1. KB-IDS

2. Academic Advisor: Dr. Yuval Elovici Technical Advisor: Asaf Shabtai Team Members: Eliya Rahamim Elad Ankry Uri Kanonov

3. Background An IDS is used to detect malicious behaviors that indicates a breach in the security of a computer system The Knowledge-based Temporal-Abstraction (KBTA) method in which a computational mechanism extracts meaningful conclusions from raw time-stamped data and knowledge. Android is an operating system for mobile devices, based on the Linux kernel, developed by Google. It allows development of applications in Java, controlling the phone via Google-developed Java libraries.

4. Problem Domain In the modern age Smartphones as well as the threats they are susceptible to, are a growing trend This strengthens the need for sophisticated defense mechanisms to protect them

5. Current Situation Mobile devices lack the computational strength needed to support PC-like security solutions Android, being an open source and open platform introduces new potential risks and types of attacks Android has some inherent security mechanisms that cannot cope with all possible threats Due to application sandboxing, conventional methods such as AntiVirus are futile. There is a need for a different solution…

6. Proposed Solution - HIDS

7. Knowledge-based Temporal Abstraction Developed by Prof. Yuval Shahar, 1997 Knowledge (KBTA Security ontology) Four inference mechanisms: - Temporal Context Forming - Contemporaneous Abstraction - Temporal Interpolation - Temporal Pattern Matching Higher Level Meaningful Temporal Information: - Contexts - Abstractions - Temporal Patterns Time-Stamped Raw Data: - Primitive Parameters - Events

8. KBTA – cont. Time T1T1 T2T2 T3T3 I1I1 I2I2 TCP Packets Sent ( ) Primitives Abstractions Patterns Worm Pattern Internet Connection Mode Context Contexts Events T0T0 TCP Packets Sent State = HIGH Events ( ) Wi-Fi Connection High Medium Low

9. Func. Requirements - Agent Registration/Login Ability to register with the Control Center. Ability to login to the Control Center and to receive configuration for the various installed components Monitor Every predefined time window, the agent samples state parameters, and counts the number of system/user events that occurred in the time-window. Send monitored data The agent will send the monitored data to the analysis servers and the Control Center at the end of each predefined time window. Receive alerts Ability to receive alerts along with any associated data from the Threat Weighting Unit.

10. Func. Requirements – Analysis Servers Receive and analyze monitored data Ability to receive and analyze the data received from the agent and output a conclusion regarding the existence of a threat Send analysis result Ability to send the analysis result to the Threat Weighting Unit

11. Func. Requirements – KBTA Server KBTA processing Ability to incrementally process the received data according to the KBTA method supporting the following elements: - Primitive - Event - Context - State - Trend - Pattern Configure monitored patterns Ability to set which patterns will be computed and monitored for threat presence

12. Func. Requirements – Threat Weighting Unit Weight Threat Assessments Ability to receive threat assessments (along with any associated data) from multiple local analysis servers and weight them, outputting a single assessment. Alert Ability to dispatch an alert (along with any associated data) to both the agent and the Control Center in case of threat detection

13. Non-Func. Requirements Gathering a feature batch (maximum 40) by the agent should take less than 10 seconds. CPU usage by the HIDS should be under 10% The HIDS should take at most 10MB on the data partition of the device The HIDS will be developed in Java using the Android SDK For demo and testing purposes, a real device will be supplied by DT Labs

15. Collect features, Analyze Data and Weight Assessments Primary actors: Android Description: After a time trigger the agent collects the monitored feature values and sends them to all of the local analysis servers. Each of the servers analyzes the data and outputs a threat assessment. The assessments are weighted by the TWU and if a threat is found, an alert along with any associated data, is dispatched to the agent and the Control Center. Trigger: A time trigger from Android Pre-conditions: The agent is installed on the device and is running Post-conditions: If a threat is found, an alert along with any associated data has been dispatched

18. Risks Risk: The HIDS consumes too much CPU Solution: Reducing the quantity of the features collected by the agent and/or decreasing the collection rate Risk: The HIDS consumes too much memory Solution: Reducing the time frame for keeping raw data in the KBTA’s memory Risk: The HIDS consumes too much bandwidth Solution: Lessening the amount of data transmitted to and from the Control Center

19. The End And so Android lived happily ever after…