• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1721-1736
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• 2013

Black and gray hole attack is one kind of routing disturbing attacks and can bring great damage to the network. As a result, an efficient algorithm to detect black and gray attack is important. This paper demonstrate an adaptive approach to detecting black and gray hole attacks in ad hoc network based on a cross layer design. In network layer, we proposed a path-based method to overhear the next hop's action. This scheme does not send out extra control packets and saves the system resources of the detecting node. In MAC layer, a collision rate reporting system is established to estimate dynamic detecting threshold so as to lower the false positive rate under high network overload. We choose DSR protocol to test our algorithm and ns-2 as our simulation tool. Our experiment result verifies our theory: the average detection rate is above 90% and the false positive rate is below 10%. Moreover, the adaptive threshold strategy contributes to decrease the false positive rate.

• Convergence Security Journal
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• v.14 no.7
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• pp.17-22
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• 2014

Wireless Ad hoc Network is threatened from many types of attacks because of its open structure, dynamic topology and the absence of infrastructure. Attacks by malicious nodes inside the network destroy communication path and discard packet. The damage is quite large and detecting attacks are difficult. In this paper, we proposed attack detection technique using secure authentication infrastructure for efficient detection and prevention of internal attack nodes. Cluster structure is used in the proposed method so that each nodes act as a certificate authority and the public key is issued in cluster head through trust evaluation of nodes. Symmetric Key is shared for integrity of data between the nodes and the structure which adds authentication message to the RREQ packet is used. ns-2 simulator is used to evaluate performance of proposed method and excellent performance can be performed through the experiment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• Convergence Security Journal
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• v.13 no.1
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• pp.19-24
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• 2013

MANET has a highly dynamic topology because it consists of only mobile nodes. Various attacks using these characteristics exist. Among them, damage of the attacks based flooding such as DoS or DDos is large and traceback of the attack node is not easy. It is because route information by moving of intermediate nodes which pass the data changes frequently. In this paper, we propose table-based traceback technique to perform efficient traceback although route information by moving of nodes changes frequently. Cluster head manages route management table in order to form cluster status table and network topology snapshot for storing the location information of mobile nodes when cluster member nodes change. Also, bloom filter is used to reduce the amount of storing route information. The performance of the proposed technique is confirmed through experiment.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.127-135
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• 2007

As the Internet is used widely, criminal offense that use computer is increasing, and an information security technology to remove this crime is becoming competitive power of the country. In this paper, we suggest network-based intrusion detection system that use fuzzy expert system. This system can decide quick intrusion decision from attack pattern applying fuzzy rule through the packet classification method that is done similarity of protocol and fixed time interval. Proposed system uses fuzzy logic to detect attack from network traffic, and gets analysis result that is automated through fuzzy reasoning. In present network environment that must handle mass traffic, this system can reduce time and expense of security

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.64-72
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• 2024

In recent times cyber attackers can use Artificial Intelligence (AI) to boost the sophistication and scope of attacks. On the defense side, AI is used to enhance defense plans, to boost the robustness, flexibility, and efficiency of defense systems, which means adapting to environmental changes to reduce impacts. With increased developments in the field of information and communication technologies, various exploits occur as a danger sign to cyber security and these exploitations are changing rapidly. Cyber criminals use new, sophisticated tactics to boost their attack speed and size. Consequently, there is a need for more flexible, adaptable and strong cyber defense systems that can identify a wide range of threats in real-time. In recent years, the adoption of AI approaches has increased and maintained a vital role in the detection and prevention of cyber threats. In this paper, an Ensemble Deep Restricted Boltzmann Machine (EDRBM) is developed for the classification of cybersecurity threats in case of a large-scale network environment. The EDRBM acts as a classification model that enables the classification of malicious flowsets from the largescale network. The simulation is conducted to test the efficacy of the proposed EDRBM under various malware attacks. The simulation results show that the proposed method achieves higher classification rate in classifying the malware in the flowsets i.e., malicious flowsets than other methods.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.119-128
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• 2024

The moveable ad hoc networks are untrustworthy and susceptible to any intrusion because of their wireless interaction approach. Therefore the information from these networks can be stolen very easily just by introducing the attacker nodes in the system. The straight route extent is calculated with the help of hop count metric. For this purpose, routing protocols are planned. From a number of attacks, the wormhole attack is considered to be the hazardous one. This intrusion is commenced with the help of couple attacker nodes. These nodes make a channel by placing some sensor nodes between transmitter and receiver. The accessible system regards the wormhole intrusions in the absence of intermediary sensor nodes amid target. This mechanism is significant for the areas where the route distance amid transmitter and receiver is two hops merely. This mechanism is not suitable for those scenarios where multi hops are presented amid transmitter and receiver. In the projected study, a new technique is implemented for the recognition and separation of attacker sensor nodes from the network. The wormhole intrusions are triggered with the help of these attacker nodes in the network. The projected scheme is utilized in NS2 and it is depicted by the reproduction outcomes that the projected scheme shows better performance in comparison with existing approaches.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.415-425
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• 2010

In public network, user authentication is important security technology. Especially, password-based authentication method is used the most widely in distributed environments, and there are many authentication methods. Their SPMA protocol indicates vulnerability about problem that NSPA protocol does not offer mutual authentication, and proposed Strong Password Mutual Authentication protocol with mutual authentication. However, SPMA protocol has vulnerability of replay attack. In the paper, we analyzed vulnerability to replay attack of SPMA protocol. And we also proposed Improved Strong Password Mutual Authentication protocol to secure on replay attack with same efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.94-102
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• 2016

In this work we propose a new method to countermeasure against the abatement attack to the security server that is induced by man-in-the-middle attack. To that purpose, we first investigate the state of the art in the current research about the abatement attack. After that, we propose a new countermeasure method that can cope with the unresolved problems in the current method, which can cover diverse types of network.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.185-192
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• 2006

By mistaking normal packets for harmful traffic, it may not offer service according to the intention of attacker with harmful traffic, because it is not easy to classify network traffic for normal service and it for DUoS(Distributed DoS) attack like the Internet worm. And in the IPv6 environment these researches on harmful traffic are weak. In this dissertation, hosts in the IPv6 environment are attacked by NETWIB and their attack traffic is monitored, then the statistical information of the traffic is obtained from MIB(Management Information Base) objects used in the IPv6. By adapting the ESM(Exponential Smoothing Method) to this information, a normal traffic boundary, i.e., a threshold is determined. Input traffic over the threshold is thought of as attack traffic.