowty

A Host-Based Anomaly Detection Framework Using XGBoost and LSTM for IoT Devices

Xiali Wang, Xiang Lu, Ximeng Liu
2020 Wireless Communications and Mobile Computing  
The collected system call sequences are firstly processed by the famous n -gram model, which is a common method used for host-based intrusion detections.  ...  To this end, in this paper, we propose a stacking model to couple the Extreme Gradient Boosting (XGBoost) model and the Long Short-Term Memory (LSTM) model together for the abnormal state analysis on the  ...  Requests for access to these data should be made to Xia-Li Wang, xialiwang4@gmail.com. The other part of the data is the ADFA-LD dataset. It is designed for evaluation by system call base HIDS.  ... 
doi:10.1155/2020/8838571 fatcat:gcdpxuuudbd6tckgyyp5d3q3v4

Efficient and effective realtime prediction of drive-by download attacks

Gaya K. Jayasinghe, J. Shane Culpepper, Peter Bertok
2014 Journal of Network and Computer Applications  
However, static and semidynamic analysis techniques are vulnerable to commonly employed evasion techniques.  ...  While several alternatives to mitigate the threat have been proposed, approaches to realtime detection of drive-by download attacks has been predominantly limited to static and semi-dynamic analysis techniques  ...  most m − n + 1 distinct n-grams.  ... 
doi:10.1016/j.jnca.2013.03.009 fatcat:374cg7porzh3vljydik34gwuxu

Ransomware Detection Based On Opcode Behavior Using K-Nearest Neighbors Algorithm

Deris Stiawan, Somame Morianus Daely, Ahmad Heryanto, Nurul Afifah, Mohd Yazid Idris, Rahmat Budiarto
2021 Information Technology and Control  
In this paper, we propose Control Flow Graph (CFG) asan extracting opcode behaviour technique, combined with 4-gram (sequence of 4 "words") to extract opcodesequence to be incorporated into Trojan Ransomware  ...  The opcode CFG 4-gram can fully represent the detailed behavioural characteristics of Trojan Ransomware.The proposed ransomware detection method considers the closest distance to a previously identifiedransomware  ...  The formula to measure the Recall is expressed in Equation ( 4 ). . (4) Experimental Results Feature Extraction Results N-gram extraction feature is used to extract opcode sequences with N = 1 to  ... 
doi:10.5755/j01.itc.50.3.25816 fatcat:leojudbtg5c47jiiry7ockw5nu

Prediction and Analysis of Quorum Sensing Peptides Based on Sequence Features

Akanksha Rajput, Amit Kumar Gupta, Manoj Kumar, Lukasz Kurgan
2015 PLoS ONE  
Exploiting above properties, we have developed a Support Vector Machine (SVM) based predictive model.  ...  Quorum sensing peptides (QSPs) are the signaling molecules used by the Gram-positive bacteria in orchestrating cell-to-cell communication.  ...  Query "Gram-positive bacteria NOT quorum sensing AND sequence length range 5 to 65" was used to obtain negative data equivalent to positive data set.  ... 
doi:10.1371/journal.pone.0120066 pmid:25781990 pmcid:PMC4363368 fatcat:73rakkelcfgq7k2nlcxvyfx6vu

Molding CNNs for text: non-linear, non-consecutive convolutions [article]

Tao Lei, Regina Barzilay, Tommi Jaakkola
2015 arXiv   pre-print
Instead of concatenating word representations, we appeal to tensor algebra and use low-rank n-gram tensors to directly exploit interactions between words already at the convolution stage.  ...  Moreover, we extend the n-gram convolution to non-consecutive words to recognize patterns with intervening words.  ...  Indeed, we appeal to tensor algebra to introduce a non-linear feature mapping that operates on nonconsecutive n-grams.  ... 
arXiv:1508.04112v2 fatcat:t472virw2jceblpdv5zr7wwa6y

Molding CNNs for text: non-linear, non-consecutive convolutions

Tao Lei, Regina Barzilay, Tommi Jaakkola
2015 Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing  
Instead of concatenating word representations, we appeal to tensor algebra and use low-rank n-gram tensors to directly exploit interactions between words already at the convolution stage.  ...  Moreover, we extend the n-gram convolution to non-consecutive words to recognize patterns with intervening words.  ...  Indeed, we appeal to tensor algebra to introduce a non-linear feature mapping that operates on nonconsecutive n-grams.  ... 
doi:10.18653/v1/d15-1180 dblp:conf/emnlp/LeiBJ15 fatcat:hdjayrzlzzcl3gv4wit6kbt36a

Combining Code Embedding with Static Analysis for Function-Call Completion [article]

M. Weyssow, H. Sahraoui, B. Frénay, B. Vanderose
2020 arXiv   pre-print
Previous works on code completion have mainly exploited static type systems of programming languages or code history of the project under development or of other projects using common APIs.  ...  The results show that the use of the trained model along with a code suggestion plug-in based on static type analysis improves significantly the correctness of the completion suggestions.  ...  In Section V-A, we use n-grams to quantify the predictability of function sequences in source codes.  ... 
arXiv:2008.03731v2 fatcat:yytgbdsh7bhwhfq3vu7rbpisli

SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides

Leyi Wei, Jijun Tang, Quan Zou
2017 BMC Genomics  
Conclusions: The proposed SkipCPP-Pred is a simple and fast sequence-based predictor featured with the adaptive k-skip-n-gram model for the improved prediction of CPPs.  ...  The novelty of the proposed predictor is that we present a sequence-based feature representation algorithm called adaptive k-skip-n-gram that sufficiently captures the intrinsic correlation information  ...  In the ROC analysis, area under the receiver operating characteristic curve (AUC) is the major metric to evaluate the predictive performance of a predictor.  ... 
doi:10.1186/s12864-017-4128-1 pmid:29513192 fatcat:ix3o4acoz5enbgh27wblasdyey

Learning Orthographic Structure With Sequential Generative Neural Networks

Alberto Testolin, Ivilin Stoianov, Alessandro Sperduti, Marco Zorzi
2015 Cognitive Science  
(n-grams and hidden Markov models).  ...  One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events.  ...  Acknowledgments This study was supported by the European Research Council (grant no. 210922 to M.Z.). I.  ... 
doi:10.1111/cogs.12258 pmid:26073971 fatcat:k47jad5555ewzbwopstezdozi4

EVIL: Exploiting Software via Natural Language [article]

Pietro Liguori, Erfan Al-Hossami, Vittorio Orbinato, Roberto Natella, Samira Shaikh, Domenico Cotroneo, Bojan Cukic
2021 arXiv   pre-print
We present an extensive experimental study to evaluate the feasibility of EVIL, using both automatic and manual analysis, and both at generating individual statements and entire exploits.  ...  Writing exploits for security assessment is a challenging task. The writer needs to master programming and obfuscation techniques to develop a successful exploit.  ...  BLEU measures translation quality by the accuracy of translating n-grams to n-grams, for n-gram of size 1 to 4 [57] .  ... 
arXiv:2109.00279v1 fatcat:jknu7gdckzf7ldz6hmpj75lcva
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