The main contributions of this paper are: (1) providing an overview of malware types and malware detection approaches, (2) discussing the current malware analysis techniques, their findings and limitations, (3) studying the malware obfuscation, attacking and anti-analysis techniques, and (4) exploring the structure of memory-based analysis in malware detection.
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Alternatively, memory analysis is a promising technique that gives a comprehensive view of malware and it is expected to become more popular in malware analysis. Likewise, a considerable false positive rate and the high amount of scanning time are the main limitations of heuristic-based techniques. However, it is not effective in detecting zero-day malware and it is easily defeated by malware that uses obfuscation techniques.
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DESCARGAR COMMAND BAR PARA OLLYDBG SOFTWARE
The Signature-based technique is largely used today by anti-virus software to detect malware, is fast and capable to detect known malware. This paper presents a semantic and detailed survey of methods used for malware detection like signature-based and heuristic-based. Therefore, security researchers are taking great efforts to develop accurate and effective techniques to detect malware. Due to the vast number of malware, it is impossible to handle malware by human engineers. A software that sneaks to your computer system without your knowledge with a harmful intent to disrupt your computer operations. Now a day the threat of malware is increasing rapidly. Results show that prosody modification and speaker adaptive training helps to minimize the word error rate (WER) of the Punjabi-ASR system to 8.79% when tested using children's speech. This prosody modified speech overcomes the massive need for children's speech for training the ASR system and improves the recognition rate. The developed Punjabi-ASR system is trained with the help of adult speech and prosody-modified adult speech. The pitch period and duration (speaking rate) of the speech signal can be altered with prosody modification without influencing the naturalness, message of the signal and helps to overcome the acoustic variations present in the adult's and children's speech. Thus, the main objective of the research work is to increase the speech recognition rate of the Punjabi-ASR system by reducing these inter-speaker acoustic variabilities with the help of prosody modification and speaker adaptive training. These inter-speaker acoustic variabilities are mainly because of the higher pitch and lower speaking rate of the children. The speech recognition rate of such systems is very less when tested using the children's speech, due to the presence of the inter-speaker acoustic variabilities between the adults and children's speech. Most of the automatic speech recognition (ASR) systems are trained using adult speech due to the less availability of the children's speech dataset.