Kaspersky Lab, Zao

Nikolay Denishchenko

Pavel A Zelensky

Yury V Mashevsky

Yuri Mashevsky

Yury V Namestnikov

Oleg V Zaitsev

Andrey A Efremov

Igor G Chekunov

Yuri V Namestnikov

A system, method and computer program product for optimization of execution of anti-malware (AV) applications. A number of false-positive determinations by an AV system are reduced by correcting malware detection rules using correction coefficients. A number of malware objects detected by the AV system are increased by correction of ratings determined by the rules using correction coefficients. An automated testing of new detection rules used by the AV system is provided. The new rules having zero correction coefficients are added to the rules database and results of application of the new rules are analyzed and the rules are corrected or modified for further testing.

Optimization of anti-malware processing by automated correction of detection rules

A system, method and computer program product for detection of the previously unknown malware, the method comprising: (a) receiving event information and file metadata from a remote computer; (b) identifying whether the event information or the file metadata are indicative of the already known malware presence, indicative of the unknown malware presence, or indicative of malware absence; (c) if the event information or the file metadata are indicative of the known malware or indicative of malware absence, filtering out the event information and the file metadata; (d) performing a risk analysis and risk assessment for the remaining event information and the remaining file metadata to determine if the event and the file metadata are indicative of the previously unknown malware presence; and (e) where performing a risk analysis and risk assessment includes a 'parent-child' hierarchy of the files, and the risk assessed to the parent is based on the risk associated with the child.

Method and system for detection of previously unknown malware

A system, method and computer program product for detection of epidemics caused by malware programs or computer viruses. Detection of local and global epidemics is performed automatically. A source of an epidemic is calculated and analyzed based on collected statistics. A spread of the epidemic is predicted and an accurate prognosis referring to the time frame and to geographical areas of the epidemic spread is made. The prognosis is made based on a calculated value of 'connection strength' coefficient. The connection strength coefficient reflects a volume of information exchange (i.e., a number and a quality of connection channels) between the countries. An epidemic is detected in its infancy and its spread is monitored in time and propagation across different countries. Then, effective security and protection measures can be invoked in a timely manner.

Method and system for detection and prediction of computer virus-related epidemics

A system, method and computer program product for detection of false positives occurring during execution of anti-malware applications. The detection and correction of the false positives is implemented in two phases, before creation of new anti-virus databases (i.e., malware black lists) or before creation of new white lists, and after the anti-virus databases or new white lists are created and new false positives are detected. The system calculates a probability of detection of a certain potential malware object. Based on this probability, the system decides to either correct a white list (i.e., a collection of known clean objects) or update a black list (i.e., a collection of known malware objects). A process is separated into a several steps: creation and update (or correction) of white lists; creation and update of black lists; detection of collisions between these lists and correction of black lists or white lists based on the detected collisions.

Growing community of inventors

Moscow, Russia

Nikolay Denishchenko