Wise Anti Malware PRO 2.1.8.106 RePack [Full]
existing software package managers are popular in terms of easy-to-use and management. however, they do not possess sufficient security guarantees and are vulnerable to various threats such as malware. these issues have attracted the attention of researchers, and they have proposed solutions to improve the security of package managers. among them, an effective approach is to add signatures to the packages and resolve problems by verifying the signatures. unfortunately, this is not practical because of the growing number of packages, requiring an enormous amount of signature data. to address this issue, we propose a method to generate the signatures and the verification process dynamically. our method adds signatures to the packages by analyzing the program code during the execution. the signatures are saved in the package repositories. the signatures are verified using the signature cache, and are updated whenever the signatures of a new version are added. our method is implemented in a standalone tool, and is independent from the package managers. it can be used as an additional tool to improve the security of package managers or integrated into existing package managers. by deploying our tool, the security of package managers can be improved, and the usability can be maintained.
software security is an important issue to ensure the safety of software products. in particular, unauthorized access to the source code of software products, which is widely used as a vehicle for malware propagation, is one of the biggest threats to software security. even though various approaches have been proposed to protect source code, no practical methods have been developed yet because of the difficulty of their maintenance. in this paper, we propose a source code protection method based on information hiding and verification techniques. a software product is encrypted, and the security level of the product can be determined by decrypting the product. the decryption process is performed only once upon installation. to protect the source code, we introduce a version control system to track changes to the source code. our method enables the application of source code protection to a range of existing software products, such as web applications. the proposed scheme is readily implemented, as it does not require any dedicated hardware or specialized software tools, and thus can be realized in practice.
All Anti-Virus Antivirus software will detect this file and tell you it is a Trojan. Hence, this file should not be there. If it is there, we suspect the file was infected by malware. We do not believe that it is a malware file. No action is required on your part. Remove this file. You can use any Anti-Virus software to remove this file. If you do not have a Anti-Virus software or do not want to use one, then you can remove this file using Filezila. Running the cleaning utility for this file will remove its associated.exe file. If you want to remove this file from our database so others will not see it in our listings, choose Remove from Database. This will remove it from our database, but also delete the related.exe file.
While typical cybersecurity solutions can have a relatively low false negative rate, they often have a high false positive rate, especially when it comes to malware detection. We presented a strategy to improve security and usability through minimizing the false positive rate. The proposed method can automatically detect malware obfuscation code while guaranteeing the privacy of the user. We believe this study can be useful for designing future cybersecurity standards.
The specificity of network intrusion detection systems (NIDSs) is limited by false positives in an environment with a very large number of normal traffic. However, typical NIDSs are focused on attacks rather than on normal traffic. To address this problem, we presented a method of accurately and efficiently detecting attacks from a large amount of normal traffic. Our method applies online behavioral models to normal traffic, and can detect attacks successfully. We believe the method will be useful for future NIDSs.
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