Success Factors for Cyber Security Operation Center (SOC) Establishment

Majid, Maziana Abd; Ariffi, K

doi:10.4108/eai.18-7-2019.2287841

Cited by 13 publications

(15 citation statements)

References 13 publications

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“…Research often describes operations within a SOC following the People, Processes, and Technologies (PPT) framework [3], [30]- [33]. This framework is used for various information technology topics like knowledge management [70] or customer relationship management [34].…”

Section: A Delimitation and Definitionmentioning

confidence: 99%

“…• Network Operations Center: A Network Operations Center (NOC) oversees identifying, investigating, prioritizing, escalating, and resolving problems [17], [38]. However, in NOCs, the addressed problems are different as the NOC focuses on incidents impacting the performance and availability of an organization's net- General Aspects References Definition & Delimitation [2], [3], [5], [17], [22]- [39] Architecture [3], [4], [6], [30], [34], [39]- [61] Operating Models [2], [3], [7], [25], [33], [46], [62]- [68] work [36], [72]. As incidents can occur on all systems not just networks, it is beneficial for organizations when the NOC and SOC teams work together.…”

Section: A Delimitation and Definitionmentioning

confidence: 99%

See 1 more Smart Citation

Security Operations Center: A Systematic Study and Open Challenges

et al. 2020

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Section: A Delimitation and Definitionmentioning

confidence: 99%

Section: A Delimitation and Definitionmentioning

confidence: 99%

Security Operations Center: A Systematic Study and Open Challenges

et al. 2020

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“…e IoE can be applied in various fields such as smart cities, smart homes, intelligent transportations, automated agriculture, and convenient healthcare (Figure 1). e IoE often suffers from its computation limitations in processing capabilities and fixed storage, leading to the lack of device safety, privacy, and performance [1][2][3][4][5][6]. Considering the ubiquitous application of IoE in our society, it is imperative to improve their security and performance Fig 1.…”

Section: Introductionmentioning

confidence: 99%

“…Many applications can lose our private information on banking, health, and location services due to these security constraints. A security measure is required to secure communication in which the interception of messages by malicious users cannot harm our privacy [3,8].…”

Section: Introductionmentioning

confidence: 99%

Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex Internet of Things Applications

Hasan

Shafiq²,

Islam

et al. 2021

Complexity

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As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things (IoT) has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables and control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning-based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications.

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“…Based on previous research, SOC has been developed and implemented by organizations without adhering to specific guidelines or international standards. Besides, past research has also highlighted that no international guidelines and standards have been used by organizations to develop and implement the SOC [13]. This is reflected in the inequality and diversity of SOC infrastructure and its implementation [14].…”

Section: Introductionmentioning

confidence: 99%

Model for successful development and implementation of Cyber Security Operations Centre (SOC)

Majid

Ariffin

2021

PLoS ONE

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Cyberattacks have changed dramatically and have become highly advanced. This latest phenomenon has a massive negative impact on organizations, such as financial losses and shutting-down of operations. Therefore, developing and implementing the Cyber Security Operations Centre (SOC) is imperative and timely. Based on previous research, there are no international guidelines and standards used by organizations that can contribute to the successful implementation and development of SOC. In this regard, this study focuses on highlighting the significant factors that will impact and contribute to the success of SOC. Simultaneously, it will further design a model for the successful development and implementation of SOC for the organization. The study was conducted quantitatively and involved 63 respondents from 25 ministries and agencies in Malaysia. The results of this study will enable the retrieval of ten success factors for SOC, and it specifically focuses on humans, processes, and technology. The descriptive analysis shows that the top management support factor is the most influential factor in the success of the development and implementation of SOC. The study also contributes to the empirical finding that technology and process factors are more significant in the success of SOCs. Based on the regression test, the technology factor has major impact on determining the success of SOC, followed by the process and human factors. Relevant organizations or agencies can use the proposed model to develop and implement SOCs, formulate policies and guidelines, strengthen human models, and enhance cyber security.

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Success Factors for Cyber Security Operation Center (SOC) Establishment

Cited by 13 publications

References 13 publications

Security Operations Center: A Systematic Study and Open Challenges

Security Operations Center: A Systematic Study and Open Challenges

Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex Internet of Things Applications

Model for successful development and implementation of Cyber Security Operations Centre (SOC)

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