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In-depth Correlation Power Analysis Attacks on a Hardware Implementation of CRYSTALS-Dilithium

During the standardisation process of post-quantum cryptography, NIST encourages research on side-channel analysis for candidate schemes. As the recommended lattice signature scheme, CRYSTALS-Dilithium, when i...

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Atomic cross-chain swap based on private key exchange

Atomic Cross-Chain Swap (ACCS) is one important topic in cryptocurrency, where users can securely and trustlessly exchange assets between two different blockchains. However, most known ACCS schemes assume spec...

HSS: enhancing IoT malicious traffic classification leveraging hybrid sampling strategy

Using deep learning models to deal with the classification tasks in network traffic offers a new approach to address the imbalanced Internet of Things malicious traffic classification problems. However, the em...

Key derivable signature and its application in blockchain stealth address

Stealth address protocol (SAP) is widely used in blockchain to achieve anonymity. In this paper, we formalize a key derivable signature scheme (KDS) to capture the functionality and security requirements of SA...

Polar code-based secure transmission with higher message rate combining channel entropy and computational entropy

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respective...

Dissecting zero trust: research landscape and its implementation in IoT

As a progressive security strategy, the zero trust model has attracted notable attention and importance within the realm of network security, especially in the context of the Internet of Things (IoT). This pap...

Study of smart grid cyber-security, examining architectures, communication networks, cyber-attacks, countermeasure techniques, and challenges

Smart Grid (SG) technology utilizes advanced network communication and monitoring technologies to manage and regulate electricity generation and transport. However, this increased reliance on technology and co...

A multi-agent adaptive deep learning framework for online intrusion detection

The network security analyzers use intrusion detection systems (IDSes) to distinguish malicious traffic from benign ones. The deep learning-based (DL-based) IDSes are proposed to auto-extract high-level featur...

Iterative and mixed-spaces image gradient inversion attack in federated learning

As a distributed learning paradigm, federated learning is supposed to protect data privacy without exchanging users’ local data. Even so, the gradient inversion attack , in which the adversary can reconstruct the ...

Winternitz stack protocols for embedded systems and IoT

This paper proposes and evaluates a new bipartite post-quantum digital signature protocol based on Winternitz chains and an  oracle. Mutually mistrustful Alice and Bob are able to agree and sign a series of do...

Joint contrastive learning and belief rule base for named entity recognition in cybersecurity

Named Entity Recognition (NER) in cybersecurity is crucial for mining information during cybersecurity incidents. Current methods rely on pre-trained models for rich semantic text embeddings, but the challenge...

DTA: distribution transform-based attack for query-limited scenario

In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually res...

A survey on lattice-based digital signature

Lattice-based digital signature has become one of the widely recognized post-quantum algorithms because of its simple algebraic operation, rich mathematical foundation and worst-case security, and also an impo...

Shorter ZK-SNARKs from square span programs over ideal lattices

Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) are cryptographic protocols that offer efficient and privacy-preserving means of verifying NP language relations and have drawn consid...

Revocable and verifiable weighted attribute-based encryption with collaborative access for electronic health record in cloud

The encryption of user data is crucial when employing electronic health record services to guarantee the security of the data stored on cloud servers. Attribute-based encryption (ABE) scheme is considered a po...

Maxwell’s Demon in MLP-Mixer: towards transferable adversarial attacks

Models based on MLP-Mixer architecture are becoming popular, but they still suffer from adversarial examples. Although it has been shown that MLP-Mixer is more robust to adversarial attacks compared to convolu...

Practical solutions in fully homomorphic encryption: a survey analyzing existing acceleration methods

Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread application in various fields, like outsourcing computation and secure...

A circuit area optimization of MK-3 S-box

In MILCOM 2015, Kelly et al. proposed the authentication encryption algorithm MK-3, which applied the 16-bit S-box. This paper aims to implement the 16-bit S-box with less circuit area. First, we classified th...

Intrusion detection system for controller area network

The rapid expansion of intra-vehicle networks has increased the number of threats to such networks. Most modern vehicles implement various physical and data-link layer technologies. Vehicles are becoming incre...

CT-GCN+: a high-performance cryptocurrency transaction graph convolutional model for phishing node classification

Due to the anonymous and contract transfer nature of blockchain cryptocurrencies, they are susceptible to fraudulent incidents such as phishing. This poses a threat to the property security of users and hinder...

Enhanced detection of obfuscated malware in memory dumps: a machine learning approach for advanced cybersecurity

In the realm of cybersecurity, the detection and analysis of obfuscated malware remain a critical challenge, especially in the context of memory dumps. This research paper presents a novel machine learning-bas...

BRITD: behavior rhythm insider threat detection with time awareness and user adaptation

Researchers usually detect insider threats by analyzing user behavior. The time information of user behavior is an important concern in internal threat detection.

F3l: an automated and secure function-level low-overhead labeled encrypted traffic dataset construction method for IM in Android

Fine-grained function-level encrypted traffic classification is an essential approach to maintaining network security. Machine learning and deep learning have become mainstream methods to analyze traffic, and ...

WAS: improved white-box cryptographic algorithm over AS iteration

The attacker in white-box model has full access to software implementation of a cryptographic algorithm and full control over its execution environment. In order to solve the issues of high storage cost and in...

Full-round impossible differential attack on shadow block cipher

Lightweight block ciphers are the essential encryption algorithm for devices with limited resources. Its goal is to ensure the security of data transmission through resource-constrained devices. Impossible dif...

Minimizing CNOT-count in quantum circuit of the extended Shor’s algorithm for ECDLP

The elliptic curve discrete logarithm problem (ECDLP) is a popular choice for cryptosystems due to its high level of security. However, with the advent of the extended Shor’s algorithm, there is concern that E...

Towards the transferable audio adversarial attack via ensemble methods

In recent years, deep learning (DL) models have achieved significant progress in many domains, such as autonomous driving, facial recognition, and speech recognition. However, the vulnerability of deep learnin...

LayerCFL: an efficient federated learning with layer-wised clustering

Federated Learning (FL) suffers from the Non-IID problem in practice, which poses a challenge for efficient and accurate model training. To address this challenge, prior research has introduced clustered FL (C...

A novel botnet attack detection for IoT networks based on communication graphs

Intrusion detection systems have been proposed for the detection of botnet attacks. Various types of centralized or distributed cloud-based machine learning and deep learning models have been suggested. Howeve...

Machine learning based fileless malware traffic classification using image visualization

In today’s interconnected world, network traffic is replete with adversarial attacks. As technology evolves, these attacks are also becoming increasingly sophisticated, making them even harder to detect. Fortu...

Research on privacy information retrieval model based on hybrid homomorphic encryption

The computational complexity of privacy information retrieval protocols is often linearly related to database size. When the database size is large, the efficiency of privacy information retrieval protocols is...

Performance evaluation of Cuckoo filters as an enhancement tool for password cracking

Cyberthreats continue their expansion, becoming more and more complex and varied. However, credentials and passwords are still a critical point in security. Password cracking can be a powerful tool to fight ag...

Tor network anonymity evaluation based on node anonymity

In order to address the shortcomings of traditional anonymity network anonymity evaluation methods, which only analyze from the perspective of the overall network and ignore the attributes of individual nodes,...

Verifiable delay functions and delay encryptions from hyperelliptic curves

Verifiable delay functions (VDFs) and delay encryptions (DEs) are two important primitives in decentralized systems, while existing constructions are mainly based on time-lock puzzles. A disparate framework ha...

MSLFuzzer: black-box fuzzing of SOHO router devices via message segment list inference

The popularity of small office and home office routers has brought convenience, but it also caused many security issues due to vulnerabilities. Black-box fuzzing through network protocols to discover vulnerabi...

A deep learning aided differential distinguisher improvement framework with more lightweight and universality

In CRYPTO 2019, Gohr opens up a new direction for cryptanalysis. He successfully applied deep learning to differential cryptanalysis against the NSA block cipher SPECK32/64, achieving higher accuracy than trad...

Attack based on data: a novel perspective to attack sensitive points directly

Adversarial attack for time-series classification model is widely explored and many attack methods are proposed. But there is not a method of attack based on the data itself. In this paper, we innovatively pro...

Improved lower bound for the complexity of unique shortest vector problem

Unique shortest vector problem (uSVP) plays an important role in lattice based cryptography. Many cryptographic schemes based their security on it. For the cofidence of those applications, it is essential to c...

Evolution of blockchain consensus algorithms: a review on the latest milestones of blockchain consensus algorithms

Blockchain technology has gained widespread adoption in recent years due to its ability to enable secure and transparent record-keeping and data transfer. A critical aspect of blockchain technology is the use ...

Graph neural network based approach to automatically assigning common weakness enumeration identifiers for vulnerabilities

Vulnerability reports are essential for improving software security since they record key information on vulnerabilities. In a report, CWE denotes the weakness of the vulnerability and thus helps quickly under...

EPASAD: ellipsoid decision boundary based Process-Aware Stealthy Attack Detector

Due to the importance of Critical Infrastructure (CI) in a nation’s economy, they have been lucrative targets for cyber attackers. These critical infrastructures are usually Cyber-Physical Systems such as powe...

Generic attacks on small-state stream cipher constructions in the multi-user setting

Small-state stream ciphers (SSCs), which violate the principle that the state size should exceed the key size by a factor of two, still demonstrate robust security properties while maintaining a lightweight de...

Evicting and filling attack for linking multiple network addresses of Bitcoin nodes

Bitcoin is a decentralized P2P cryptocurrency. It supports users to use pseudonyms instead of network addresses to send and receive transactions at the data layer, hiding users’ real network identities. Tradit...

Aparecium: understanding and detecting scam behaviors on Ethereum via biased random walk

Ethereum’s high attention, rich business, certain anonymity, and untraceability have attracted a group of attackers. Cybercrime on it has become increasingly rampant, among which scam behavior is convenient, c...

An efficient permutation approach for SbPN-based symmetric block ciphers

It is challenging to devise lightweight cryptographic primitives efficient in both hardware and software that can provide an optimum level of security to diverse Internet of Things applications running on low-...

IHVFL: a privacy-enhanced intention-hiding vertical federated learning framework for medical data

Vertical Federated Learning (VFL) has many applications in the field of smart healthcare with excellent performance. However, current VFL systems usually primarily focus on the privacy protection during model ...

Intrusion detection systems for wireless sensor networks using computational intelligence techniques

Network Intrusion Detection Systems (NIDS) are utilized to find hostile network connections. This can be accomplished by looking at traffic network activity, but it takes a lot of work. The NIDS heavily utiliz...

Detecting fake reviewers in heterogeneous networks of buyers and sellers: a collaborative training-based spammer group algorithm

It is not uncommon for malicious sellers to collude with fake reviewers (also called spammers) to write fake reviews for multiple products to either demote competitors or promote their products’ reputations, f...

Continuously non-malleable codes from block ciphers in split-state model

Non-malleable code is an encoding scheme that is useful in situations where traditional error correction or detection is impossible to achieve. It ensures with high probability that decoded message is either c...

Use of subword tokenization for domain generation algorithm classification

Domain name generation algorithm (DGA) classification is an essential but challenging problem. Both feature-extracting machine learning (ML) methods and deep learning (DL) models such as convolutional neural n...

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Volume 9, Issue 1, 2023

Research papers, classifying social media bots as malicious or benign using semi-supervised machine learning.

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The nature of losses from cyber-related events: risk categories and business sectors

Contribution threat perception, school climate and prejudice as mediator to student’s cyber aggression, post-quantum cryptographic assemblages and the governance of the quantum threat, juror interpretations of metadata and content information: implications for the going dark debate, adapting cybersecurity practice to reduce wildlife cybercrime, tell me more, tell me more: repeated personal data requests increase disclosure, the power of beliefs in us cyber strategy: the evolving role of deterrence, norms, and escalation, maximizing the benefits from sharing cyber threat intelligence by government agencies and departments, development of a new ‘human cyber-resilience scale’, the security mindset: characteristics, development, and consequences, defining the reporting threshold for a cybersecurity incident under the nis directive and the nis 2 directive, a systematization of voter registration security, realizing credible remote agricultural auditing with trusted video technology, testing human ability to detect ‘deepfake’ images of human faces, a close look at a systematic method for analyzing sets of security advice, digital fingerprinting for identifying malicious collusive groups on twitter, the concept of modern political confrontation in cyber space, predictive taxonomy analytics (lasso): predicting outcome types of cyber breach, executive decision-makers: a scenario-based approach to assessing organizational cyber-risk perception, from russia with fear: fear appeals and the patterns of cyber-enabled influence operations, cybersecurity in uk universities: mapping (or managing) threat intelligence sharing within the higher education sector, learning about simulated adversaries from human defenders using interactive cyber-defense games, efficient collective action for tackling time-critical cybersecurity threats, email alerts, affiliations.

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The 2020 Cyber Security Report

Crypto miners, targeted ransomware and cloud attacks dominate the threat landscape.

Each year, Check Point Research (CPR) reviews previous year cyber incidents to gather key insights about the global cyber threat landscape. In this 2020 Cyber Security Annual Report, we offer a review of 2019’s major cyber incidents, suggest predictions for 2020, and recommend best practices to help keep your organization safe from cyber attacks. With the popularity of cloud computing and network-connected smartphones, it’s no secret that there are more ways to invade an organization. A once hardened network perimeter is now blurred and porous to cyber attacks, and the bad actors are well aware. If there’s one clear takeaway from 2019, it’s that no organization, big or small, is immune from a devastating cyber attack. Cyber exploits are more sophisticated, illusive, and targeted than ever before. With cybercrime rates estimated to have generated US$1.5 trillion in 2018, navigating today’s complex cyber threat landscape requires comprehensive cyber security.

In 2019, becoming an under protected, “sweet spot” for hacking was dangerous for entire industries. A large number of state and local public sector agencies were ravaged by ransomware attacks . In some cases, entire local governments were forced to declare a state of emergency due to the massive leaks of sensitive data and loss of services. In this 2020 Cyber Security Annual Report, we provide you with a timeline of 2019’s significant cyber events, including their relevant facts and insights. By analyzing our telemetric, product and vulnerability research, and our own ThreatCloud threat intelligence, we offer a detailed analysis of the cyber trends you need to consider. We then offer our 2020 vision which includes cyber security predictions. Finally, we offer recommendations on cyber protection strategies, using security “hygiene” best practices, advanced technology, and the focus on prevention, not detection or remediation. In order to adopt a winning strategy against zero-day, unknown cyber attacks, prevention should be considered.

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IoT cybersecurity in 5G and beyond: a systematic literature review

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• Published: 28 May 2024

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• Sandeep Pirbhulal 1   na1 ,
• Sabarathinam Chockalingam 2   na1 ,
• Ankur Shukla 2   na1 &
• Habtamu Abie 1  

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The 5th generation (5G) and beyond use Internet of Things (IoT) to offer the feature of remote monitoring for different applications such as transportation, healthcare, and energy. There are several advantages of 5G and beyond for IoT applications like high speed and low latency. However, they are prone to cybersecurity threats due to networks softwarization and virtualization, thus raising additional security challenges and complexities. In this paper, we conducted a systematic literature review (SLR) of cybersecurity for 5G and beyond-enabled IoT. By developing a taxonomy to classify and characterize existing research, we identified and analyzed strategies, key patterns, mechanisms, performance evaluation, validation parameters and challenges of cybersecurity and resilience for 5G and beyond-enabled IoT in existing studies. We used “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)” recommendations for this SLR. Through our search in scientific databases, 4449 records published between 2017 and 2023 were initially identified, which were then reduced to 558 records after title and abstract screening to be considered for the eligibility check process. After screening the full-text, 79 articles were finalized for thorough analysis. The findings of this study suggest that 35% of the included studies focus on authentication and access control as security aspects, 59% studies are based on combination of both network layer and application layer as main operation layer, and 34% of the included studies use real-time implementation for validation purpose while the remaining studies utilize simulation or theoretical analysis. Our SLR also highlights open research challenges of 5G and beyond-enabled IoT cybersecurity and suggests a tentative solution for each challenge, which can be a focus of future research. Finally, key limitations of our SLR and threats to validity are addressed.

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Acknowledgements

This research is funded from the Research Council of Norway through, the SFI Norwegian Centre for Cybersecurity in Critical Sectors (NORCICS) , with the Project Number #310105 in addition to INTPART projects, Reinforcing Competence in Cybersecurity of Critical Infrastructures: A Norway-US Partnership (RECYCIN) , with the Project Number #309911 and International Alliance for Strengthening Cybersecurity and Privacy in Healthcare (CybAlliance) , with the Project Number #337316.

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Sandeep Pirbhulal, Sabarathinam Chockalingam and Ankur Shukla have contributed equally to this work.

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Sandeep Pirbhulal & Habtamu Abie

Department of Risk and Security, Institute for Energy Technology, 1777, Halden, Norway

Sabarathinam Chockalingam & Ankur Shukla

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SP, SC, and AS did initial conceptualisation and data records analysis; SP, and HA prepared the study design and literature review; SP, SC, and AS were involved in writing-original draft preparation; and HA did writing-review and editing. All authors have revised the manuscript together, read and agreed to the published version of the manuscript.

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Pirbhulal, S., Chockalingam, S., Shukla, A. et al. IoT cybersecurity in 5G and beyond: a systematic literature review. Int. J. Inf. Secur. (2024). https://doi.org/10.1007/s10207-024-00865-5

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Accepted : 04 May 2024

Published : 28 May 2024

DOI : https://doi.org/10.1007/s10207-024-00865-5

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