conficker detection

1. The existence and development inevitability of IDS (Intrusion Detection System) (1) The complexity of network security and passive defense methods are insufficient. (2) related firewalls: devices with network boundaries can be attacked by themselves, and some attacks are poorly protected. Not all threats come from outside the firewall. (3) Easy intrusion: Intrusion tutorials are everywhere; various tools are at your fingertips 2. Intrusion

In the previous sections, we have covered what is target detection and how to detect targets, as well as the concepts of sliding windows, bounding box, and IOU, non-maxima suppression.Here will summarize the current target detection research results, and several classical target detection algorithms to summarize, this article is based on deep learning target

With the increase in hacker technology, wireless LAN (WLANs) is under more and more threats. Session hijacking and DoS attacks caused by misconfiguration of wireless base stations (WAPs) affect the security of Wireless LAN. Wireless networks are not only attacked based on the traditional wired network TCP/IP architecture, but may also be threatened by the security issues of the 802.11 standard issued by the Institute of Electrical and Electronics Engineers (IEEE. To better detect and defend agai

Now with the improvement of hacker technology, the wireless local area network (WLANS) is threatened more and more. The failure to configure a wireless base station (WAPS) causes session hijacking and denial of service attacks (Dos) to be like a plague that affects the security of wireless LANs in general. Wireless networks are vulnerable not only to the traditional wired network TCP/IP architecture but also to the security issues of the Institute of Electrical and Electronics Engineers (IEEE) r

Rapid objectdetection using a Boosted Cascade of simple Features fast target detection using the easy feature cascade classifierNote: Some translations are not allowed in a red fontTranslation, Tony,[email protected]Summary:This paper introduces a vision application of machine learning in target detection, which can process images quickly and achieve a higher recognition rate. The success of this work is du

Article Title: perfect solution for using the intrusion detection system in linux. Linux is a technology channel of the IT lab in China. Includes basic categories such as desktop applications, Linux system management, kernel research, embedded systems, and open source. 　　 Introduction to intrusion detection systems As more and more companies transfer their core services to the Internet, network security is

(reproduced, did not find the original source, such as invasion of the deletion or reminder to increase the source, thank you.) ) Pedestrian detection resources (top) Review literature http://www.cvrobot.net/pedestrian-detection-resource-1-summary-review-survey/ Pedestrian detection resources (below) code data http://www.cvrobot.net/pedestrian-

sensitive profiles, power through kernel exploits, use scripts that can be invoked by root users under a low-privileged user directory, task scheduling, and so on (from getting started to giving up) (4) Very strong concealment Some malicious web scripts can be nested in a normal web page to run, and not easily be avira. Webshell can also traverse the server firewall, because the data that interacts with the controlled server or remote host is passed through 80 ports, so it is not blocked by the

Webshell detection-Log Analysis It is always believed that the final meaning of log analysis is evidence collection and prediction-a complete story of ongoing, ongoing, and future attacks (when. where. who. what happened. why ).This article explains how to identify webshell, that is, to trace the attack events that have occurred from the identified attack events. The implanted webshell is undoubtedly a definite attack event, as long as it has been pas

Reprint Please specify source: http://blog.csdn.net/lsh_20131 IntroductionThe edge detection of digital image is an important foundation of image processing such as segmentation, target recognition and region shape extraction. In the image understanding and analysis, the first step is often edge detection. At present, edge Detection has become one of the most act

1. R-cnn:rich feature hierarchies for accurate object detection and semantic segmentationTechnical route: Selective search + CNN + SVMsSTEP1: Candidate Box extraction (selective search)Training: Given a picture, use the Seletive search method to extract 2000 candidate boxes from it. Due to the size of the candidate boxes, considering that the subsequent CNN requires a uniform image size, the 2000 candidate boxes all resize to the 227*227 resolution (i

One of the target detection (traditional algorithm and deep learning source learning) This series of writing about target detection, including traditional algorithms and in-depth learning methods will involve, focus on the experiment and not focus on the theory, theory-related to see the paper, mainly rely on OPENCV. First, what is the target detection algorithms

First, Background introductionSkin detection has been widely used in many computer applications such as face recognition and tracking, gesture recognition, image retrieval and classification. The above research topics must solve a fundamental problem, that is, the image is precisely divided into two areas of the skin and background, the accuracy of the division is directly affecting the precision and performance of the follow-up work, so skin

This paper aims at the vulnerabilities of intrusion detection system to understand the hacker's intrusion methods. Once the network intrusion detection system is installed, the network intrusion detection system will analyze the hacker attacks on the Internet, and you can use the counterattack function of this intrusion detec