Towards privacy preserving threat intelligence

Dara, Sashank; Zargar, Saman Taghavi; Muralidhara, V. N.

doi:10.1016/j.jisa.2017.11.006

Cited by 6 publications

(6 citation statements)

References 2 publications

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“…This means that there is a lack of contribution to defending against mobile APTs. This study identified 60 primary studies of which 40 primary studies focused on APT detection [1,3,[5][6][7]28,76,86,97,98,100,106,111,115,[124][125][126][127][128][129]134,[136][137][138][139]142,172,173,176], six primary studies focused on APT protection [4,91,92,118,121,125], four primary studies focused on APT mitigation [142][143][144][145], three primary studies focused on APT identification [98,107,146], and [116] focused on the detection and response to APTs as shown in Table 5.…”

Section: Rq2: What Are the Proposed Defensive Mechanisms Available To...mentioning

confidence: 99%

“…In addition, APTs can be tackled using game theory. Game theory techniques have been utilized to detect or mitigate APTs on IoT [1,82], computers [98,145], and in general [135,151,152]. In addition, game theory has been used with risk management approaches to identify the APT in fog computing [111] and IoT [107].…”

Section: Rq2: What Are the Proposed Defensive Mechanisms Available To...mentioning

confidence: 99%

“…Following the existing APT defense solutions defined above in Section 4.2, the authors present the following research gaps: 5.1.1. Solution Techniques Are Ineffective and Not Fully Bullet-Proof Most of the APT defense solutions [1,[3][4][5][6][7]28,76,[86][87][88]94,97,98,[100][101][102][103]106,108,111,115,117,121,124,127,[133][134][135][136][140][141][142][143]145,147,172,173,176,178] being investigated have loopholes and limitations. Based on the literature, the APT defense solutions have focused on identifying, protecting, detecting, and responding to APT attacks.…”

Section: Research Gapsmentioning

confidence: 99%

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Exploration of Mobile Device Behavior for Mitigating Advanced Persistent Threats (APT): A Systematic Literature Review and Conceptual Framework

Jabar

Singh

2022

Sensors

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During the last several years, the Internet of Things (IoT), fog computing, computer security, and cyber-attacks have all grown rapidly on a large scale. Examples of IoT include mobile devices such as tablets and smartphones. Attacks can take place that impact the confidentiality, integrity, and availability (CIA) of the information. One attack that occurs is Advanced Persistent Threat (APT). Attackers can manipulate a device’s behavior, applications, and services. Such manipulations lead to signification of a deviation from a known behavioral baseline for smartphones. In this study, the authors present a Systematic Literature Review (SLR) to provide a survey of the existing literature on APT defense mechanisms, find research gaps, and recommend future directions. The scope of this SLR covers a detailed analysis of most cybersecurity defense mechanisms and cutting-edge solutions. In this research, 112 papers published from 2011 until 2022 were analyzed. This review has explored different approaches used in cybersecurity and their effectiveness in defending against APT attacks. In a conclusion, we recommended a Situational Awareness (SA) model known as Observe–Orient–Decide–Act (OODA) to provide a comprehensive solution to monitor the device’s behavior for APT mitigation.

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Section: Rq2: What Are the Proposed Defensive Mechanisms Available To...mentioning

confidence: 99%

Section: Rq2: What Are the Proposed Defensive Mechanisms Available To...mentioning

confidence: 99%

Section: Research Gapsmentioning

confidence: 99%

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Exploration of Mobile Device Behavior for Mitigating Advanced Persistent Threats (APT): A Systematic Literature Review and Conceptual Framework

Jabar

Singh

2022

Sensors

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“…It embraces all evidence‐based knowledge about existing or emerging threats, which can be used to support cyberdefense decisions . TI has recently attracted great attention, including vendors of security solutions who offer diverse TI solutions …”

Section: Collaborative Security Information Sharing Situation Awarementioning

confidence: 99%

“…Technical TI is the lowest‐level data, gathered and processed by technical tools . An important factor that should be considered in the TI domain is users' privacy as a considerable amount of data delivered to TI services originally contain identifiers of their source …”

Section: Collaborative Security Information Sharing Situation Awarementioning

confidence: 99%

Threat intelligence platform for the energy sector

Wróbel

2019

Softw Pract Exp

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In recent years, critical infrastructures and power systems in particular have been subjected to sophisticated cyberthreats, including targeted attacks and advanced persistent threats. A promising response to this challenging situation is building up enhanced threat intelligence (TI) that interlinks information sharing and fine-grained situation awareness. In this paper, a framework that integrates all levels of TI, ie, strategic, tactical, operational, and technical, is presented. The platform implements the centralized model of information exchange with peer-to-peer interactions between partners as an option. Several supportive solutions were introduced, including anonymity mechanisms or data processing and correlation algorithms. A data model that enables communication of cyberincident information, both in natural language and machine-readable formats, was defined. Similarly, security requirements for critical components were devised. A pilot implementation of the platform was developed and deployed in the operational environment, which enabled practical evaluation of the design. Also, the security of the anonymity architecture was analyzed.

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