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Formal Representation and Comparative Analysis of Software Runtime Process
2015
The Advanced Science Journal
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Using a software tracing frameworks we obtain sequences of system calls produced during the execution of the pair of programs. ...
Overall, the best-performing metric is a cosine distance, resulting in order-of-magnitude different values for input pairs of different degrees of similarity. ...
Applications include intrusion detection, threat analysis and various predictive algorithms. ...
doi:10.15550/asj.2015.02.038
fatcat:x5izforndjfyrg3ttdsbu4joru
Intrusion Anomaly Detection based on Sequence
2018
International Journal of Performability Engineering
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This new method is superior to previously provided frequent episode pattern matching algorithms for compact detection models, with high detection efficiency and low time delays. ...
Essentially, this algorithm follows the idea of TEIRESIAS, with an additional redundancy controlling mechanism. ...
Anomaly detection is widely used to detect multiple types of intrusion, which can detect unknown intrusion patterns [11] . ...
doi:10.23940/ijpe.18.02.p11.300309
fatcat:fo2mgkwborbjhel2tztdup7ehi
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
2016
IEEE Communications Surveys and Tutorials
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This survey paper describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection. ...
Based on the number of citations or the relevance of an emerging method, papers representing each method were identified, read, and summarized. ...
One of the promising approaches used was based on the longest common subsequence metric. ...
doi:10.1109/comst.2015.2494502
fatcat:n6l5u4xgvbc7jgsy35mlmlpwp4
MORPHEUS
2004
Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security - VizSEC/DMSEC '04
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A "clean" training set thus obtained improves the performance of existing online host-based anomaly detection systems by increasing the number of attack detections. ...
Most of the prevalent anomaly detection systems use some training data to build models. These models are then utilized to capture any deviations resulting from possible intrusions. ...
Overall, the results indicate that the filtering process was instrumental in increasing the number of detections without increasing the number of false alarms. ...
doi:10.1145/1029208.1029212
dblp:conf/vizsec/TandonCM04
fatcat:zx7xunvrg5gx3dy6sbilzwexdm
Security improvements Zone Routing Protocol in Mobile Ad Hoc Network
2014
International Journal of Computer Applications Technology and Research
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Proactive routing protocols: In it, all the nodes continuously search for routing information with in a network, so that when a route is needed, the route is already known. ...
The attractive features of ad-hoc networks such as dynamic topology, absence of central authorities and distributed cooperation hold the promise of revolutionizing the ad-hoc networks across a range of ...
rule based techniques and hybrid techniques.we can't make as many rules as possible.We can develop this system with the help of SMT technique which can increase the efficiency of the system.In existing ...
doi:10.7753/ijcatr0309.1001
fatcat:n7yb26a6zbgwnpvfmvka3cnpoq
Software behaviour correlation in a redundant and diverse environment using the concept of trace abstraction
2013
Proceedings of the 2013 Research in Adaptive and Convergent Systems on - RACS '13
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We propose an approach for detecting anomalies in the presence of OS diversity. ...
We achieve this by comparing kernel-level traces generated from instances of the same application deployed on different OS. ...
Our repeat detection algorithm is described in Figure 6 and is based on n-gram extraction techniques, a well-known approach used in text mining. ...
doi:10.1145/2513228.2513305
dblp:conf/racs/Hamou-LhadjMFMCK13
fatcat:au3e2vnl3zewxnmthmtqq5p6wq
Cyberspace Security Using Adversarial Learning and Conformal Prediction
2015
Intelligent Information Management
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Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns ...
Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted self-managing defensive shield to detect, disrupt, and deny intrusive ...
The data mining output augments the rules found with support and confidence indices, which are characteristic of the whole transaction data set T . ...
doi:10.4236/iim.2015.74016
fatcat:wqiu3pkl6zeurlr3mizdahhgd4
Intrusion-Detection Systems
[chapter]
2012
Handbook of Computer Networks
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The series also serves as a forum for topics that may not have reached a level Researchers, as well as developers, are encouraged to contact Professor Sushil Jajodia with VULNERABILITY ANALYSIS ...
Series on ADVANCES IN INFORMATION SECURITY are, one, to establish the state of the art of, and set the course for future research in information security and, two, to serve as a central reference source ...
Acknowledgment This work has been partially funded by the Ministero dell'Università e della Ricerca (MiUR) in the framework of the RECIPE Project, and by the EU as part of the IST Programme -within the ...
doi:10.1002/9781118256107.ch26
fatcat:aeidzkegvfc27dqqmztiayv3dm
Exact String Matching Algorithms: Survey, Issues, and Future Research Directions
2019
IEEE Access
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with a core focus on exact string matching algorithms. ...
The main purpose of this survey is to propose new classification, identify new directions and highlight the possible challenges, current trends, and future works in the area of string matching algorithms ...
Hashing-based approaches can be classified further as q-gram and non q-gram approaches, as shown in Figure 7 .
1) Q-QRAMS APPROACH The q-gram approach divides a given sequence into n subsequences for ...
doi:10.1109/access.2019.2914071
fatcat:2bkgo6vkjjd63nl2yavplt6gw4
Improving database quality through eliminating duplicate records
2006
Data Science Journal
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By introducing a concept of String Matching Points (SMP) in string comparison, string matching accuracy and efficiency are improved, compared with other commonly-applied field matching algorithms. ...
The paper discusses the development of field matching algorithms from the developed general framework. ...
But q-gram is an inherent space expensive technique, with (m-q+1) q-grams for a string with length of m. High space consumption means high computational cost in database systems. ...
doi:10.2481/dsj.5.127
fatcat:xxjc63i2yjghtox7dw5wvdilnq
Finding Surprisingly Frequent Patterns of Variable Lengths in Sequence Data
2016
Proceedings of the 2016 SIAM International Conference on Data Mining
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We address the problem of finding 'surprising' patterns of variable length in sequence ...
These tasks encompass a wide range of spectrum, from more traditional association rule mining and frequent pattern mining tasks to newer ones, such as intrusion detection, customer behaviour analysis in ...
We also compare our method with five other well-known anomaly detectione techniques. ...
doi:10.1137/1.9781611974348.4
dblp:conf/sdm/SadoddinSR16
fatcat:yerjh5tny5a2rpezrhaqah4vem
A comprehensive survey on machine learning for networking: evolution, applications and research opportunities
2018
Journal of Internet Services and Applications
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Therefore, this is a timely contribution of the implications of ML for networking, that is pushing the barriers of autonomic network operation and management. ...
This survey is original, since it jointly presents the application of diverse ML techniques in various key areas of networking across different network technologies. ...
Acknowledgments We thank the anonymous reviewers for their insightful comments and suggestions that helped us improve the quality of the paper. ...
doi:10.1186/s13174-018-0087-2
fatcat:jvwpewceevev3n4keoswqlcacu
Automated State Machines Applied in Client Honeypots
2010
2010 5th International Conference on Future Information Technology
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The data mining techniques with static analysis are divided into four main categories [17] [18] : N-grams: it involves a sequence of hexadecimal strings extracted from an executable file. ...
A number of state machine signatures with the longest sequence L are identified by creating a behaviour group for all the Ni states with the longest similar states S; L identifies the longest similar states ...
doi:10.1109/futuretech.2010.5482695
fatcat:n6xgujmyeng6lmqgqwoou52cfy
Selecting and Improving System Call Models for Anomaly Detection
[chapter]
2009
Lecture Notes in Computer Science
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Finally, the impact of these modifications are discussed by comparing the performance of the two original implementations with two modified versions complemented with our models. ...
We begin by comparing them and analyzing their respective performance in terms of detection accuracy. ...
In [31] the LERAD algorithm (Learning Rules for Anomaly Detection) is used to mine rules expressing "normal" values of arguments, normal sequences of system calls, or both. ...
doi:10.1007/978-3-642-02918-9_13
fatcat:ig2yhvyi7rbfhns6db4aonmoza
The Principal Rare Earth Elements Deposits of the United States: A Summary of Domestic Deposits and a Global Perspective
[chapter]
2012
Non-Renewable Resource Issues
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Mining ceased in this area in late 1978 because of increasing environmental regulations that made mining operations more costly. ...
Mining ceased in this area in late 1978 because of increasing environmental regulations that made mining operations more costly. ...
The monzonite and pegmatite intrusions may be monazite bearing or monazite free. ...
doi:10.1007/978-90-481-8679-2_7
fatcat:gjrly73w3za6fchanmjuulyzxq
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