• Title/Summary/Keyword: Security Techniques

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A Secure Active Packet Transfer using Cryptographic Techniques (암호 기술을 이용한 안전한 능동 패킷 전송)

  • 김영수;나중찬;손승원
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.12 no.2
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    • pp.135-145
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    • 2002
  • Active networks represent a new approach to network architecture. Nodes(routers, switches, etc.) can perform computations on user data, while packets can carry programs to be executed on nodes and potentially change the state of them. While active networks provide a flexible network iufrastructure, they are more complex than traditional networks and raise considerable security problems. Nodes are Public resources and are essential to the proper and contract running of many important systems. Therefore, security requirements placed upon the computational environment where the code of packets will be executed must be very strict. Trends of research for active network security are divided into two categories: securing active nodes and securing active packets. For example, packet authentication or monitoring/control methods are for securing active node, but some cryptographic techniques are for the latter. This paper is for transferring active packets securely between active nodes. We propose a new method that can transfer active packets to neighboring active nodes securely, and execute executable code included in those packets in each active node. We use both public key cryptosystem and symmetric key cryptosystem in our scheme

Framework Design for Malware Dataset Extraction Using Code Patches in a Hybrid Analysis Environment (코드패치 및 하이브리드 분석 환경을 활용한 악성코드 데이터셋 추출 프레임워크 설계)

  • Ki-Sang Choi;Sang-Hoon Choi;Ki-Woong Park
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.3
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    • pp.403-416
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    • 2024
  • Malware is being commercialized and sold on the black market, primarily driven by financial incentives. With the increasing demand driven by these sales, the scope of attacks via malware has expanded. In response, there has been a surge in research efforts leveraging artificial intelligence for detection and classification. However, adversaries are integrating various anti-analysis techniques into their malware to thwart analytical efforts. In this study, we introduce the "Malware Analysis with Dynamic Extraction (MADE)" framework, a hybrid binary analysis tool devised to procure datasets from advanced malware incorporating Anti-Analysis techniques. The MADE framework has the proficiency to autonomously execute dynamic analysis on binaries, encompassing those laden with Anti-VM and Anti-Debugging defenses. Experimental results substantiate that the MADE framework can effectively circumvent over 90% of diverse malware implementations using Anti-Analysis techniques and can adeptly extract relevant datasets.

How to use attack cases and intelligence of Korean-based APT groups (한국어 기반 APT 그룹의 공격사례 및 인텔리전스 활용 방안)

  • Lee Jung Hun;Choi Youn Sung
    • Convergence Security Journal
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    • v.24 no.3
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    • pp.153-163
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    • 2024
  • Despite the increasing hacking threats and security threats as IT technology advances and many companies adopt security solutions, cyberattacks and threats still persist for years. APT attack is a technique of selecting a specific target and continuing to attack. The threat of an APT attack uses all possible means through the electronic network to perform APT for years. Zero-day attacks, malicious code distribution, and social engineering techniques are performed, and some of them directly invade companies. These techniques have been in effect since 2000, and are similarly used in voice phishing, especially for social engineering techniques. Therefore, it is necessary to study countermeasures against APT attacks. This study analyzes the attack cases of Korean-based APT groups in Korea and suggests the correct method of using intelligence to analyze APT attack groups.

A Comprehensive Survey of TPM for Defense Systems

  • Cheol Ryu;Jae-Ho Lee;Do-Hyung Kim;Hyung-Seok Lee;Young-Sae Kim;Jin-Hee Han;Jeong-nyeo Kim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.7
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    • pp.1953-1967
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    • 2024
  • Lately, there has been a notable surge in the defense industry's efforts to develop highly advanced intelligent systems. These systems encompass sophisticated computing platforms that boast an impressive level of autonomy. However, it's important to acknowledge that these very systems are not impervious to vulnerabilities stemming from both hardware and software tampering. Within the context of this discourse, our focus of the survey is directed towards the hardware security module. This component stands out for its capability to offer a significantly heightened level of protection when compared to conventional software-based techniques. Through the lens of this paper, we embark on a comprehensive survey of Trusted Platform Module (TPM), a hardware security module, shedding light on its potential to fortify the defense against threats that emerge from various vectors of attack.

Research on Utilizing Emulab for Malware Analysis (악성코드 분석을 위한 Emulab 활용 방안 연구)

  • Lee, Man-hee;Seok, Woo-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.1
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    • pp.117-124
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    • 2016
  • Virtual environment is widely used for analyzing malware which is increasing very rapidly. However, knowing this trend, hackers are adopting virtual environment detection techniques for malware to kill itself or stop malicious behaviors when detecting virtual environments. Various research is going on in order to thwart any efforts to utilize anti-virtualization techniques, but until now several techniques can evade most of well known virtual environments, making malware analysis very difficult. Emulab developed by Utah University assigns real systems and networks as researchers want in realtime. This research seeks how to use Emulab for malware analysis.

Role of Machine Learning in Intrusion Detection System: A Systematic Review

  • Alhasani, Areej;Al omrani, Faten;Alzahrani, Taghreed;alFahhad, Rehab;Alotaibi, Mohamed
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.155-162
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    • 2022
  • Over the last 10 years, there has been rapid growth in the use of Machine Learning (ML) techniques to automate the process of intrusion threat detection at a scale never imagined before. This has prompted researchers, software engineers, and network specialists to rethink the applications of machine ML techniques particularly in the area of cybersecurity. As a result there exists numerous research documentations on the use ML techniques to detect and block cyber-attacks. This article is a systematic review involving the identification of published scholarly articles as found on IEEE Explore and Scopus databases. The articles exclusively related to the use of machine learning in Intrusion Detection Systems (IDS). Methods, concepts, results, and conclusions as found in the texts are analyzed. A description on the process taken in the identification of the research articles included: First, an introduction to the topic which is followed by a methodology section. A table is used to list identified research articles in the form of title, authors, methodology, and key findings.

Android Malware Detection using Machine Learning Techniques KNN-SVM, DBN and GRU

  • Sk Heena Kauser;V.Maria Anu
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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    • pp.202-209
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    • 2023
  • Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

Voice Verification System for m-Commerce on CDMA Network

  • Kyung, Youn-Jeong
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.4E
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    • pp.176-182
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    • 2003
  • As the needs for wireless Internet service is increasing, the needs for secure m-commerce is also increasing. Conventional security techniques are reinforced by biometric security technique. This paper utilized the voice as biometric security techniques. We developed speaker verification system for m-commerce (mobile commerce) via wireless internet and wireless application protocol (WAP). We named this system the mVprotek. We implemented the system as client-server architecture. The clients are mobile phone simulator and personal digital assistant (PDA). The verification results are obtained by integrating the mVprotek system with SK Telecom's code dimension multiple access (CDMA) system. Utilizing f-ratio weighting and virtual cohort model normalization showed much better performance than conventional background model normalization technique.

Systems Analysis of the Internet E-Mail Security Using IDEFO Modeling (IDEFO 모델링을 이용한 인터넷 전자우편 보안시스템 분석)

  • Kim, Joong-In;Kim, Seok-Woo
    • IE interfaces
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    • v.9 no.3
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    • pp.249-256
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    • 1996
  • The Internet e-mail security software and standards, such as PGP (Pretty Good Privacy) and PEM (Privacy Enhanced Mail), have several limitations that should be overcome for their further applications to the Internet and network environments. In order to improve and reengineer those software, details of the As-Is software processing should be analyzed. One of the possible techniques for software analysis is IDEFO function modeling. Although IDEFO has been mainly used for BPR as one of the industrial engineering techniques, it has been rarely applied to the analysis of software processing and reengineering in computer and software engineering fields. Additionally, no sufficient details of PGP and PEM processing are analyzed in the literature. The objective of this paper is to demonstrate the application of the IDEFO to the systems analysis of the Internet e-mail security software as well as to provide software developers with the basis for software improvements.

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A Secure WLAN Authentication Scheme

  • Singh, Rajeev;Sharma, Teek Parval
    • IEIE Transactions on Smart Processing and Computing
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    • v.2 no.3
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    • pp.176-187
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    • 2013
  • Message replay, malicious Access Point (AP) associations and Denial of Service (DoS) attacks are the major threats in Wireless LANs. These threats are possible due to a lack of proper authentication and insecure message communications between wireless devices. Current wireless authentication & key exchange (AKE) schemes and security protocols (WEP, WPA and IEEE 802.11i) are not sufficient against these threats. This paper presents a novel Secure WLAN Authentication Scheme (SWAS). The scheme introduces the delegation concept of mobile authentication in WLANs, and provides mutual authentication to all parties (Wireless Station, Access Point and Authentication Server). The messages involved in the process serve both authentication and key refreshing purposes. The scheme enhances the security by protecting the messages through cryptographic techniques and reduces the DoS impact. The results showed that cryptographic techniques do not result in extra latencies in authentication. The scheme also reduces the communication cost and network overhead.

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