Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst themselves.In recent years,this field of resear...Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst themselves.In recent years,this field of research has become increasingly popular due to the host of useful applications it can potentially serve.A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security improvement.The present article takes on one of these two issues namely the throughput enhancement.For the purpose of improving network productivity,a hybrid clustering based packet propagation protocol has been proposed.The protocol makes use of not only clustering mechanisms of machine learning but also utilizes the traditional forwarding function approach to arrive at an optimum model.The result of the simulation is a novel transmission protocol which significantly enhances network productivity and increases throughput value.展开更多
With the evolution of cybersecurity countermeasures,the threat landscape has also evolved,especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware.Fileless malware d...With the evolution of cybersecurity countermeasures,the threat landscape has also evolved,especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware.Fileless malware does not use traditional executables to carry-out its activities.So,it does not use the file system,thereby evading signature-based detection system.The fileless malware attack is catastrophic for any enterprise because of its persistence,and power to evade any anti-virus solutions.The malware leverages the power of operating systems,trusted tools to accomplish its malicious intent.To analyze such malware,security professionals use forensic tools to trace the attacker,whereas the attacker might use anti-forensics tools to erase their traces.This survey makes a comprehensive analysis of fileless malware and their detection techniques that are available in the literature.We present a process model to handle fileless malware attacks in the incident response process.In the end,the specific research gaps present in the proposed process model are identified,and associated challenges are highlighted.展开更多
With the evolution of cybersecurity countermeasures,the threat landscape has also evolved,especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware.Fileless malware d...With the evolution of cybersecurity countermeasures,the threat landscape has also evolved,especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware.Fileless malware does not use traditional executables to carry-out its activities.So,it does not use the file system,thereby evading signature-based detection system.The fileless malware attack is catastrophic for any enterprise because of its persistence,and power to evade any anti-virus solutions.The malware leverages the power of operating systems,trusted tools to accomplish its malicious intent.To analyze such malware,security professionals use forensic tools to trace the attacker,whereas the attacker might use anti-forensics tools to erase their traces.This survey makes a comprehensive analysis of fileless malware and their detection techniques that are available in the literature.We present a process model to handle fileless malware attacks in the incident response process.In the end,the specific research gaps present in the proposed process model are identified,and associated challenges are highlighted.展开更多
文摘Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst themselves.In recent years,this field of research has become increasingly popular due to the host of useful applications it can potentially serve.A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security improvement.The present article takes on one of these two issues namely the throughput enhancement.For the purpose of improving network productivity,a hybrid clustering based packet propagation protocol has been proposed.The protocol makes use of not only clustering mechanisms of machine learning but also utilizes the traditional forwarding function approach to arrive at an optimum model.The result of the simulation is a novel transmission protocol which significantly enhances network productivity and increases throughput value.
文摘With the evolution of cybersecurity countermeasures,the threat landscape has also evolved,especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware.Fileless malware does not use traditional executables to carry-out its activities.So,it does not use the file system,thereby evading signature-based detection system.The fileless malware attack is catastrophic for any enterprise because of its persistence,and power to evade any anti-virus solutions.The malware leverages the power of operating systems,trusted tools to accomplish its malicious intent.To analyze such malware,security professionals use forensic tools to trace the attacker,whereas the attacker might use anti-forensics tools to erase their traces.This survey makes a comprehensive analysis of fileless malware and their detection techniques that are available in the literature.We present a process model to handle fileless malware attacks in the incident response process.In the end,the specific research gaps present in the proposed process model are identified,and associated challenges are highlighted.
文摘With the evolution of cybersecurity countermeasures,the threat landscape has also evolved,especially in malware from traditional file-based malware to sophisticated and multifarious fileless malware.Fileless malware does not use traditional executables to carry-out its activities.So,it does not use the file system,thereby evading signature-based detection system.The fileless malware attack is catastrophic for any enterprise because of its persistence,and power to evade any anti-virus solutions.The malware leverages the power of operating systems,trusted tools to accomplish its malicious intent.To analyze such malware,security professionals use forensic tools to trace the attacker,whereas the attacker might use anti-forensics tools to erase their traces.This survey makes a comprehensive analysis of fileless malware and their detection techniques that are available in the literature.We present a process model to handle fileless malware attacks in the incident response process.In the end,the specific research gaps present in the proposed process model are identified,and associated challenges are highlighted.
