Add to ORKGThis paper presents a scareware detection method that is based on performing data mining on extracted variable length opcode sequences derived from instruction sequences of binary files. Our experimental results show that many common supervised learning algorithms generate accurate models from subsets of our data set
New malware outbreaks cannot provide thousands of training samples which are required to counter mal...
Malware detectors require a specification of malicious behav-ior. Typically, these specifications ar...
Adversarial learning has previously demonstrated effectiveness as a tool for improving performance i...
This paper presents a scareware detection method that is based on performing data mining on extracte...
Scareware is a recent type of malicious software that may pose financial and privacy-related threats...
A trojan horse is a program that surreptitiously performs its operation under the guise of a legitim...
Internet worms pose a serious threat to computer security. Traditional approaches using signatures t...
Malicious programs pose a serious threat to computer security. Traditional approaches using signatur...
In this paper, we present a novel approach to detect unknown virus using dynamic instruction sequenc...
Malware can be defined as any type of malicious code that has the po-tential to harm a computer or n...
In this paper, we present a novel approach to detect unknown virus using dynamic instruction sequenc...
Abstract. The recent growth in network usage has motivated the creation of new malicious code for va...
Thousands of new malware codes are developed every day. Signature-based methods, which are employed ...
This paper describes our research in evaluating the use of supervised data mining algorithms for an ...
Adware represents a possible threat to the security and privacy of computer users. Traditional signa...
New malware outbreaks cannot provide thousands of training samples which are required to counter mal...
Malware detectors require a specification of malicious behav-ior. Typically, these specifications ar...
Adversarial learning has previously demonstrated effectiveness as a tool for improving performance i...
This paper presents a scareware detection method that is based on performing data mining on extracte...
Scareware is a recent type of malicious software that may pose financial and privacy-related threats...
A trojan horse is a program that surreptitiously performs its operation under the guise of a legitim...
Internet worms pose a serious threat to computer security. Traditional approaches using signatures t...
Malicious programs pose a serious threat to computer security. Traditional approaches using signatur...
In this paper, we present a novel approach to detect unknown virus using dynamic instruction sequenc...
Malware can be defined as any type of malicious code that has the po-tential to harm a computer or n...
In this paper, we present a novel approach to detect unknown virus using dynamic instruction sequenc...
Abstract. The recent growth in network usage has motivated the creation of new malicious code for va...
Thousands of new malware codes are developed every day. Signature-based methods, which are employed ...
This paper describes our research in evaluating the use of supervised data mining algorithms for an ...
Adware represents a possible threat to the security and privacy of computer users. Traditional signa...
New malware outbreaks cannot provide thousands of training samples which are required to counter mal...
Malware detectors require a specification of malicious behav-ior. Typically, these specifications ar...
Adversarial learning has previously demonstrated effectiveness as a tool for improving performance i...