P2P Distributed Intrusion Detections by Using Mobile Agents

Ye, Dayong; Bai, Quan; Zhang, Minjie; Ye, Zhen

doi:10.1109/icis.2008.21

Cited by 20 publications

(16 citation statements)

References 6 publications

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“…Dastjerdi et al [78] propose a new IDS system by combining and extending the peer-to-peer IDS based on mobile agents [79] and the distributed intrusion detection using mobile agent (DIDMA) [80]. It consists of four main components namely IDS control center (IDS CC), agency, application specific static agent detector and specialized investigative mobile agent.…”

Section: Intrusion Detection Systems (Ids)mentioning

confidence: 99%

Cloud Computing Security: A Survey

2014

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Cloud computing is an emerging technology paradigm that migrates current technological and computing concepts into utility-like solutions similar to electricity and water systems. Clouds bring out a wide range of benefits including configurable computing resources, economic savings, and service flexibility. However, security and privacy concerns are shown to be the primary obstacles to a wide adoption of clouds. The new concepts that clouds introduce, such as multi-tenancy, resource sharing and outsourcing, create new challenges to the security community. Addressing these challenges requires, in addition to the ability to cultivate and tune the security measures developed for traditional computing systems, proposing new security policies, models, and protocols to address the unique cloud security challenges. In this work, we provide a comprehensive study of cloud computing security and privacy concerns. We identify cloud vulnerabilities, classify known security threats and attacks, and present the state-of-the-art practices to control the vulnerabilities, neutralize the threats, and calibrate the attacks. Additionally, we investigate and identify the limitations of the current solutions and provide insights of the future security perspectives. Finally, we provide a cloud security framework in which we present the various lines of defense and identify the dependency levels among them. We identify 28 cloud security threats which we classify into five categories. We also present nine general cloud attacks along with various attack incidents, and provide effectiveness analysis of the proposed countermeasures. OPEN ACCESSComputers 2014, 3 2

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Section: Intrusion Detection Systems (Ids)mentioning

confidence: 99%

Cloud Computing Security: A Survey

2014

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“…The second is that when a system with a single central server and numerous clients, the scalability is a problem, as the server has to maintain many connections to the clients. In order to overcome the two problems, several P2P intrusion detection architectures were presented, like [15]. In this paper, we will utilize ETAP to demonstrate the detection process against Doorknob-Rattling attack [12] in a P2P environment.…”

Section: An Example Of Etap Potential Applicationmentioning

confidence: 99%

An Efficient Task Allocation Protocol for P2P Multi-agent Systems

Bai

Zhang

et al. 2009

2009 IEEE International Symposium on Parallel and Distributed Processing With Applications

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Recently, task allocation in multi-agent systems has been investigated by many researchers. Some researchers suggested to have a central controller which has a global view about the environment to allocate tasks. Although centralized control brings convenience during task allocation processes, it also has some obvious weaknesses. Firstly, a central controller plays an important role in a multi-agent system, but task allocation procedures will break down if the central controller of a system cannot work properly. Secondly, centralized multi-agent architecture is not suitable for distributed working environments. In order to overcome some limitations caused by centralized control, some researchers proposed distributed task allocation protocols. They supposed that each agent has a limited local view about its direct linked neighbors, and can allocate tasks to its neighbors. However, only involving direct linked neighbors could limit resource origins, so that the task allocation efficiency will be greatly reduced. In this paper, we propose an efficient task allocation protocol for P2P multi-agent systems. This protocol allows not only neighboring agents but also indirect linked agents in the system to help with a task if needed. Through this way, agents can achieve more efficient and robust task allocations in loosely coupled distributed environments (e.g. P2P multi-agent systems). A set of experiments are presented in this paper to evaluate the efficiency and adaptability of the protocol. The experiment result shows that the protocol can work efficiently in different situations. Abstract-Recently, task allocation in multi-agent systems has been investigated by many researchers. Some researchers suggested to have a central controller which has a global view about the environment to allocate tasks. Although centralized control brings convenience during task allocation processes, it also has some obvious weaknesses. Firstly, a central controller plays an important role in a multi-agent system, but task allocation procedures will break down if the central controller of a system cannot work properly. Secondly, centralized multiagent architecture is not suitable for distributed working environments. In order to overcome some limitations caused by centralized control, some researchers proposed distributed task allocation protocols. They supposed that each agent has a limited local view about its direct linked neighbors, and can allocate tasks to its neighbors. However, only involving direct linked neighbors could limit resource origins, so that the task allocation efficiency will be greatly reduced. In this paper, we propose an efficient task allocation protocol for P2P multi-agent systems. This protocol allows not only neighboring agents but also indirect linked agents in the system to help with a task if needed. Through this way, agents can achieve more efficient and robust task allocations in loosely coupled distributed environments (e.g. P2P multi-agent systems). A set of experiments are presented in this pap...

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“…Intrusion is a set of actions which attempt to comprise the confidentiality, denial of resources or unauthorized use of resources [1]. Intrusion Detection System (IDS) is used to detect various intrusions in network environment and to prevent information from malicious attackers [2]. Detection is not introduced to replace prevention-based techniques such as authentication and access control; instead, it is intended to complement existing security measures and detect actions that bypass the security monitoring and control component of the system [3].…”

Section: Introductionmentioning

confidence: 99%

“…This approach allows the detection of intrusions which the system has learned their signatures perfectly. Anomaly intrusion detection [7], [8], [9] are designed to detect general misuse and attacks for which no signature exists. This attempts to construct a model according to the statical knowledge about the normal activity of the computer system.…”

Section: Introductionmentioning

confidence: 99%

ACO based Distributed Intrusion Detection System

Janakiraman¹

2009

JDCTA

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Intrusion detection is a problem of great significance to protecting information systems security. An intruder may move between multiple nodes in the network to conceal the origin of attack. Distributed intrusion detection and prevention plays an increasingly important role in securing computer networks. To overcome the limitations of conventional intrusion detection systems, alerts are made in distributed intrusion detection system which are exchanged and correlated in a cooperative fashion. It is necessary to develop fast machine learning based intrusion detection algorithms with high detection rates and low false alarm rates, due to the variety of network behaviors and the rapid development of attack fashions. The system has to observe to trigger thousands of alerts per day, in which most are mistakenly triggered by the false identification. So it is difficult for the analyst to correctly identify alerts related to the attack. This paper presents an intelligent learning approach using Ant Colony Optimization (ACO) based distributed intrusion detection system to detect intrusions in the distributed network. The experimental results on the proposed system with the feature extraction algorithm is effective to detect the unseen intrusion attacks with high detection rate and recognize normal network traffic with low false alarm rate.

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P2P Distributed Intrusion Detections by Using Mobile Agents

Cited by 20 publications

References 6 publications

Cloud Computing Security: A Survey

Cloud Computing Security: A Survey

An Efficient Task Allocation Protocol for P2P Multi-agent Systems

ACO based Distributed Intrusion Detection System

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