The invention discloses an attack detection method and system for WEB; the method comprises the following steps: firstly implementing attack characteristic detection to the url accessed by a user; then implementing misinformation analysis and fail-to-declare analysis treatment to the detection result, wherein the misinformation analysis mainly solves the misinformation caused by normal embedded resources of the website and the web crawlers, the fail-to-declare analysis is to treat the undetected abnormal behaviors conducted by the detected abnormal users. Based on the results of the treatment above, calculating the total normal access time of each abnormal user under each domain name; when the access time is less than the average value of all users, taking the ratio between the access time and the average value as an abnormality scoring index of the abnormal user; otherwise, the abnormality score is a weighted value w of the ratio between the access time and the maximum access time of all users. By the misinformation analysis and fail-to-declare analysis treatment, the efficiency of the attack detection method and system for WEB is significantly increased.

Attack detection method and system for WEB

The invention discloses an intrusion detection rule creation method based on an industrial control network variant attack. The existing rule library of ModbusTCP abnormal flow is designed and summarized by analyzing the vulnerability of the ModbusTCP industrial control protocol, the genetic algorithm is improved in combination with the common attack variation manners of the existing industrial control network so as to automatically create an intrusion detection rule, the created rule is stored according to the adaption value thereof, the variant attack can be effectively detected, the rule library is expanded, and the intrusion detection rule creation method has the advantages of high detection accuracy and high instantaneity.

Intrusion detection rule creation method based on industrial control network variant attack

The invention provides an internet of things (IOT) intrusion detection method and device, and relates to the technical field of IOT security. The method comprises the steps of acquiring environmental data changed with time, wherein the environmental data comprises one or more data of light intensity, temperature, humidity, pressure, gravity, vibration frequency, position, speed, acceleration and volume; according to the environmental data at the current moment and the environmental data at the adjacent moment, calculating the fluctuation quantity of the environmental data at current moment relative to the environmental data at the adjacent moment; determining an intrusion detection model corresponding to traffic data at the current moment according to the fluctuation quantity, and performing intrusion detection on the traffic data at the current moment via the intrusion detection model, wherein the traffic data at the current moment corresponds to the environmental data at the current moment. The IOT intrusion detection method and device can solve the technical problems that the intrusion behavior cannot be accurately detected by adopting the existing IOT intrusion detection method and the detection result is unreliable.

Internet of things (IOT) intrusion detection method and device

The embodiment of the invention provides an IOT (Internet of things) invasion monitoring method and device, relating to the field of IOT safety. The method comprises a step of obtaining the data collected by an IOT sensing layer node by using sensing equipment, a step of establishing an IOT invasion classification model by using a TrAdaBoost method based on the obtained data as training data, wherein the IOT invasion classification comprises an invasion behavior set and a normal behavior set, a step of obtaining the test data collected by the IOT sensing layer node by using sensing equipment again, and carrying out classification judgment by using the IOT invasion classification model, and a step of carrying out interception and alarm processing if the test data is divided into the invasion behavior set. The problem of monitoring the invasion behavior of the IOT sensing layer is solved.

IOT invasion monitoring method and device

An experience-aware anomaly processing system and a method for an experience-aware anomaly processing system are provided. The experience-aware anomaly processing system comprises an anomaly detection module configured to receive geographic location data with corresponding time information of a target object, and analyze target object behavior based on the geographic location data with corresponding time information of the target object; a user feedback module configured to receive user feedback from a user and model user feedback behavior when the user receives an alarm message indicating the target object is abnormal; and a decision module configured to receive user setting from the user, and make a detection decision through fusing target object behavior information corresponding to the target object behavior, user feedback behavior information corresponding to the user feedback behavior, and the user setting.

Experience-aware anomaly processing system and method

The invention discloses an intrusion detecting method of an internet-of-things sensing layer, and relates to a safe detecting method of the internet-of-things sensing layer, in particular to a detecting method for judging whether intrusion behaviors exist in the internet of things by combining the feature detection technique and the abnormal detection technique In order to solve the problems that the false alarm rate and the omission rate are high and the detection rate is low in the prior art, the method is used for performing intrusion detecting by combining the feature detection technique and the abnormal detection technique Compared with the prior art, the method has the advantages of being low in false alarm rate and the omission rate, high in detection rate, good in timeliness and the like, and is suitable for the intrusion detection of abnormal behaviors of the internet-of-things sensing layer

Intrusion detecting method of internet-of-things sensing layer

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Hu Xiangdong

Author Tools

Chat about Author

Papers

Intrusion detecting method of internet-of-things sensing layer