It is increasingly common for enterprises and other organizations to outsource network processing to the cloud. For example, enterprises may outsource firewalling, caching, and deep packet inspection, just as they outsource compute and storage. However, this poses a threat to enterprise confidentiality because the cloud provider gains access to the organization’s traffic. We design and build Em...

Machine learning approaches based on decision trees (DTs) have been proposed for classifying networking traffic. Although this technique has been proven to have the ability to classify encrypted and unknown traffic, the software implementation of DT cannot cope with the current speed of packet traffic. In this paper, hardware architecture of decision tree is proposed on NetFPGA platform. The pr...

This paper enhances the data confidentiality and energy saving of an existing solution. Our approach utilizes encrypted message as a key generator (KG) for the next message. Thus, a KG that used to be exposed is now encrypted. A masking policy is incorporated to an encryption technique to further improve the data confidentiality. Furthermore, the proposed method no longer requires a transmissio...

Most tools to recognize the application associated with network connections use well-known signatures as basis for their classification. This approach is very effective in enterprise and campus networks to pinpoint forbidden applications (peer to peer, for instance) or security threats. However, it is easy to use encryption to evade these mechanisms. In particular, Secure Sockets Layer (SSL) li...

Peer-to-Peer (P2P) networks gained their reputation throughout the last decade thanks for breaking down communication barriers while enabling media content exchange in a click of a button. Yet, the complexity of P2P architecture had an unfortunate side-effect in the form of fluctuations in download rate and service fairness issues for the users while becoming a heavy financial burden for Intern...

While web-based applications are becoming increasingly ubiquitous, they also present new security and privacy challenges. In particular, recent research revealed that many high profile Web applications might cause private user information to leak from encrypted traffic due to side-channel attacks exploiting packet sizes and timing. Moreover, existing solutions, such as random padding and packet...

The increasing popularity of specialized Internet-connected devices and appliances, dubbed the Internet-of-Things (IoT), promises both new conveniences and new privacy concerns. Unlike traditional web browsers, many IoT devices have al­ ways-on sensors that constantly monitor fine-grained details of users’ physical environments and influence the devices’ network communications. Passive network ...

The accurate classification of traffic data is challenging for network management and security, especially in imbalanced situations. limitation the existing convolutional neural networks that they have problems such as overfitting, instability, poor generalization when used to classify datasets. In this paper, we propose a new encrypted model. proposed model based on improved block attention mo...