# Report of the 2017 IEEE Cyber Science and Technology Congress
## 5 Cyber Communications and Security  
This section consists of six papers and they are all related to computer and network security in different application areas. We also include three papers from the short paper section here because they are also related to security.  
In [27], [PERSON] et al. reported their experience in the design and implementation of a cyber security testbed for teaching students. This testbed was meant to showcase their authors vision on how an educational testbed ought to be built. They believe the testbeds should facilitate a wide range of audience to learn cyber security skills.  
In [28], [PERSON] et al. proposed a novel malware detection method for the Android platform based on extreme learning machine. The method detects malware based on the sensitive permissions and sensitive application programming interface calls. They validated their approach with a testing tool named WaffleDetector. In [29], [PERSON] and [PERSON] analyzed the details of HTTP spectral Hijacking attack and proposed a mechanism to detect such attacks.  
In [30], [PERSON] et al. presented a reliability study on the distributed advanced metering infrastructure (AMI) for smart grid. The identified the reliability issues in AMI and outlined two solutions. They proposed a mathematical model that ensures good overall network reliability, and validated their approach via simulation.  
In [31], [PERSON] et al. proposed an interference management mechanism for physical layer security in a two-tier heterogeneous network (HetNet). The study considers an eavesdropping attack where there are several users of the HetNet and one eavesdropper. The objective of the mechanism is to maximize the secrecy rate of users under the eavesdropping attack.  
In [32], [PERSON] et al. proposed a novel content caching framework for mobile edge networks. The framework relies on the data collected from users' mobile devices, which are used to infer user preferences on communicational and computational tasks. The framework consists of an ambient data collection scheme and an application predication scheme. The latter is critical to predict the application that a user is likely to launch and the corresponding content will be needed for the application launch, and therefore the content can be prefetched.  
In [33], [PERSON] et al. addressed the security concerns of a green roof monitoring system, which consists of numerous Internet of Things (IoT). They experimented with several authentication and credential update schemes to ensure proper access control to the system. In [34], [PERSON] et al. proposed the use of a randomly switching controller to counter the active system identification attacks. Such attacks are often launched to gain insight to the target system models prior to attacks that might comprise the system.  
Contrary to most other research that focuses on the detection of security attacks and defense mechanisms, in [35], [PERSON] et al. presented a study on the attackers themselves. They argued that it is time to revise the traditional model on cyber criminals, which captures the attacker's \"skills, knowledge, resources, access to the target organization and motivation to offend\" (or SKRAM for short). They proposed a revised SKRAM model that considers the attacker's online circumstances.