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A Survey on Ransomware Malware and Ransomware Detection Techniques

Abstract: is a kind of malignant programming (malware) that takes steps to distribute or hinders admittance to information or a PC framework, for the most part by scrambling it, until the casualty pays a payoff expense to the assailant. As a rule, the payoff request accompanies a cutoff time. Assuming that the casualty doesn't pay on schedule, the information is gone perpetually or the payoff increments. Presently days and assailants executed new strategies for effective working of assault. In this paper, we center around ransomware network assaults and study of discovery procedures for deliver product assault. There are different recognition methods or approaches are accessible for identification of payment product assault. Keywords: Network Security, Malware, Ransomware, Ransomware Detection Techniques

Analysis and Evaluation of Wireless Network Security with the Penetration Testing Execution Standard (PTES)

The use of computer networks in an agency aims to facilitate communication and data transfer between devices. The network that can be applied can be using wireless media or LAN cable. At SMP XYZ, most of the computers still use wireless networks. Based on the findings in the field, it was found that there was no user management problem. Therefore, an analysis and audit of the network security system is needed to ensure that the network security system at SMP XYZ is safe and running well. In conducting this analysis, a tool is needed which will be used as a benchmark to determine the security of the wireless network. The tools used are Penetration Testing Execution Standard (PTES) which is one of the tools to become a standard in analyzing or auditing network security systems in a company in this case, namely analyzing and auditing wireless network security systems. After conducting an analysis based on these tools, there are still many security holes in the XYZ wireless SMP that allow outsiders to illegally access and obtain vulnerabilities in terms of WPA2 cracking, DoS, wireless router password cracking, and access point isolation so that it can be said that network security at SMP XYZ is still not safe

A Sensing Method of Network Security Situation Based on Markov Game Model

The sensing of network security situation (NSS) has become a hot issue. This paper first describes the basic principle of Markov model and then the necessary and sufficient conditions for the application of Markov game model. And finally, taking fuzzy comprehensive evaluation model as the theoretical basis, this paper analyzes the application fields of the sensing method of NSS with Markov game model from the aspects of network randomness, non-cooperative and dynamic evolution. Evaluation results show that the sensing method of NSS with Markov game model is best for financial field, followed by educational field. In addition, the model can also be used in the applicability evaluation of the sensing methods of different industries’ network security situation. Certainly, in different categories, and under the premise of different sensing methods of network security situation, the proportions of various influencing factors are different, and once the proportion is unreasonable, it will cause false calculation process and thus affect the results.

The Compound Prediction Analysis of Information Network Security Situation based on Support Vector Combined with BP Neural Network Learning Algorithm

In order to solve the problem of low security of data in network transmission and inaccurate prediction of future security situation, an improved neural network learning algorithm is proposed in this paper. The algorithm makes up for the shortcomings of the standard neural network learning algorithm, eliminates the redundant data by vector support, and realizes the effective clustering of information data. In addition, the improved neural network learning algorithm uses the order of data to optimize the "end" data in the standard neural network learning algorithm, so as to improve the accuracy and computational efficiency of network security situation prediction.MATLAB simulation results show that the data processing capacity of support vector combined BP neural network is consistent with the actual security situation data requirements, the consistency can reach 98%. the consistency of the security situation results can reach 99%, the composite prediction time of the whole security situation is less than 25s, the line segment slope change can reach 2.3% ,and the slope change range can reach 1.2%,, which is better than BP neural network algorithm.

Network intrusion detection using oversampling technique and machine learning algorithms

The expeditious growth of the World Wide Web and the rampant flow of network traffic have resulted in a continuous increase of network security threats. Cyber attackers seek to exploit vulnerabilities in network architecture to steal valuable information or disrupt computer resources. Network Intrusion Detection System (NIDS) is used to effectively detect various attacks, thus providing timely protection to network resources from these attacks. To implement NIDS, a stream of supervised and unsupervised machine learning approaches is applied to detect irregularities in network traffic and to address network security issues. Such NIDSs are trained using various datasets that include attack traces. However, due to the advancement in modern-day attacks, these systems are unable to detect the emerging threats. Therefore, NIDS needs to be trained and developed with a modern comprehensive dataset which contains contemporary common and attack activities. This paper presents a framework in which different machine learning classification schemes are employed to detect various types of network attack categories. Five machine learning algorithms: Random Forest, Decision Tree, Logistic Regression, K-Nearest Neighbors and Artificial Neural Networks, are used for attack detection. This study uses a dataset published by the University of New South Wales (UNSW-NB15), a relatively new dataset that contains a large amount of network traffic data with nine categories of network attacks. The results show that the classification models achieved the highest accuracy of 89.29% by applying the Random Forest algorithm. Further improvement in the accuracy of classification models is observed when Synthetic Minority Oversampling Technique (SMOTE) is applied to address the class imbalance problem. After applying the SMOTE, the Random Forest classifier showed an accuracy of 95.1% with 24 selected features from the Principal Component Analysis method.

Cyber Attacks Visualization and Prediction in Complex Multi-Stage Network

In network security, various protocols exist, but these cannot be said to be secure. Moreover, is not easy to train the end-users, and this process is time-consuming as well. It can be said this way, that it takes much time for an individual to become a good cybersecurity professional. Many hackers and illegal agents try to take advantage of the vulnerabilities through various incremental penetrations that can compromise the critical systems. The conventional tools available for this purpose are not enough to handle things as desired. Risks are always present, and with dynamically evolving networks, they are very likely to lead to serious incidents. This research work has proposed a model to visualize and predict cyber-attacks in complex, multilayered networks. The calculation will correspond to the cyber software vulnerabilities in the networks within the specific domain. All the available network security conditions and the possible places where an attacker can exploit the system are summarized.

Network Security Policy Automation

Network security policy automation enables enterprise security teams to keep pace with increasingly dynamic changes in on-premises and public/hybrid cloud environments. This chapter discusses the most common use cases for policy automation in the enterprise, and new automation methodologies to address them by taking the reader step-by-step through sample use cases. It also looks into how emerging automation solutions are using big data, artificial intelligence, and machine learning technologies to further accelerate network security policy automation and improve application and network security in the process.

Rule-Based Anomaly Detection Model with Stateful Correlation Enhancing Mobile Network Security

Research on network security technology of industrial control system.

The relationship between industrial control system and Internet is becoming closer and closer, and its network security has attracted much attention. Penetration testing is an active network intrusion detection technology, which plays an indispensable role in protecting the security of the system. This paper mainly introduces the principle of penetration testing, summarizes the current cutting-edge penetration testing technology, and looks forward to its development.

Detection and Prevention of Malicious Activities in Vulnerable Network Security Using Deep Learning

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ACCEPTED PAPERS

Enhancing Load Balancing by Intrusion Detection System Chain on SDN Data Plane Nadia Niknami (Temple University), Jie Wu (Temple University)

HoneyCam: Towards Scalable High-Interaction IoT Camera Honeypot Based on 360 degree Videos Chongqi Guan (Penn State University), Xianda Chen (The Pennsylvania State University), Guohong Cao (The Pennsylvania State University), Sencun Zhu (The Pennsylvania State University), Thomas La Porta (The Pennsylvania State University)

Network-Level Adversaries in Federated Learning Giorgio Severi (Northeastern University), Matthew Jagielski (Google Research), Gokberk Yar (Northeastern University), Yuxuan Wang (LinkedIn Corporation), Alina Oprea (Northeastern University), Cristina Nita-Rotaru (Northeastern University)

Efficient Public Verification of Confidential Supply-Chain Transactions Kilian Becher (Technische Universität Dresden), Mirko Schaefer (Technische Universität Dresden), Axel Schroepfer (SAP AG), Thorsten Strufe (Karlsruhe Institute of Technology)

SysCap: Profiling and Crosschecking Syscall and Capability Configurations for Docker Images Yunlong Xing (George Mason University), Jiahao Cao (Tsinghua University), Xinda Wang (George Mason University), Sadegh Torabi (George Mason University), Kun Sun (George Mason University), Fei Yan (Wuhan University), Qi Li (Tsinghua University)

Securing Communication Against Leaky Switches Leila Rashidi (University of Calgary), Sogand Sadrhaghighi (University of Calgary), Majid Ghaderi (University of Calgary), Cristina Nita-Rotaru (Northeastern University), Reihaneh Safavi-Naini (University of Calgary)

AutoDefense: Reinforcement Learning Based Autoreactive Defense Against Network Attacks Yu Mi (Case Western Reserve University), David Mohaisen (University of Central Florida), An Wang (Case Western Reserve University)

Returning to Port: Efficient Detection of Home Router Devices Thomas Papastergiou (Georgia Institute of Technology), Roberto Perdisci (University of Georgia), Manos Antonakakis (Georgia Tech)

Transferability of Adversarial Examples in Machine Learning-based Malware Detection Yang Hu (Virginia Tech), Ning Wang (Virginia Tech), Yimin Chen (University of Massachusetts Lowell), Wenjing Lou (Virginia Tech), Thomas Hou (Virginia Tech)

On Security of Proof-of-Policy (PoP) in the Execute-Order-Validate Blockchain Paradigm Best Paper Runner-Up Shan Wang (Southeast University), Ming Yang (Southeast University), Bryan Pearson (University of Central Florida), Tingjian Ge (University of Massachusetts, Lowell), Xinwen Fu (University of Massachusetts Lowell), Wei Zhao (Shenzhen Institute of Advanced Technology)

GateKeeper: Operator-centric Trusted App Management Framework on ARM TrustZone Balachandar Gowrisankar (National University of Singapore), Daisuke Mashima (Advanced Digital Sciences Center), Wen Shei Ong (Illinois at Singapore Pte Ltd), Quanqi Ye (Advanced Digital Sciences Center), Ertem Esiner (Advanced Digital Sciences Center), Binbin Chen (Singapore University of Technology and Design), Zbigniew Kalbarczyk (University of Illinois at Urbana Champaign)

Refining Network Message Segmentation with Principal Component Analysis Stephan Kleber (Ulm University), Frank Kargl (Ulm University)

Alexa Skills: Security Vulnerabilities and Countermeasures Dan Su (Beijing Jiaotong University), Jiqiang Liu (Beijing Jiao Tong University), Sencun Zhu (The Pennsylvania State University), Wei Wang (Beijing Jiaotong University), Xiaoyang Wang (Beijing Jiaotong University)

HallMonitor: A Framework for Identifying Network Policy Violations in Software Daniel Olszewski (University of Florida), Patrick Traynor (University of Florida), Kevin Butler (University of Florida), Weidong Zhu (University of Florida), Sandeep Sathyanarayana (University of Florida)

RadioNet: Robust Deep-Learning Based Radio Fingerprinting Haipeng Li (University of Cincinnati), Kaustubh Gupta (University of Nebraska - Lincoln), Chenggang Wang (University of Cincinnati), Nirnimesh Ghose (University of Nebraska - Lincoln), Boyang Wang (University of Cincinnati)

5G Messaging: System Insecurity and Defenses Jinghao Zhao (University of California, Los Angeles), Qianru Li (UCLA), Zengwen Yuan (UCLA), Zhehui Zhang (UCLA), Songwu Lu (UCLA)

MultiEvasion: Evasion Attacks Against Multiple Malware Detectors Hao Liu (University of Cincinnati), Wenhai Sun (Purdue University), Nan Niu (University of Cincinnati), Boyang Wang (University of Cincinnati)

Multi-Protocol IoT Network Reconnaissance Stefan Gvozdenovic (Boston University), Johannes Becker (Boston University), John Mikulskis (Boston University), David Starobinski (Boston University)

Ransomware Detection in Databases through Dynamic Analysis of Query Sequences Christoph Sendner (University of Würzburg), Lukas Iffländer (University of Würzburg), Sebastian Schindler (University of Würzburg), Michael Jobst (University of Würzburg), Alexandra Dmitrienko (University of Würzburg), Samuel Kounev (University of Würzburg)

A Study on the Testing of Android Security Patches Christopher Brant (University of Florida), Tuba Yavuz (University of Florida)

Learning-Based Radio Fingerprinting for RFID Secure Authentication Scheme Jiaqi Xu (The Ohio State University), Xingya Zhao (The Ohio State University), Arjun Bakshi (The Ohio State University), Kannan Srinivasan (The Ohio State University)

DASK: Driving-Assisted Secret Key Establishment Edwin Yang (University of Oklahoma), Song Fang (University of Oklahoma), Dakun Shen (Central Michigan University)

Eolo: IoT Proximity-based Authentication via Pressure Correlated Variations Omar Ibrahim (HBKU - CSE - ICT Division), Gabriele Oligeri (HBKU - CSE - ICT Division), Roberto Di Pietro (Hamad Bin Khalifa University)

An Active Learning Approach to Dynamic Alert Prioritization for Real-time Situational Awareness Yeongwoo Kim (KTH Royal Institute of Technology), György Dán (KTH Royal Institute of Technology)

TrafficSpy: Disaggregating VPN-encrypted IoT Network Traffic for User Privacy Inference Qi Li (Colorado School of Mines), Keyang Yu (Colorado School of Mines), Dong Chen (Colorado School of Mines), Mo Sha (Florida International University), Long Cheng (Clemson University)

Agent-Level Differentially Private Federated Learning via Compressed Model Perturbation  Yuanxiong Guo (University of Texas at San Antonio), Rui Hu (University of Texas at San Antonio), Yanmin Gong (University of Texas at San Antonio)

Securing Wireless Channels: Reliable Shared Secret Extraction through OTFS Usama Saeed (Virginia Tech), Lingjia Liu (Virginia Tech), Kai Zeng (George Mason University), Robert Calderbank (Duke University)

Systematically Analyzing Vulnerabilities in Connection Establishment Phase of Wi-Fi Systems Naureen Hoque (Rochester Institute of Technology), Hanif Rahbari (Rochester Institute of Technology), Cullen Rezendes (Rochester Institute of Technology)

Performant Binary Fuzzing without Source Code using Static Instrumentation Eric Pauley (Pennsylvania State University), Gang Tan (Pennsylvania State University), Danfeng Zhang (Pennsylvania State University), Patrick McDaniel (Pennsylvania State University)

Stealthy Off-Target Coupled-Control-Plane Jamming Shreya Gupta (Rice University), Chia-Yi Yeh (Rice University), Edward Knightly (Rice University)

Membership Inference Attack in Face of Data Transformations Jiyu Chen (University of California, Davis), Yiwen Guo (none), Hao Chen (UC Davis), Neil Gong (Duke University)

SIGTAM: A Tampering Attack on Wi-Fi Preamble Signaling and Countermeasures Zhengguang Zhang (University of Arizona), Marwan Krunz (University of Arizona)

A User-Friendly Two-Factor Authentication Method against Real-Time Phishing Attacks Yuanyi Sun (Pennsylvania State University), Sencun Zhu (The Pennsylvania State University), Yao Zhao (Shape Security), Pengfei Sun (Shape Security)

Supporting Law-Enforcement to Cope with Blacklisted Websites: Framework and Case Study Mir Mehedi Ahsan Pritom (University of Texas at San Antonio), Shouhuai Xu (University of Colorado Colorado Springs)

NL2GDPR: Automatically Develop GDPR Compliant Android Application Features from Natural Language Faysal Hossain Shezan (University of Virginia), Yingjie Lao (Clemson University), Minlong Peng (Baidu Research), Xin Wang (Baidu Research), Mingming Sun (Baidu Research), Ping Li (Baidu Research)

Detecting DNS hijacking by using NetFlow data Martin Fejrskov (Aalborg University), Emmanouil Vasilomanolakis (Technical University of Denmark), Jens Pedersen (Aalborg University)

PRM - Private Interference Discovery for IEEE 802.15.4 Networks Dominik George (Eindhoven University of Technology), Savio Sciancalepore (Eindhoven University of Technology (TU/e))

ACADIA: Efficient and Robust Adversarial Attacks Against Deep Reinforcement Learning Haider Ali (Virginia Tech), Mohannad Al Ameedi (Virginia Tech), Ananthram Swami (Army Research Lab.), Rui Ning (Old Dominion University), Jiang Li (Old Dominion University), Hongyi Wu (The University of Arizona), Jin-Hee Cho (Virginia Tech)

Security Analysis of Mixed RF-FSO Blockage Attack Over Generalized RF Fading and Atmospheric Turbulence Neji Mensi (Howard University), Danda Rawat (Howard University), Chunmei Liu (Howard University)

Tweak: Towards Portable Deep Learning Models for Domain-Agnostic LoRa Device Authentication Jared Gaskin (Oregon State University), Bechir Hamdaoui (Oregon State University), Weng-Keen Wong (Oregon State University)

Absolute Security in High-Frequency Wireless Links Alejandro Cohen (Technion), Rafael D'Oliveira (Clemson University), Chia-Yi Yeh (Rice University), Hichem Guerboukha (Brown University), Rabi Shrestha (Brown University), Zhaoji Fang (Brown University), Edward Knightly (Rice University), Muriel Médard (MIT), Daniel Mittleman (Brown University)

When Third-Party JavaScript Meets Cache: Explosively Amplifying Security Risks on the Internet Tao Hou (University of South Florida), Shengping Bi (New Mexico State University), Mingkui Wei (George Mason University), Tao Wang (New Mexico State University), Zhuo Lu (University of South Florida), Yao Liu (University of South Florida)

Error Prevalence in NIDS datasets: A Case Study on CIC-IDS-2017 and CSE-CIC-IDS-2018 Best Paper Award Lisa Liu (University of New South Wales), Gints Engelen (University of Leuven), Daryl Essam (University of New South Wales at the Australian Defence Force Academy), Timothy Lynar (University of New South Wales at the Australian Defence Force Academy), Wouter Joosen (University of Leuven)

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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...

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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.

network security research papers 2022

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...

network security research papers 2022

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...

network security research papers 2022

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...

A buffer overflow detection and defense method based on RISC-V instruction set extension

Buffer overflow poses a serious threat to the memory security of modern operating systems. It overwrites the contents of other memory areas by breaking through the buffer capacity limit, destroys the system ex...

network security research papers 2022

Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset

In recent years, many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify attacks. The deployment of the unsupervised autoencoder model is computationally exp...

Detecting compromised email accounts via login behavior characterization

The illegal use of compromised email accounts by adversaries can have severe consequences for enterprises and society. Detecting compromised email accounts is more challenging than in the social network field,...

Security estimation of LWE via BKW algorithms

The Learning With Errors (LWE) problem is widely used in lattice-based cryptography, which is the most promising post-quantum cryptography direction. There are a variety of LWE-solving methods, which can be cl...

A convolutional neural network to detect possible hidden data in spatial domain images

Hiding secret data in digital multimedia has been essential to protect the data. Nevertheless, attackers with a steganalysis technique may break them. Existing steganalysis methods have good results with conve...

Optimal monitoring and attack detection of networks modeled by Bayesian attack graphs

Early attack detection is essential to ensure the security of complex networks, especially those in critical infrastructures. This is particularly crucial in networks with multi-stage attacks, where multiple n...

Towards the universal defense for query-based audio adversarial attacks on speech recognition system

Recently, studies show that deep learning-based automatic speech recognition (ASR) systems are vulnerable to adversarial examples (AEs), which add a small amount of noise to the original audio examples. These ...

FMSA: a meta-learning framework-based fast model stealing attack technique against intelligent network intrusion detection systems

Intrusion detection systems are increasingly using machine learning. While machine learning has shown excellent performance in identifying malicious traffic, it may increase the risk of privacy leakage. This p...

MRm-DLDet: a memory-resident malware detection framework based on memory forensics and deep neural network

Cyber attackers have constantly updated their attack techniques to evade antivirus software detection in recent years. One popular evasion method is to execute malicious code and perform malicious actions only...

AppChainer: investigating the chainability among payloads in android applications

Statistics show that more than 80 applications are installed on each android smartphone. Vulnerability research on Android applications is of critical importance. Recently, academic researchers mainly focus on...

Enhancing non-profiled side-channel attacks by time-frequency analysis

Side-channel analysis (SCA) has become an increasing important method to assess the physical security of cryptographic systems. In the process of SCA, the number of attack data directly determines the performa...

An efficient confidentiality protection solution for pub/sub system

Publish/subscribe(pub/sub) systems are widely used in large-scale messaging systems due to their asynchronous and decoupled nature. With the population of pub/sub cloud services, the privacy protection problem...

NBA: defensive distillation for backdoor removal via neural behavior alignment

Recently, deep neural networks have been shown to be vulnerable to backdoor attacks. A backdoor is inserted into neural networks via this attack paradigm, thus compromising the integrity of the network. As soo...

Are our clone detectors good enough? An empirical study of code effects by obfuscation

Clone detection has received much attention in many fields such as malicious code detection, vulnerability hunting, and code copyright infringement detection. However, cyber criminals may obfuscate code to imp...

SkillSim: voice apps similarity detection

Virtual personal assistants (VPAs), such as Amazon Alexa and Google Assistant, are software agents designed to perform tasks or provide services to individuals in response to user commands. VPAs extend their f...

Rainbow: reliable personally identifiable information retrieval across multi-cloud

Personally identifiable information (PII) refers to any information that links to an individual. Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violati...

Reversible data hiding based on histogram and prediction error for sharing secret data

With the advancement of communication technology, a large number of data are constantly transmitted through the internet for various purposes, which are prone to be illegally accessed by third parties. Therefo...

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network security research papers 2022

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Cyberbullying among Saudi’s Higher-Education Students: Implications for Educators and Policymakers by Dr. Abdulrahman M Al-Zahrani

Research paper on cyber security by mrs. ashwini sheth, mr. sachin bhosale, and mr. farish kurupkar, supporting the cyber analytic process using visual history on large displays by ankit singh, alex endert, christopher andrews, lauren bradel, robert kincaid, chris north , issues regarding cybersecurity in modern world by h. geldiyev, m. churiyev, and r. mahmudov, fuzzbuster: towards adaptive immunity from cyber threats by paul robertson, cyberspace in space: fragmentation, vulnerability, and uncertainty by johan eriksson, artificial intelligence in cyber security by matthew n.o. sadiku, omobayode i. fagbohungbe, and sarhan m. musa, women’s awareness of the cyber bullying risk in digital media during the enforcement of the movement control order (mco) by mohd farhan md ariffin and dr. mohammad fahmi abdul hamid, survey on the applications of artificial intelligence in cyber security by shidawa baba atiku, achi unimke aaron, goteng kuwunidi job, fatima shittu, and ismail zahraddeen yakubu, a methodical analysis of medical internet of things (miot) security and privacy in current and future trends by dr. yusuf perwej, dr. nikhat akhtar, neha kulshrestha, and pavan mishra.

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Book cover

  • Conference proceedings
  • © 2024

Cryptology and Network Security with Machine Learning

Proceedings of ICCNSML 2022

  • Bimal Kumar Roy 0 ,
  • Atul Chaturvedi 1 ,
  • Boaz Tsaban 2 ,
  • Sartaj Ul Hasan 3

Applied Statistics Unit, Indian Statistical Institute, Kolkata, India

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Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

Department of mathematics, bar-ilan university, ramat gan, israel, department of mathematics, indian institute of technology jammu, jammu, india.

Presents recent research in the field of cryptology and network security

Discusses the outcomes of ICCNSML 2022, held in Kanpur, India

Serves as a reference guide for researchers and practitioners in academia and industry

Part of the book series: Algorithms for Intelligent Systems (AIS)

Conference series link(s): ICCNSML: International Conference on Cryptology & Network Security with Machine Learning

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Conference proceedings info: ICCNSML 2022.

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Table of contents (38 papers)

Front matter, role and applications of emerging technologies in smart city architecture.

  • Nand Kishore Sharma, Surendra Rahamatkar, Abhishek Singh Rathore

A Review on Blockchain-Based Electronic Health Record (EHR) System for Secure Data Storage

  • Vandani Verma, Garima Thakran

SVM-RF: A Hybrid Machine Learning Model for Detection of Malicious Network Traffic and Files

  • Prashant Mathur, Arjun Choudhary, Chetanya Kunndra, Kapil Pareek, Gaurav Choudhary

Key-Insulated Aggregate Proxy Signature

  • P. V. S. S. N. Gopal, T. Gowri, P. Vasudeva Reddy

A Comprehensive Study of Cryptocurrency Trend Analysis Based on a Novel Machine Learning Technique

  • Paras Sharma, Adhiraj Gupta, Rakesh Kumar Bajaj, Prateek Thakral

Flaws of a Password-Based Three-Party Authenticated Key Agreement Protocol in Post-quantum Environment

  • Sonam Yadav, Vivek Dabra, Pradeep Malik, Saru Kumari

Multivariate Aggregate and Multi-signature Scheme

  • Satyam Omar, Sahadeo Padhye, Dhananjoy Dey

Optical Network Modeling and Performance Using Random Graph Theory

  • Rahul Deo Shukla, Ajay Pratap, Raghuraj Singh Suryavanshi

A Survey on Recent Progress in Blockchain Technology

  • Naseem Ahmad Khan, Prateek Singh, Radiant Ambesh, Md Tarique Jamal Ansari

Cryptanalysis of Lattice-Based Threshold Changeable Multi-secret Sharing Scheme

  • Ramakant Kumar, Sahadeo Padhye

Amazon Web Service IOT and Authentication of Edge Devices

  • Meenakshi Srivastava, Arsh

On Picture Fuzzy Information-Based Hybrid Cryptographic TOPSIS Approach for Best Suitable Cloud Storage and Security Level

  • Himanshu Dhumras, Rakesh Kumar Bajaj, Varun Shukla

Network Layer Performance of Hybrid Buffer-Based Optical Router

  • Sumit Chandra, Shahnaz Fatima, Raghuraj Singh Suryavanshi

Efficient and Secure Data Aggregation for UAV-to-Ground Station Communication in Smart City Environment

  • Girraj Kumar Verma, Dheerendra Mishra, Neeraj Kumar

BBIWMS: A Secure Blockchain-Based Framework for Integrated Water Management System for Smart City

  • B. C Girish Kumar, K. G. Harsha, G. Mahesh, Varun Shukla, Surendra Talari

An Intelligent Network Intrusion Detection Framework for Reliable UAV-Based Communication

  • Sujit Bebortta, Sumanta Kumar Singh

Distributed and Hash-Based Mixers for User Anonymity on Blockchain

  • P. Guna Shekar, Raghwendra Singh, Debanjan Sadhya, Bodhi Chakraborty

Implementation and Analysis of Different Visual Cryptographic Schemes

  • Vanashree Gupta, Smita Bedekar

A New Data Communication Method Using RSA and Steganography

  • Varun Shukla, Manoj Kumar Misra, Shivani Dixit, Himanshu Dhumras

Other Volumes

  • Public Key Cryptography
  • Elliptic Curve Cryptography
  • Post Quantum Cryptography
  • Lattice Based Cryptography
  • Non Commutative Ring Based Cryptography
  • Cryptocurrency
  • Hash Functions
  • Security and Privacy in Machine Learning
  • Block Chain
  • IoT Security
  • Wireless Security Protocols
  • Quantum Computing
  • ICCNSML 2022 Proceedings

Bimal Kumar Roy

Atul Chaturvedi

Boaz Tsaban

Sartaj Ul Hasan

Book Title : Cryptology and Network Security with Machine Learning

Book Subtitle : Proceedings of ICCNSML 2022

Editors : Bimal Kumar Roy, Atul Chaturvedi, Boaz Tsaban, Sartaj Ul Hasan

Series Title : Algorithms for Intelligent Systems

DOI : https://doi.org/10.1007/978-981-99-2229-1

Publisher : Springer Singapore

eBook Packages : Engineering , Engineering (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024

Hardcover ISBN : 978-981-99-2228-4 Published: 18 October 2023

Softcover ISBN : 978-981-99-2231-4 Due: 01 November 2024

eBook ISBN : 978-981-99-2229-1 Published: 17 October 2023

Series ISSN : 2524-7565

Series E-ISSN : 2524-7573

Edition Number : 1

Number of Pages : XII, 470

Number of Illustrations : 77 b/w illustrations, 130 illustrations in colour

Topics : Communications Engineering, Networks , Mobile and Network Security , Cryptology , Professional Computing , Cyber-physical systems, IoT

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  1. Cyber risk and cybersecurity: a systematic review of data availability

    Depending on the amount of data, the extent of the damage caused by a data breach can be significant, with the average cost being USD 392 million Footnote 1 (IBM Security 2020). This research paper reviews the existing literature and open data sources related to cybersecurity and cyber risk, focusing on the datasets used to improve academic ...

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    network security Latest Research Papers | ScienceGate network security Recently Published Documents TOTAL DOCUMENTS 4849 (FIVE YEARS 1231) H-INDEX 45 (FIVE YEARS 8) Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords A Survey on Ransomware Malware and Ransomware Detection Techniques

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    Information technology Cyber-attacks Cyber security Emerging trends Key management 1. Introduction For more than two decades, the Internet has played a significant role in global communication and has become increasingly integrated into the lives of people around the world.

  4. Artificial intelligence for cybersecurity: Literature review and future

    Explores research from 2010 to February 2022 related to AI applications for cybersecurity from a descriptive point of view, and a detailed state-of-the-art analysis ... The article is a full research paper (i.e., not a presentation or supplement to a poster). ... Customized optimal allocation and network security configuration: Planning ...

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    This paper reviews research work done in cybersecurity including the types of cybersecurity. The paper also discusses threats and prevention methods and an overview of future threats in cybersecurity. Published in: 2022 International Conference on Advances in Computing, Communication and Materials (ICACCM) Article #:

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  7. ACCEPTED PAPERS

    ACCEPTED PAPERS. Enhancing Load Balancing by Intrusion Detection System Chain on SDN Data Plane. Nadia Niknami (Temple University), Jie Wu (Temple University) HoneyCam: Towards Scalable High-Interaction IoT Camera Honeypot Based on 360 degree Videos. Chongqi Guan (Penn State University), Xianda Chen (The Pennsylvania State University), Guohong ...

  8. NDSS Symposium 2022: Collaborative Security Research in Action

    The NDSS Symposium 2022 Poster Award winners were Arushi Arora (Purdue University), Sai Raj Karra (Purdue University), Dave Levin (University of Maryland) and Christina Garman (Purdue University), with their poster, Improving the Performance and Security of Tor's Onion Services.

  9. A comprehensive survey on SDN security: threats, mitigations, and

    Nowadays, security threats on Software Defined Network SDN architectures are similar to traditional networks. However, the profile of these threats changes with SDN. For example, a denial-of-service attack on a centralized controller that manages a large network of several network devices (routers, switches, etc.) is more destructive than a targeted attack against a router. A spoofed SDN ...

  10. Full article: Cyber Security and Emerging Technologies

    Firstly, 'technological breakthroughs are transforming the threat landscape by generating new uncertainties and empowering new adversaries' (p. 3). At the same time, 'data volume and accessibility are revolutionizing sense-making' (p. 6). Finally, emerging technologies are imperilling the secrecy that lies at the heart of espionage (p. 7).

  11. Home

    His research interests are in all areas of computer and network security. He has published a monograph and over 260 refereed technical papers. His research has been sponsored by NSF, ARO, AFOSR, DARPA, DHS, DOE, AFRL, NSA, TTC, CISCO, and HP. ... 2022 Usage 284,555 downloads 41 Altmetric mentions . ISSN: 2523-3246 (electronic)

  12. A survey on blockchain technology and its security

    Under a Creative Commons. Blockchain is a technology that has desirable features of decentralization, autonomy, integrity, immutability, verification, fault-tolerance, anonymity, auditability, and transparency. In this paper, we first carry out a deeper survey about blockchain technology, especially its history, consensus algorithms ...

  13. Articles

    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 ... Keya Xu and Guang Cheng. Cybersecurity 2024 7 :1. Research Published on: 1 January 2024.

  14. Cyber Security Challenges and Trends on Recent Technologies

    Cyber Security Challenges and Trends on Recent Technologies Abstract: Protecting data and information systems (such as networking, computing systems, and cloud services, as well as software) is the goal of cyber security.

  15. 2022 IEEE International Conference on Cyber Security and Resilience

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  17. Data Science and Security: Proceedings of IDSCS 2022

    This book presents best selected papers presented at the International Conference on Data Science for Computational Security (IDSCS 2022), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, during 11 - 12 February 2022. The book proposes new technologies and discusses future solutions and ...

  18. Top 10 Cybersecurity Research Papers to Know About in 2022

    Issues regarding cybersecurity in modern world by H. Geldiyev, M. Churiyev, and R. Mahmudov In this paper, the authors try to define such concepts as cyberspace, cybersecurity, as well as assess the degree of danger related to cyber attacks and cyber wars.

  19. Security and privacy protection in cloud computing ...

    With the development of cloud computing, privacy security issues have become increasingly prominent, which is of concern to industry and academia. We review the research progress on privacy security issues from the perspective of several privacy security protection technologies in cloud computing. First, we introduce some privacy security risks ...

  20. Cryptography

    Cryptography. , Volume 6, Issue 1 (March 2022) - 13 articles. Cover Story ( view full-size image ): Anonymous authentication systems have received the attention of many fields, as they secure user privacy. Both group signatures and ring signatures preserve user anonymity, allowing users to hide their identity within a group.

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    Computer Network Security and Technology Research Abstract: The rapid development of computer network system brings both a great convenience and new security threats for users. Network security problem generally includes network system security and data security.

  22. Cryptology and Network Security with Machine Learning

    The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2022), organized by PSIT, Kanpur, India during 16 - 18 December 2022. This conference proceeding will provide the understanding of core concepts of Cryptology & Network Security with ML in data communication.

  23. (PDF) Survey on Wireless Network Security

    Survey on Wireless Network Security To find these threats, sources, and specific areas of the sys tem that may be affected should be known so that the informa rity classification is necessary to...

  24. Gartner Identifies the Top Cybersecurity Trends for 2024

    Generative AI (GenAI), unsecure employee behavior, third-party risks, continuous threat exposure, boardroom communication gaps and identity-first approaches to security are the driving forces behind the top cybersecurity trends for 2024, according to Gartner, Inc. "GenAI is occupying significant headspace of security leaders as another challenge to manage, but also offers an opportunity to ...