• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.91-105
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• 2002

The attackers on Internet-connected systems we are seeing today are more serious and technically complex than those in the past. So it is beyond the scope of amy one system to deal with the intrusions. That the multiple IDSes (Intrusion Detection System) coordinate by sharing attacker's information for the effective detection of the intrusion is the effective method for improving the intrusion detection performance. The system which uses BBA (BlackBoard Architecture) for the information sharing can be easily expanded by adding new agents and increasing the number of BB (BlackBoard) levels. Moreover the subdivided levels of blackboard enhance the sensitivity of the intrusion detection. For the simulation, security models are constructed based on the DEVS (Discrete EVent system Specification) formalism. The intrusion detection agent uses the ES (Expert System). The intrusion detection system detects the intrusions using the blackboard and the firewall responses these detection information.

• ETRI Journal
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• v.43 no.2
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• pp.332-343
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• 2021

With cyberattack techniques on the rise, there have been increasing developments in the detection techniques that defend against such attacks. However, cyber attackers are now developing fileless malware to bypass existing detection techniques. To combat this trend, security vendors are publishing analysis reports to help manage and better understand fileless malware. However, only fragmentary analysis reports for specific fileless cyberattacks exist, and there have been no comprehensive analyses on the variety of fileless cyberattacks that can be encountered. In this study, we analyze 10 selected cyberattacks that have occurred over the past five years in which fileless techniques were utilized. We also propose a methodology for classification based on the attack techniques and characteristics used in fileless cyberattacks. Finally, we describe how the response time can be improved during a fileless attack using our quick and effective classification technique.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.203-216
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• 2019

The nature of wireless transmission has made wireless sensor networks defenseless against various attacks. This paper presents warning message counter method (WMC) to detect blackhole attack, grayhole attack and sinkhole attack in wireless sensor networks. The objective of these attackers are, to draw the nearby network traffic by false routing information and disrupt the network operation through dropping all the received packets (blackhole attack), selectively dropping the received packets (grayhole and sinkhole attack) and modifying the content of the packet (sinkhole attack). We have also attempted light weighted symmetric key cryptography to find data modification by the sinkhole node. Simulation results shows that, WMC detects sinkhole attack, blackhole attack and grayhole attack with less false positive 8% and less false negative 6%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1659-1673
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• 2019

Android platform provides In-app Billing service for purchasing valuable items inside mobile applications. However, it has become a major target for attackers to achieve valuable items without actual payment. Especially, application developers suffer from automated attacks targeting all the applications in the device, not a specific application. In this paper, we propose a novel scheme detecting automated attacks with probabilistic tests. The scheme tests the signature verification method in a non-deterministic way, and if the method was replaced by the automated attack, the scheme detects it with very high probability. Both the analysis and the experiment result show that the developers can prevent their applications from automated attacks securely and efficiently by using of the proposed scheme.

• ETRI Journal
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• v.43 no.3
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• pp.549-560
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• 2021

Cyberattacks are often difficult to identify with traditional signature-based detection, because attackers continually find ways to bypass the detection methods. Therefore, researchers have introduced artificial intelligence (AI) technology for cybersecurity analysis to detect malicious PowerShell scripts. In this paper, we propose a feature optimization technique for AI-based approaches to enhance the accuracy of malicious PowerShell script detection. We statically analyze the PowerShell script and preprocess it with a method based on the tokens and abstract syntax tree (AST) for feature selection. Here, tokens and AST represent the vocabulary and structure of the PowerShell script, respectively. Performance evaluations with optimized features yield detection rates of 98% in both machine learning (ML) and deep learning (DL) experiments. Among them, the ML model with the 3-gram of selected five tokens and the DL model with experiments based on the AST 3-gram deliver the best performance.

• Electronics and Telecommunications Trends
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• v.36 no.5
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• pp.21-31
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• 2021

Ransomware attacks, such as Conti, Ryuk, Petya, and Sodinokibi, that target medical institutions are increasing rapidly. In 2020, in the United States., ransomware attacks affected over 600 separate clinics, hospitals, and organizations, and more than 18 million patient records. The cost of these attacks is estimated to be almost $21 billion USD. The first death associated with a ransomware attack was reported in 2020 by the University Hospital of Düesseldorf in Germany. In the case of medical institutions, as introduced in the Medjack report issued by TrapX Labs, in many cases, attackers target medical devices that are relatively insecure and then penetrate deep into more critical network infrastructure, such as EMR servers. This paper introduces security vulnerabilities of hospital medical devices, considerations for ransomware response by medical institutions, and related technology trends.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6B
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• pp.219-232
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• 2008

A novel idea of protocol security analysis is presented based on trusted freshness. The idea has been implemented not only by hand but also by a belief muitisets formalism for automation. The key of the security analysis based on trusted freshness is a freshness principle: for each participant of a cryptographic protocol, the security of the protocol depends only on the sent or received one-way transformation of a message, which includes a trusted freshness. The manual security analysis method and the belief multisets formalism are all established on the basis of the freshness principle. Security analysis based on trusted freshness can efficiently distinguish whether a message is fresh or not, and the analysis results suggest the correctness of a protocol convincingly or the way to construct attacks intuitively from the absence of security properties. Furthermore, the security analysis based on trusted freshness is independent of the idealization of a protocol, the concrete formalization of attackers' possible behaviors, and the formalization of concurrent runs of protocols.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1159-1168
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• 2012

Control Flow Integrity(CFI) and Control Flow Locking(CFL) prevent unintended execution of software and provide integrity in control flow. Attackers, however, can still hijack program controls since CFI and CFL does not support fine-granularity, context-sensitive protection. In this paper, we propose a new CFI scheme, Source-code CFI(SCFI), to overcome the problems. SCFI provides context-sensitive locking for control flow. Thus, the proposed approach protects software against the attacks on the previous CFI and CFL schemes and improves safety.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.294-303
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• 2021

VANET is an upcoming technology with an encouraging prospect as well as great challenges, specifically in its security. This paper intends to survey such probable attacks and the correlating detection mechanisms that are introduced in the literature. Accordingly, administering security and protecting the owner's privacy has become a primary argument in VANETs. To furnish stronger security and preserve privacy, one should recognize the various probable attacks on the network and the essence of their behavior. This paper presents a comprehensive survey on diversified attacks and the recommended unfolding by the various researchers which concentrate on security services and the corresponding countermeasures to make VANET communications more secure.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.103-112
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• 2022

Background: A presentation attack places the printed image or displayed video at the front of the sensor to deceive the biometric recognition system. Usually, presentation attackers steal a genuine user's biometric image and use it for presentation attack. In recent years, reconstruction attack and adversarial attack can generate high-quality fake images, and have high attack success rates. However, their attack rates degrade remarkably after image shooting. Methods: In order to comprehensively analyze the threat of presentation attack to palmprint recognition system, this paper makes six palmprint presentation attack datasets. The datasets were tested on texture coding-based recognition methods and deep learning-based recognition methods. Results and conclusion: The experimental results show that the presentation attack caused by the leakage of the original image has a high success rate and a great threat; while the success rates of reconstruction attack and adversarial attack decrease significantly.