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274
IMDS: Intelligent Malware Detection System
, 2007
"... The proliferation of malware has presented a serious threat to the security of computer systems. Traditional signature-based antivirus systems fail to detect polymorphic and new, previously unseen malicious executables. In this paper, resting on the analysis of Windows API execution sequences called ..."
Abstract
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Cited by 22 (10 self)
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called by PE files, we develop the Intelligent Malware Detection System (IMDS) using Objective-Oriented Association (OOA) mining based classification. IMDS is an integrated system consisting of three major modules: PE parser, OOA rule generator, and rule based classifier. An OOA Fast FP-Growth algorithm
Classification of Artificial Intelligence IDS
"... Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is relatively new addition to such techniques. Intrusion detection systems (IDSs) are used to find out if someone has intrusion into or is trying to get in the network. One ..."
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intelligence (AI) methods / techniques in in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in
Voting Methods For Malware Detection
"... Abstract-The internet plays an important role in all areas of society from economy to the government. Nowadays Computer Security is pretentious by malicious data. Computer security means keeping the information on computer in a secure manner. so detection of malware is an paramount substance. In an ..."
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as malware representation. The results indicated that the proposed model reduced the number of false negatives. The proposed model will be tested for detection of di_erent types of malware. This proposed system use Trust Base Veto Algorithm for deciding malware or benign. Also research work proposes
An intelligent PE-malware detection system based on association mining
, 2008
"... The proliferation of malware has presented a serious threat to the security of computer systems. Traditional signature-based anti-virus systems fail to detect polymorphic/metamorphic and new, previously unseen malicious executables. Data mining methods such as Naive Bayes and Decision Tree have been ..."
Abstract
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Cited by 11 (3 self)
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been studied on small collections of executables. In this paper, resting on the analysis of Windows APIs called by PE files, we develop the Intelligent Malware Detection System (IMDS) using Objective-Oriented Association (OOA) mining based classification. IMDS is an integrated system consisting
Intrusion Detection Based On Artificial Intelligence Technique
"... Information Technology has become a main and important component to support critical infrastructure services in various sectors of our society. It is being used for sharing information and various operations. Many organizations are used to create complex network systems to give supply to the users. ..."
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artificial intelligence techniques. In this paper, we will have a look on a technique: K-Nearest Neighbors Algorithm for the understanding Intrusion Detection System. K-Nearest-Neighbors is one of the simplest and effective classification methods. This research shows the performance of the techniques
A Review of Vessel Extraction Techniques and Algorithms
- ACM Computing Surveys
, 2000
"... Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by means of a classification of the existing r ..."
Abstract
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Cited by 185 (0 self)
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into six main categories: (1) pattern recognition techniques, (2) model-based approaches, (3) tracking-based approaches, (4) artificial intelligence-based approaches, (5) neural network-based approaches, and (6) miscellaneous tube-like object detection approaches. Some of these categories are further
Artificial Immune Clonal Selection Classification Algorithms for Classifying Malware and Benign Processes Using API Call Sequences
"... Abstract Machine learning is an important field of artificial intelligence in which models are generated by extracting rules and functions from large datasets. Machine learning includes a diversity of methods and algorithms such as decision trees, lazy learning, knearest neighbors, Bayesian methods ..."
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of the immune system to develop computational algorithms for function optimization, pattern recognition, novelty detection, and process control, and classification. There are four main sub fields of research that have emerged in AIS cantered on prominent immunological theories; negative selection algorithms
Artificial Intelligence
, 2011
"... There is a need to come up with efficient algorithms which can perform automatic video-based behaviour analysis. It is a challenging problem, as it requires correctly modelling individual behaviours and learning switching dynamics between these behaviours. This task if done manually is a slow, labor ..."
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, laborious and error prone process. So there is a need for techniques that can automatically analyze huge volumes of data and potentially reduce time taken to detect behaviours. In this thesis, the Auto-Regressive Hidden Markov Model (AR-HMM) was evaluated for doing automatic video-based behaviour analysis
CIMDS: Adapting Postprocessing Techniques of Associative Classification for Malware Detection
"... Abstract—Malware is software designed to infiltrate or damage a computer system without the owner’s informed consent (e.g., viruses, backdoors, spyware, trojans, and worms). Nowadays, numerous attacks made by the malware pose a major security threat to computer users. Unfortunately, along with the d ..."
Abstract
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Cited by 4 (0 self)
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to analyze and classify the file samples is needed. In our previous work, we have developed an intelligent malware detection system (IMDS) by adopting associative classification method based on the analysis of application programming interface (API) execution calls. Despite its good performance in malware
6 Malware Classification through HEX Conversion and Mining
"... The malicious codes are normally referred as malware. Systems are vulnerable to the traditional attacks, and attackers continue to find new ways around existing protection mechanisms in order to execute their injected code. Malware is a pervasive problem in distributed computer and network systems. ..."
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extraction of unique signatures from malware files. This is primarily intended for high-speed network traffic. The signature extraction process is based on a comparison with a common function repository. The data mining framework employed in this research learns through analyzing the behavior of existing
Results 1 - 10
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274
