نتایج جستجو برای: intrusion detection systems idss
تعداد نتایج: 1697787 فیلتر نتایج به سال:
Intrusion Detection Systems (IDSs) for Mobile Ad hoc NETworks (MANETs) are indispensable since traditional intrusion prevention based techniques are not strong enough to protect MANETs. However, the dynamic environment of MANETs makes the design and implementation of IDSs a very challenging task. In this paper, we present a non-overlapping Zone-Based Intrusion Detection System (ZBIDS) that fits...
Currently, intrusion detection systems (IDSs) are widely deployed in enterprise networks for detecting network attacks. Most existing commercial IDSs are based on misuse detection model. In misuse detection, although known attacks can be detected, unknown ones cannot be detected because attack signatures for unknown attacks cannot be generated. In this paper, we propose a method for detecting n...
In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). Poisoning attack, which is one of the most recognized security threats towards machine learning-based IDSs, injects some adversarial samples into the training phase, inducing data drifting of training data and a significant performance decrease of target IDSs over testing data. In this pape...
Intrusion detection systems (IDSs) must meet the security goals while minimizing risks of wrong detections. In this paper, we study the issue of building a risk-sensitive intrusion detection mode1. To determinate whether a system calls sequence is normal or not, we consider not only the probability of this sequence belonging to normal sequences set or intrusion sequences set, but also the risk ...
Intrusion detection systems (IDS) strive to catch computer system intrusion & utilize by any garnering and analyzing data. Wireless IDSs garner all local wireless transmissions and generate alerts based either on predefined signatures or on anomalies in the traffic. These wireless IDS can monitor and analyze user and system activities of known attacks, identity abnormal network activity and det...
Intrusion detection systems (IDSs) are well-known and widely-deployed security tools to detect cyber-attacks and malicious activities in computer systems and networks. A signature-based IDS works similar to anti-virus software. It employs a signature database of known attacks, and a successful match with current input raises an alert. A signature-based IDS cannot detect unknown attacks, either ...
Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network...
To be effective, current intrusion detection systems (IDSs) must incorporate artificial intelligence methods for plan recognition. Plan recognition is critical both to predicting the future actions of attackers and planning appropriate responses to their actions. However network security places a new set of requirements on plan recognition. In this paper we present an argument for including pla...
Intrusion detection systems (IDSs) are currently drawing a great amount of interest as a key part of system defence. IDSs collect network traffic information from some point on the network or computer system and then use this information to secure the network. Recently, machine learning methodologies are playing an important role in detecting network intrusions (or attacks), which further helps...
Due to the increase in access of malicious data over the internet resources, intrusions Detection Systems (IDSs) have become the necessary component of the computer and information security framework. Although the field of IDSs is still developing, they are not able to detect all types of intrusions. New intelligent Intrusion Detection Systems (IDSs) which are based on sophisticated algorithms ...
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