A Hybrid Mitigation Technique for Malicious Network Traffic based on Active Response

Ibor, Ayei E.; Epiphaniou, Gregory

doi:10.14257/ijsia.2015.9.4.08

Cited by 7 publications

(11 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Next, we will present the findings and analysis of the research questions. Watering hole [3,28,79,84,88,99,101,102] Malware [1,3,88,89,[102][103][104][105] Application repackaging [106] Attacks on an Internet-facing server [3,83,89,101] Removable device [3,89,107] Drive-by download [96] Spoofing attack [7,82,108] SQL injection Execution [3,5,82,84,[86][87][88]90,94,97,101,[109][110][111][112][113][114] Zero day, known vulnerability [79,101,115] Remote code execution/Code injection ...…”

Section: Analysis and Findings Of Research Questionsmentioning

confidence: 99%

“…Malware-Malicious software such as spyware, Trojans, and bots are used to carry out unauthorized operations on a targeted system in order to steal information or disrupt the system [87,116,121,144,[172][173][174]; 5.…”

Section: Initial Accessmentioning

confidence: 99%

“…The attackers seek to maintain their foothold through each access, action, or configuration change to the targeted devices [176]. A User to Root (U2R) attack is used to maintain the foothold by gaining root access to the target system [116].…”

Section: Persistencementioning

confidence: 99%

See 2 more Smart Citations

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

Jabar

Singh

2022

Sensors

View full text Add to dashboard Cite

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.

show abstract

Section: Analysis and Findings Of Research Questionsmentioning

confidence: 99%

Section: Initial Accessmentioning

confidence: 99%

See 1 more Smart Citation

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

Jabar

Singh

2022

Sensors

View full text Add to dashboard Cite

show abstract

“…A deep presentation-learning arrangement has also been developed for chance management employing a single symmetric presentation from the asymmetric dataset. The correctness of models was determined to be 91.62 percent [18]. As a solution to this difficulty, an enhanced and effective adversary version will be provided.…”

Section: Proposed Model For Cyber-attack Detection and Mitigation Systemmentioning

confidence: 99%

Novel SHP-ECC Mechanism Architecture for Attack Node Mitigation and to Predict Future Community Intrusions

Prabhu

Nethravathi

2022

IJAEML

View full text Add to dashboard Cite

Purpose: Because of the apparent rapid advancement in the field of information and communication technology and its constant connection to the internet, customer and organizational data have become vulnerable to cyber-attacks, necessitating the explanation of solutions to ensure the security and protection of information throughout the industry. Today, it is critical for governments and major corporations to implement cybersecurity systems to ensure the confidentiality and security of data in the face of cyber-attacks. As community-based fully systems have become more important in today's society, they've become targets for malicious actions, prompting both industry and the research community to place a greater emphasis on resolving community intrusion detection difficulties. In network intrusion detection challenges, gadget examining algorithms have proven to be a valuable tool. Design/Methodology/Approach: This research provided a fully unique architecture for attack node mitigation as a result of the use of a novel type and encryption mechanism. First, the UNSW-NB15 dataset is received and separated into training and testing data. Within the Training section, information is first and foremost pre-processed, and capabilities are extracted. The relevant features are then chosen using the Taxicab Woodpecker Mating algorithm (TWMA). The BRELU-ResNet classifier is then used to classify the attacked and non-attacked data. The typical statistics are encrypted using the ESHP-ECC method, which is then saved in the security log report. Following that, the shortest distance will be calculated using Euclidean distance. Finally, the information is decrypted utilizing a set of ideas known as DSHP-ECC. If the entry appears in the log record while testing, it is marked as attacked statistics and will not be communicated. The method of detecting cyber-assaults will continue if it is not detected. Findings/Result: The analysis is based on the UNSW-NB 15 dataset, which shows that the proposed approach achieves an excessive security level of 93.75 percent. Originality/Value: This experimental-based research article examines the malicious activities in the cyberspace and mitigated by using a SHP-ECC mechanism. Paper Type: Research Article

show abstract

“…al. [22] discusses both misuses and anomaly detection methods while discovering a new cross technique by combining the ideas of J48, Boyer Moore and K-NN algorithms so that it detects the intrusions better, this algorithm is HYBRITQ-4.…”

Section: Literature Surveymentioning

confidence: 99%

Intrusion detection mechanism with machine learning process A case study with FMIFSSVM, FLCFSSVM, misuses SVM, anomaly SVM and Bayesian methods

Murthy¹,

Satyanarayana²

2018

IJET

View full text Add to dashboard Cite

Today, there is a far reaching of Internet benefits everywhere throughout the world, numerous sorts and vast number of security dangers are expanding. Since it isn't in fact possible to assemble a framework without any vulnerability, Intrusion Detection System (IDS), which can successfully distinguish Intrusion, gets to have pulled in consideration. Intrusion detection can be characterized as the way toward distinguishing irregular, unauthorized or unapproved action that objective is to target a system and its assets. IDS plays a very important role for analyzing the network passage, also it assumes a key part to analyze the system activity log and each log is portrayed by huge arrangement of highlights and it requires tremendous computational preparing force and time for the characterization procedure. This work proposes filter based feature selection methods to predict intrusion with Feature based Mutual Information Feature Selection Support Vector Machine (FMIFSSVM), Feature based Liner Correlation Feature Selection Support Vector Machine (FLCFSSVM), misuses SVM, anomaly SVM and Bayesian methods. The performances of these methods are considered by using the intrusion detection calculation data set called Knowledge Discovery in Databases (KDD) cup 99. Detection Rate (DR), False Alarm Rate (FAR) and Percentage of Successful Prediction (PSP) are the major performance measures studied in this work.

show abstract

A Hybrid Mitigation Technique for Malicious Network Traffic based on Active Response

Cited by 7 publications

References 19 publications

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

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

Novel SHP-ECC Mechanism Architecture for Attack Node Mitigation and to Predict Future Community Intrusions

Intrusion detection mechanism with machine learning process A case study with FMIFSSVM, FLCFSSVM, misuses SVM, anomaly SVM and Bayesian methods

Contact Info

Product

Resources

About