• 제목/요약/키워드: privacy attacks

검색결과 229건 처리시간 0.13초

Robustness Analysis of a Novel Model-Based Recommendation Algorithms in Privacy Environment

  • Ihsan Gunes
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권5호
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    • pp.1341-1368
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    • 2024
  • The concept of privacy-preserving collaborative filtering (PPCF) has been gaining significant attention. Due to the fact that model-based recommendation methods with privacy are more efficient online, privacy-preserving memory-based scheme should be avoided in favor of model-based recommendation methods with privacy. Several studies in the current literature have examined ant colony clustering algorithms that are based on non-privacy collaborative filtering schemes. Nevertheless, the literature does not contain any studies that consider privacy in the context of ant colony clustering-based CF schema. This study employed the ant colony clustering model-based PPCF scheme. Attacks like shilling or profile injection could potentially be successful against privacy-preserving model-based collaborative filtering techniques. Afterwards, the scheme's robustness was assessed by conducting a shilling attack using six different attack models. We utilize masked data-based profile injection attacks against a privacy-preserving ant colony clustering-based prediction algorithm. Subsequently, we conduct extensive experiments utilizing authentic data to assess its robustness against profile injection attacks. In addition, we evaluate the resilience of the ant colony clustering model-based PPCF against shilling attacks by comparing it to established PPCF memory and model-based prediction techniques. The empirical findings indicate that push attack models exerted a substantial influence on the predictions, whereas nuke attack models demonstrated limited efficacy.

A Beacon-Based Trust Management System for Enhancing User Centric Location Privacy in VANETs

  • Chen, Yi-Ming;Wei, Yu-Chih
    • Journal of Communications and Networks
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    • 제15권2호
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    • pp.153-163
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    • 2013
  • In recent years, more and more researches have been focusing on trust management of vehicle ad-hoc networks (VANETs) for improving the safety of vehicles. However, in these researches, little attention has been paid to the location privacy due to the natural conflict between trust and anonymity, which is the basic protection of privacy. Although traffic safety remains the most crucial issue in VANETs, location privacy can be just as important for drivers, and neither can be ignored. In this paper, we propose a beacon-based trust management system, called BTM, that aims to thwart internal attackers from sending false messages in privacy-enhanced VANETs. To evaluate the reliability and performance of the proposed system, we conducted a set of simulations under alteration attacks, bogus message attacks, and message suppression attacks. The simulation results show that the proposed system is highly resilient to adversarial attacks, whether it is under a fixed silent period or random silent period location privacy-enhancement scheme.

Shilling Attacks Against Memory-Based Privacy-Preserving Recommendation Algorithms

  • Gunes, Ihsan;Bilge, Alper;Polat, Huseyin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권5호
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    • pp.1272-1290
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    • 2013
  • Privacy-preserving collaborative filtering schemes are becoming increasingly popular because they handle the information overload problem without jeopardizing privacy. However, they may be susceptible to shilling or profile injection attacks, similar to traditional recommender systems without privacy measures. Although researchers have proposed various privacy-preserving recommendation frameworks, it has not been shown that such schemes are resistant to profile injection attacks. In this study, we investigate two memory-based privacy-preserving collaborative filtering algorithms and analyze their robustness against several shilling attack strategies. We first design and apply formerly proposed shilling attack techniques to privately collected databases. We analyze their effectiveness in manipulating predicted recommendations by experimenting on real data-based benchmark data sets. We show that it is still possible to manipulate the predictions significantly on databases consisting of masked preferences even though a few of the attack strategies are not effective in a privacy-preserving environment.

Social Media Security and Attacks

  • Almalki, Sarah;Alghamdi, Reham;Sami, Gofran;Alhakami, Wajdi
    • International Journal of Computer Science & Network Security
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    • 제21권1호
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    • pp.174-183
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    • 2021
  • The advent of social media has revolutionized the speed of communication between millions of people around the world in various cultures and disciplines. Social media is the best platform for exchanging opinions and ideas, interacting with other users of similar interests and sharing different types of media and files. With the phenomenal increase in the use of social media platforms, the need to pay attention to protection and security from attacks and misuse has also increased. The present study conducts a comprehensive survey of the latest and most important research studies published from 2018-20 on security and privacy on social media and types of threats and attacks that affect the users. We have also reviewed the recent challenges that affect security features in social media. Furthermore, this research pursuit also presents effective and feasible solutions that address these threats and attacks and cites recommendations to increase security and privacy for the users of social media.

프라이버시 보호 데이터 배포를 위한 모델 조사 (Models for Privacy-preserving Data Publishing : A Survey)

  • 김종선;정기정;이혁기;김수형;김종욱;정연돈
    • 정보과학회 논문지
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    • 제44권2호
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    • pp.195-207
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    • 2017
  • 최근 다양한 분야에서 데이터들이 활발하게 활용되고 있다. 이에 따라 데이터의 공유나 배포를 요구하는 목소리가 높아지고 있다. 그러나 공유된 데이터에 개인과 관련된 민감한 정보가 있을 경우, 개인의 민감한 정보가 드러나는 프라이버시 유출이 발생할 수 있다. 개인 정보가 포함된 데이터를 배포하기 위해 개인의 프라이버시를 보호하면서 데이터를 최소한으로 변형하는 프라이버시 보호 데이터 배포(privacy-preserving data publishing, PPDP)가 연구되어 왔다. 프라이버시 보호 데이터 배포 연구는 다양한 공격자 모델을 가정하고 이러한 공격자의 프라이버시 유출 공격으로부터 프라이버시를 보호하기 위한 원칙인 프라이버시 모델에 따라 발전해왔다. 본 논문에서는 먼저 프라이버시 유출 공격에 대해 알아본다. 그리고 프라이버시 모델들을 프라이버시 유출 공격에 따라 분류하고 각 프라이버시 모델들 간의 차이점과 요구 조건에 대해 알아본다.

피싱과 파밍 공격에 대응하기 위한 인증 프로토콜 설계 (Design Of A Secure Authentication Protocol Against Phishing And Pharming Attacks)

  • 김익수;최종명
    • 디지털산업정보학회논문지
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    • 제5권1호
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    • pp.63-70
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    • 2009
  • As individuals spend more time doing social and economic life on the web, the importance of protecting privacy against Phishing and Pharming attacks also increases. Until now, there have been researches on the methods of protection against Phishing and Pharming. However, these researches don't provide efficient methods for protecting privacy and don't consider Pharming attacks. In this paper, we propose an authentication protocol that protects user information from Phishing and Pharming attacks. In this protocol, the messages passed between clients and servers are secure because they authenticate each other using a hash function of password and location information which are certificated to clients and servers only. These messages are used only once, so that the protocol is secure from replay attacks and man-in-the-middle attacks. Furthermore, it is also secure from Pharming attacks.

데이터 익명화 결정 기법 (Data Anonymity Decision)

  • 정민경;홍동권
    • 한국지능시스템학회논문지
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    • 제20권2호
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    • pp.173-180
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    • 2010
  • 공개되는 데이터에서 각 개인의 민감한 정보를 보호하기 위한 방법으로 데이터 익명화에 관한 연구가 활발히 이루어지고 있다. 대부분의 연구들은 익명화 요구 사항에 위배되지 않으면서, 효율적인 시간 내 레코드들을 일반화하는 기법을 중심으로 연구를 진행하고 있다. 익명화 작업이 많은 시간이 요구되는 문제임을 고려한다면, 민감한 정보에 대한 프라이버시 침해의 우려가 있는지, 익명화가 요구되는지를 미리 검사하는 것은 개인 정보 보호차원뿐만 아니라 데이터의 활용성 및 시간적 효율성 측면에서도 매우 중요하다. 또한, 그러한 침해의 우려가 있다면 어떤 유형의 공격에 취약한지를 미리 판단함으로써 그에 적절한 익명화 방식을 결정하는 것도 중요하다. 본 논문에서는 민감한 속성에 대한 공격 유형을 크게 2가지로 분류한다. 그리고 데이터가 이들 공격으로부터 안전한가의 여부를 검사할 수 있는 기법을 제시하고, 불안정하다면 어떠한 공격에 취약하고 대략 어떤 방식의 일반화가 요구되는가를 제시한다. 본 연구에서는 익명화되기 전의 테이블뿐만 아니라, 익명화된 테이블, 그리고 익명화가 되었지만 삽입, 삭제로 인해 변경된 테이블도 공격성 검사 대상이 된다. 뿐만 아니라 익명화된 테이블도 민감한 정보를 제대로 보호하고 있는지 혹은 삽입 삭제로 인해 재익명화 작업이 필요한지의 여부도 본 연구의 결과로 결정할 수 있다.

Design and Analysis of Fabrication Threat Management in Peer-to-Peer Collaborative Location Privacy

  • Jagdale, Balaso;Sugave, Shounak;Kolhe, Kishor
    • International Journal of Computer Science & Network Security
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    • 제21권12spc호
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    • pp.399-408
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    • 2021
  • Information security reports four types of basic attacks on information. One of the attacks is named as fabrication. Even though mobile devices and applications are showing its maturity in terms of performance, security and ubiquity, location-based applications still faces challenges of quality of service, privacy, integrity, authentication among mobile devices and hence mobile users associated with the devices. There is always a continued fear as how location information of users or IoT appliances is used by third party LB Service providers. Even adversary or malicious attackers get hold of location information in transit or fraudulently hold this information. In this paper, location information fabrication scenarios are presented after knowing basic model of information attacks. Peer-to-Peer broadcast model of location privacy is proposed. This document contains introduction to fabrication, solutions to such threats, management of fabrication mitigation in collaborative or peer to peer location privacy and its cost analysis. There are various infrastructure components in Location Based Services such as Governance Server, Point of interest POI repository, POI service, End users, Intruders etc. Various algorithms are presented and analyzed for fabrication management, integrity, and authentication. Moreover, anti-fabrication mechanism is devised in the presence of trust. Over cost analysis is done for anti-fabrication management due to nature of various cryptographic combinations.

Anonymizing Graphs Against Weight-based Attacks with Community Preservation

  • Li, Yidong;Shen, Hong
    • Journal of Computing Science and Engineering
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    • 제5권3호
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    • pp.197-209
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    • 2011
  • The increasing popularity of graph data, such as social and online communities, has initiated a prolific research area in knowledge discovery and data mining. As more real-world graphs are released publicly, there is growing concern about privacy breaching for the entities involved. An adversary may reveal identities of individuals in a published graph, with the topological structure and/or basic graph properties as background knowledge. Many previous studies addressing such attacks as identity disclosure, however, concentrate on preserving privacy in simple graph data only. In this paper, we consider the identity disclosure problem in weighted graphs. The motivation is that, a weighted graph can introduce much more unique information than its simple version, which makes the disclosure easier. We first formalize a general anonymization model to deal with weight-based attacks. Then two concrete attacks are discussed based on weight properties of a graph, including the sum and the set of adjacent weights for each vertex. We also propose a complete solution for the weight anonymization problem to prevent a graph from both attacks. In addition, we also investigate the impact of the proposed methods on community detection, a very popular application in the graph mining field. Our approaches are efficient and practical, and have been validated by extensive experiments on both synthetic and real-world datasets.

Detection Mechanism on Vehicular Adhoc Networks (VANETs) A Comprehensive Survey

  • Shobana, Gopalakrishnan;Arockia, Xavier Annie R.
    • International Journal of Computer Science & Network Security
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    • 제21권6호
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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.