Distributed OS: Winter 2011

Evaluation

Grades in this class will be determined based on the following criteria.

Undergraduate Students:

• 20% Class participation
• 20% Wiki participation
• 10% Group project oral presentation
• 30% Group project written report
• 20% Implementation report

Graduate Students:

• 15% Class participation
• 20% Wiki participation
• 10% Group project oral presentation
• 30% Group project written report
• 25% Literature review paper

Readings

January 13, 2011: CCR (two papers)

January 18, 2011: OceanStore and Pond

Internet Governance

Problems to Solve

• Attack computers with almost no consequences
  • DDoS
  • botnets
  • capture and analyze private traffic
  • distribute malware
  • tampering with traffic
  • Unauthorized access to data and resources
  • Impersonate computers, individuals, applications
  • Fraud, theft
  • regulate behavior

Design Principles

• subjects of governance: programs and computers
• bind programs and computers to humans & human organizations, but recognize binding is imperfect
• recognize that "bad" behavior is always possible. "good" behavior is enforced through incentives and sanctions.
• rules will change. Even rules for rule changes will change. Need a "living document" governing how rules are chosen and enforced.

Scenarios

1: Stopping DDoS

Group members: Seyyed, Andrew Schoenrock, Thomas McMahon, Lester Mundt, AbdelRahman, Rakhim Davletkaliyev

• Have the machine routing packets(could be ISP provider) detect suspicious packets, if the packets are signed, then those suspicious packets could be blocked,

the sender could be put on a black list.

• (AS) Stopping DDoS against files, services, programs, etc
  • (AS) Have file replication built into the system (similar to OceanStore) so that files are always available from different servers
  • (AS) If files are not replicated then we could have a tiered messaging system (at the top level would be OS messages) and servers could then prioritize the incoming traffic. If a given server is experiencing an overload, it could send out a distress signal to its neighbours and then distribute what it is has to them. The system should have a built-in mechanism to re-balance the overall load after something like this happens. This would then mean that any DDoS attack would result in the service being more available.
    • I like this idea of having service fallover
    • Expanding on the idea of file replication and sending distress signals to it's neighbours, I could envision a group of servers that would learn to help each other out. Lending processing and storage when they are under utilized. The would sort of form a collective, club or gang. Members who didn't contribute ( always fully utilized ) would eventually be identified and banned. It would be these other computers that the targeted server would rely on for help in this situation. However cool this is it isn' really a solution because one could suppose the attackers might utilize the same strategy to recruit additional help in there attack.

• (AS) Stopping DDoS against specific machines
  • (AS) I don't think that this should be specifically addressed. I think measures introduced to guard against this will ultimately negatively impact the overall system in terms of performance.
    • I don't like the idea of sacrificing the one for the many though.
      • (AS) The main thing with what I've proposed is that the motivation behind doing a DDoS attack is completely gone (by doing one a service would either maintain or increase its overall availability). I think by eliminating the main result of a DDoS attack would mean that there would be no reason to guard against DDoS attacks on a specific machine.

• Stopping DDoS
  • Many of the DDoS attacks utilize the property of anonymity. These services serve anyone who requests there service. Many DDoS attacks then ensure sufficient traffic that the computer behind the service can no longer cope. If we remove anonymity and only serve 'known' parties the spurious requests would be ignored. So we need to 'know' who our friends are.
    • This of course requires a form of unspoofable authentication unlike IP.
      • Serving only 'known' parties reduces the distribution of information, or at least its rate. I was thinking of removing anonymity on a lower level, so that any party that's not anonymous while sending a packet to your machine is considered 'known', and anything unknown (unsigned, unrepresented in some way) is blocked. So, we don't really need to 'know' who our friends are, we just need to know who aren't.
      • Another thing I had in mind is punishment in case a 'known' party participates in DDoS-attack: not punishing the owner of that machine (who probably is a victim as well), but the software or hardware in some sense.

• Stopping DDoS
  • How about developing such a network topology and protocols that make DDoS attacks less efficient or harder to perform? Some sort of CAPTCHA, but for machines and protocols, to distinguish them from bots, maybe?

• Stopping DDoS
  • I'm not sure what it means by stopping, I don't think we can stop DDos given the way things are currently ran, we can only block it. From my knowledge most softwares that stop DDoS do so by blocking, or even complete shut down like Mccolo.

• Stopping DDos
  • One method is to use the same way of eliminating DoS by rejecting a specific rate of subsequent requests but from irrelevant sources.

• How we could stop DDoS would be to have each connection to the internet assigned to a particular identity. This identity would be used to verify who is attempting connections. The reason DDoS works is because currently, IP addresses can be spoofed. The only way to verify an identity is to request a response, but by then the damage is done. With a verified identity, connection attempts being routed can be verified during transmission, so that the request may not necessarily even reach the destination host.

Basically, we need some encryption system using keys so that as the packets are being routed, the identity of the packet's sender can be verified. Ideally the decryption would be trivial so as to prevent noticeable latency. Because an identity is verified, if there is spoofing of packets, they would be dropped during the routing. If all the identities are verified and are still attempting a DDoS attack, the attacker's identity will be traced back to the attacker.

(I think we're not looking low enough. We're trying to find a solution for this problem assuming the system that made that problem possible is still unchanged. We enforce more security by identification, encryption, etc, but the system is still problem-prone. This will allow to identify an attacker, but after the attack was started (or even finished). It's like trying to eliminate theft from a society of poor, unemployed, uneducated people by enforcing more security and punishment. Which will help to reduce the rate and motivation, but can't stop the possible attack. It is pretty stupid analogy, but rather than policing that society, I want to make them rich, employed and educated, so that thefts are just not efficient way of getting goods for them. So, rather than protecting machines from attacks, I want to make the system where DDoS-attacks are just inappropriate.)

2: Stopping phishing

Group members: Waheed Ahmed, Nicolas Lessard, Raghad Al-Awwad, Tarjit Komal

• A way of automatically checking the signature of a message to make sure it really is from a trusted source.
  • ie: "Nation of Banks, did your member TD send me a message to reset my password?"

• There should be filters to ensure where the message is coming from.If the message is coming from unknown source , it should be blocked.
• Don't use the links in an email to get to any web page, if you suspect the message might not be authentic.
• Avoid filling out forms in email messages that ask for personal financial information. Phishers can make exact forms which you can find on financial institution.
• Make is so a machine needs to be authorized to use your information -- A machine that you don't own can't use your information to do anything, regardless of whether he has it or not.
• Ensure that any website that requires the filling of personal information be a secure website which can be traced to the original organisation.
• Ensure that whatever browser you are using is up to date with the most recent security patches applied.
• Obviously, report and suspected phishing to the appropriate authorities so that proper action can be taken
• "three strikes and you're out"
  • Each machine is responsible for the massages it releases. When a machine is a repeat offender it loses access privileges

3: Limiting the spread of malware

Group members: keith, Andrew Luczak, David Barrera, Trevor Gelowsky, Scott Lyons

• (KM) Heterogenous systems - it is much easier to write code to attack a single type of system
• (KM) Individualized security policies
  • (AL) A baseline security level would help prevent malware spreading to/from a system with "individual non-security"
• (KM) Identify all programs through digital signatures
• (KM) Peer rating system for programs, customize security policies based on peer ratings
  • (SL) Need some way to keep rating system from being "gamed"
    • (AL) Maybe a program gets flagged if it experiences a rapid approval increase?
  • (AL) Need to protect against benign programs with good ratings being updated into malware
• (KM) System level forensics on program execution and resource/file modification
• (KM) Customizable user and program blacklists
• (SL) Sandboxing with breach management - know what files have been modified by a process
• (SL) Trending - what does the application spend most of its time doing?

• (DB)Multiple control/chokepoints where malware is looked for. This way, it's more difficult for attackers to take over several control points and for malware to remain unnoticed.
• (DB)Heterogeneous systems help limit the spread of malware too. There's 2 points here. (1) If we're designing this system where we're all masters of our own domains, then we're likely to have different system configurations. However (2), if we want to communicate and interact with other domains, we need some standardized communication layer or mechanism. Standardization is very closely tied to homogeneous.
• (DB)There should be consequences if you harbor malware or if malware originates from within your domain. This could be and incentive to help people be more proactive in terms of security.

4: Bandwidth hogs

Group members: Mike Preston, Fahim Rahman, Michael Du Plessis, Matthew Chou, Ahmad Yafawi

• limit bandwidth for each user
• if user has significant bandwidth demands for a certain period of time
  • add them to a watch list
  • monitor their behaviour
  • divert communication to other hosts that can satisfy requests.
    • if there are no other hosts that can satisfy the request, then distribute data to other idle and capable hosts. Load is now reduced on the one link.
• QoS
• bandwidth management/scheduling (similar to OS scheduling)
  • utilizing a round robin schedule to allow for periodic increases in bandwidth per user
  • priority system that allows for more critical operations being done by a user to take precedence over others
• have the bandwidth separated evenly across all users and allow for users to donate their bandwidth amount for others to use, but can revoke it at any time
• Tiered Bandwidth Distribution
  • The main idea is you get more bandwidth to your machine as much as you give back to the community. Its similar to some trackers and dark net programs in which they wont increase your download speed unless you contribute X amount of Bytes back to your peers.
  • Tier 1, Basic privileges i.e. all machines have minimal bandwidth.
  • Tier n, we define some requirements to be met then we increase bandwidth accordingly.
    • Drop a Tier if machine doesn't maintain the specified requirements of that specific tier.
    • Adv, monitoring bandwidth on the network is cheap while implementing what is stated above is not.
• As a metaphor to our "real world society," bandwidth control can be treated as we do speed for cars.
  • Certain areas need more free flowing traffic, so speed limits are increased. Others require a slower pace which is enforced. These "areas" can be translated to users or programs in our distributed OS model
  • There are repercussions to breaking any of these imposed limits
  • Throttling provides once possible implementation of these constraints