• 제목/요약/키워드: Threat Intelligence

검색결과 128건 처리시간 0.021초

The Effectiveness of Information Protection and Improvement Plan Based on SMEs Consulting Case

  • Kim, Jae-Nam
    • 한국컴퓨터정보학회논문지
    • /
    • 제24권11호
    • /
    • pp.201-208
    • /
    • 2019
  • 지능정보사회의 포노 사피엔스 시대에 대부분 기업 활동은 네트워크 및 정보시스템에 대한 의존도가 더욱 높아지고 있다. 우리나라 기업의 대부분을 차지하고 있는 중소기업은 보유하고 있는 정보 자산의 가치와 기술력이 점차 증가하고 있고 기업 성장의 원동력이 되는 핵심기술에 대한 보호역량은 기업의 가장 중요한 경쟁력이 될 것이다. 이에 따라 과학기술정보통신부와 한국인터넷진흥원은 높은 수준의 기업 맞춤형 정보보호 컨설팅 지원을 통해 중소기업의 현재 정보보호 수준을 평가하고 정보보호 역량을 제고함으로써 해킹, 정보유출 등 각종 사이버 위협으로부터 받는 피해를 최소화할 수 있는 기반을 제공하고 있다. 본 연구에서는 한국인터넷진흥원에서 수행한 중소기업 정보보호 컨설팅 결과를 기반으로 정보보호 효과를 분석하고 중소기업 정보보호 컨설팅 결과에서 도출된 문제점과 한계점을 파악하여 중소기업이 정보보호 관리체계를 보다 효율적이고 효과적으로 관리할 수 있는 중소기업 정보보호의 개선방안을 제안하도록 한다.

자율 운항 선박의 인공지능: 잠재적 사이버 위협과 보안 (Artificial Intelligence for Autonomous Ship: Potential Cyber Threats and Security)

  • 유지운;조용현;차영균
    • 정보보호학회논문지
    • /
    • 제32권2호
    • /
    • pp.447-463
    • /
    • 2022
  • 인공 지능(AI) 기술은 해양 산업에서 스마트 선박을 자율 운항 선박으로 발전시키는 주요 기술이다. 자율 운항 선박은 사람의 의사 판단 없이 수집된 정보로 상황을 인식하며 스스로 판단하여 운항한다. 기존의 선박 시스템은 육상에서의 제어 시스템과 마찬가지로 사이버 공격에 대한 보안성을 고려하여 설계되지 않았다. 이로 인해 선박 내·외부에서 수집되는 수많은 데이터에 대한 침해와 선박에 적용될 인공지능 기술에 대한 잠재적 사이버 위협이 존재한다. 자율 운항 선박의 안전성을 위해서는 선박 시스템의 사이버 보안뿐만 아니라, 인공지능 기술에 대한 사이버 보안에도 초점을 맞춰야 한다. 본 논문에서는 기존 선박 시스템과 자율 운항 선박에 적용될 인공지능 기술에 발생할 수 있는 잠재적인 사이버 위협을 분석하고, 자율 운항 선박 보안 위험과 보안이 필요한 범주를 도출했다. 도출한 결과를 바탕으로 향후 자율 운항 선박 사이버 보안 연구 방향을 제시하고 사이버 보안 향상에 기여한다.

Reference 기반 AI 모델의 효과적인 해석에 관한 연구 (A Study on Effective Interpretation of AI Model based on Reference)

  • 이현우;한태현;박영지;이태진
    • 정보보호학회논문지
    • /
    • 제33권3호
    • /
    • pp.411-425
    • /
    • 2023
  • 오늘날 AI(Artificial Intelligence) 기술은 다양한 분야에서 활용 목적에 맞게 분류, 회기 작업을 수행하며 광범위하게 활용되고 있으며, 연구 또한 활발하게 진행 중인 분야이다. 특히 보안 분야에서는 예기치 않는 위협을 탐지해야 하며, 모델 훈련과정에 알려진 위협 정보를 추가하지 않아도 위협을 탐지할 수 있는 비 지도학습 기반의 이상 탐지 기법이 유망한 방법이다. 하지만 AI 판단에 대한 해석 가능성을 제공하는 선행 연구 대부분은 지도학습을 대상으로 설계되었기에 학습 방법이 근본적으로 다른 비 지도학습 모델에 적용하기는 어려우며, Vision 중심의 AI 매커니즘 해석연구들은 이미지로 표현되지 않는 보안 분야에 적용하기에 적합하지 않다. 따라서 본 논문에서는 침해공격의 원본인 최적화 Reference를 탐색하고 이와 비교함으로써 탐지된 이상에 대한 해석 가능성을 제공하는 기법을 활용한다. 본 논문에서는 산출된 Reference를 기반으로 실존 데이터에서 가장 가까운 데이터를 탐색하는 로직을 추가 제안함으로써 실존 데이터를 기반으로 이상 징후에 대한 더욱 직관적인 해석을 제공하고 보안 분야에서의 효과적인 이상 탐지모델 활용을 도모하고자 한다.

EMICS: E-mail based Malware Infected IP Collection System

  • Lee, Taejin;Kwak, Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제12권6호
    • /
    • pp.2881-2894
    • /
    • 2018
  • Cyber attacks are increasing continuously. On average about one million malicious codes appear every day, and attacks are expanding gradually to IT convergence services (e.g. vehicles and television) and social infrastructure (nuclear energy, power, water, etc.), as well as cyberspace. Analysis of large-scale cyber incidents has revealed that most attacks are started by PCs infected with malicious code. This paper proposes a method of detecting an attack IP automatically by analyzing the characteristics of the e-mail transfer path, which cannot be manipulated by the attacker. In particular, we developed a system based on the proposed model, and operated it for more than four months, and then detected 1,750,000 attack IPs by analyzing 22,570,000 spam e-mails in a commercial environment. A detected attack IP can be used to remove spam e-mails by linking it with the cyber removal system, or to block spam e-mails by linking it with the RBL(Real-time Blocking List) system. In addition, the developed system is expected to play a positive role in preventing cyber attacks, as it can detect a large number of attack IPs when linked with the portal site.

A Study on UCC and Information Security for Personal Image Contents Based on CCTV-UCC Interconnected with Smart-phone and Mobile Web

  • Cho, Seongsoo;Lee, Soowook
    • International Journal of Internet, Broadcasting and Communication
    • /
    • 제7권2호
    • /
    • pp.56-64
    • /
    • 2015
  • The personal image information compiled through closed-circuit television (CCTV) will be open to the internet with the technology such as Long-Tail, Mash-Up, Collective Intelligence, Tagging, Open Application Programming Interface (Open-API), Syndication, Podcasting and Asynchronous JavaScript and XML (AJAX). The movie User Created Contents (UCC) connected to the internet with the skill of web 2.0 has the effects of abuse and threat without precedent. The purpose of this research is to develop the institutional and technological method to reduce these effects. As a result of this research, in terms of technology this paper suggests Privacy Zone Masking, IP Filtering, Intrusion-detection System (IDS), Secure Sockets Layer (SSL), public key infrastructure (PKI), Hash and PDF Socket. While in terms of management this paper suggests Privacy Commons and Privacy Zone. Based on CCTV-UCC linked to the above network, the research regarding personal image information security is expected to aid in realizing insight and practical personal image information as a specific device in the following research.

침입탐지 시스템 관리를 위한 침입경보 축약기법 적용에 관한 연구 (A Study on Intrusion Alert Redustion Method for IDS Management)

  • 김석훈;정진영;송정길
    • 융합보안논문지
    • /
    • 제5권4호
    • /
    • pp.1-6
    • /
    • 2005
  • 네트워크 시스템에 대한 악의적인 접근과 정보위협이 증가하고, 그 피해또한 기업에서 개인 사용자까지 확대되고 있다. 침입탐지 시스템, 침입차단 시스템 등 단위 보안 기능만을 제공하는 제품은 분산화, 지능화 되어가고 있는 복합적인 침입에 대한 대응에 한계가 있다. 여러 보안 제품을 연동하여 해커의 침입탐지, 대응 및 역 추적을 위한 통합 보안 관리의 필요성이 대두되고 있다. 그러나 통합보안 관리의 특성상 다양한 보안 제품에서 전송된 이벤트와 침입경보의 양이 많아 분석이 어려워 서버측의 부담이 되고 있다. 따라서 본 논문에서는 이러한 문제점을 해결하고자 침입경보 데이터를 축약하는 방법에 대하여 연구하고자 한다.

  • PDF

소셜매뉴팩처링플랫폼의 참여의도에 영향을 미치는 요인에 관한 연구 (A Study on Factors Affecting the Participation of Social Manufacturing Platforms)

  • 길이훈;김광용
    • 한국IT서비스학회지
    • /
    • 제14권3호
    • /
    • pp.147-161
    • /
    • 2015
  • The rapid changes in consumption patterns and the manufacturing industry environment are both a threat and an opportunity for small and medium-sized enterprises in Korea because it lacks innovative capacity compared to large conglomerates. In this new manufacturing environment, social manufacturing is an innovative business model that can create new business opportunities for these companies. However, there are not that many proven models of platforms where products are created jointly with consumers. Some conceptual analysis of the success factors and operation strategy of co-creation platforms have started to be released but there are almost no empirical studies conducted on this matter today. In this study, the social manufacturing platform business concept and its components were studied; various factors that affect the willingness to participate in consumer-led co-creation platforms were considered; the factors were surveyed on potential consumers; a study was carried out to analyze the relationship of these factors; a model of these factors were set up and proven.

Polymorphic Path Transferring for Secure Flow Delivery

  • Zhang, Rongbo;Li, Xin;Zhan, Yan
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제15권8호
    • /
    • pp.2805-2826
    • /
    • 2021
  • In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

Phishing Attack Detection Using Deep Learning

  • Alzahrani, Sabah M.
    • International Journal of Computer Science & Network Security
    • /
    • 제21권12호
    • /
    • pp.213-218
    • /
    • 2021
  • This paper proposes a technique for detecting a significant threat that attempts to get sensitive and confidential information such as usernames, passwords, credit card information, and more to target an individual or organization. By definition, a phishing attack happens when malicious people pose as trusted entities to fraudulently obtain user data. Phishing is classified as a type of social engineering attack. For a phishing attack to happen, a victim must be convinced to open an email or a direct message [1]. The email or direct message will contain a link that the victim will be required to click on. The aim of the attack is usually to install malicious software or to freeze a system. In other instances, the attackers will threaten to reveal sensitive information obtained from the victim. Phishing attacks can have devastating effects on the victim. Sensitive and confidential information can find its way into the hands of malicious people. Another devastating effect of phishing attacks is identity theft [1]. Attackers may impersonate the victim to make unauthorized purchases. Victims also complain of loss of funds when attackers access their credit card information. The proposed method has two major subsystems: (1) Data collection: different websites have been collected as a big data corresponding to normal and phishing dataset, and (2) distributed detection system: different artificial algorithms are used: a neural network algorithm and machine learning. The Amazon cloud was used for running the cluster with different cores of machines. The experiment results of the proposed system achieved very good accuracy and detection rate as well.

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
    • /
    • 제22권3호
    • /
    • pp.155-162
    • /
    • 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.