Identification And Security Analysis Of Network Video Surveillance Device

With the progress of Internet of things technology,the market demand is gradually increasing,and the security problems caused by it are increasing.The threat and scale of the vulnerability are gradually increasing.Such as in recent years about the webcam broke the large area network paralysis,a large number of network video monitoring equipment from abroad by IP control,many family cameras were invasion,monitor equipment safety brought great threat also gradually aroused the attention of domestic and international numerous safety staff.Due to the wide distribution of webcams,many video contents involve important privacy,which makes webcams easy to be used and cause large-scale harm.However,network video monitoring system security maintenance function is not perfect,the lack of effective identification algorithms for network video monitoring equipment and related safety effective detection and analysis of the third party testing tools,so we focus on the entire network video monitoring equipment identification and on the basis of vulnerability analysis.In the aspect of network video monitoring equipment identification,this paper proposes an online identification method based on double factor network video monitoring equipment.The method using single packet detection and stateless scanning technology through service slogan and page text content within the entire network on nearly four billion network address,which can identify offline matches for identify the location of the monitoring equipment information.Results show that we identified in 20 hours from the entire network of 1.36 million network video monitoring equipment,is concentrated in the United States,China,Brazil and domestic is concentrated distribution in Taiwan and the southeast coastal areas.In terms of network video monitoring equipment online vulnerability analysis,we identified on the basis of network video monitoring equipment,the equipment is used to detect the privacy,including equipment for detecting weak passwords,bypass authentication access holes,Web authentication to bypass the leak detection and rebound shell leak detection,the results show that in 1.36 million there are 390000 of equipment loophole.Due to network video monitoring system has the character of complexity,depend on each other,this paper establish complex coupling interdependent scale-free network model,and carries on the vulnerability analysis,the results show that with complex coupling degree of scale-free networks of mutual dependence has the maximum load node attack,attack and random maximum node attack with the same vulnerability.This article is based on double factor network video monitoring equipment on-line identification method of entire network scanning,to identify the network video monitoring equipment safety testing,analyzing the vulnerability of complex coupling network video monitoring.For security professionals for the vulnerability analysis of video monitoring..equipment,in order to further to maintain network video monitoring system and network security situational awareness,as well as the combination of artificial intelligence,machine learning algorithm found potential vulnerabilities and concealment of the invasion and high-risk security early warning,etc.