## 5 Discussion  
The precise identification of alterations in IP packet headers is of utmost importance for proactive security measures, as such modifications can act as early indicators of potential threats and malicious actions within a network [49]. The prompt detection of these modifications enables prompt intervention, ensuring the preservation of network integrity, the reduction of vulnerabilities, and the prevention of security breaches from progressing into significant events.  
Malicious actors frequently engage in the manipulation of packet headers as a means to conceal their activity. The precise identification of these alterations and the subsequent revelation of concealed attack pathways facilitate the implementation of proactive measures to counter cyberattacks. In addition, the ability to accurately detect possible threats allows for a timely reaction, hence reducing the amount of time that systems are unavailable due to attacks or compromises [50]. This measure guarantees the uninterrupted functioning of essential services and operational procedures. Likewise, complex threats frequently encompass nuanced alterations that elude conventional security protocols. The ability to accurately detect advanced threats is crucial in order to identify them, as they may otherwise remain undetected. Moreover, the precise identification of objects or events offers significant information for a study conducted after an occurrence has occurred. The analysis of modifications by security teams enables the identification of attack patterns,  
Figure 4: The model performance with CNN + LSTM on store-and-forward dataset using ROC.  
tactics, and prospective weaknesses, hence enhancing future defense mechanisms. In conclusion, prompt identification and timely reaction significantly diminish the resources necessary for mitigating security issues. This results in financial savings and the effective allocation of information technology resources.  
The combination of the CICIDS2017 dataset and a store-and-forward dataset extracted from an experimental network can provide various advantages and mitigate specific constraints when investigating attacks associated with the manipulation of \"Flow Duration\" and \"Forward Packets\". In particular, the focus would be on acknowledging the CICIDS2017 dataset as a publicly accessible benchmark dataset that holds significant prominence in the realm of network intrusion detection research [17]. A limited number of scenarios or features can be derived from the dataset as it encompasses a diverse range of attack scenarios and instances of network traffic, as long as the aforementioned features are linked to the store-and-forward dataset derived from this research experimental network. In addition, the examination of attacks that specifically target \"Flow Duration\" and \"Forward Packets\" allows for the intentional incorporation of these modifications into experimental network setups. This measure guarantees the establishment of a study environment that is characterized by enhanced focus and control, specifically targeting these types of attacks. Therefore, this study has undertaken an experimental analysis that integrates two datasets, yielding remarkable results.